1 | Country Name | Country Code | Series Name | Series Code | 1997 [YR1997] | 1998 [YR1998] | 1999 [YR1999] | 2000 [YR2000] | 2001 [YR2001] | 2002 [YR2002] | 2003 [YR2003] | 2004 [YR2004] | 2005 [YR2005] | 2006 [YR2006] | 2007 [YR2007] | 2008 [YR2008] | 2009 [YR2009] | 2010 [YR2010] | 2011 [YR2011] | 2012 [YR2012] | 2013 [YR2013] | 2014 [YR2014] | 2015 [YR2015] | 2016 [YR2016] | 2017 [YR2017] | 2018 [YR2018] | 2019 [YR2019] | 2020 [YR2020] | 2021 [YR2021] |
---|
2 | Benin | BEN | Adequacy of social insurance programs (% of total welfare of beneficiary households) | per_si_allsi.adq_pop_tot | .. | .. | .. | .. | .. | .. | 39.4935883219468 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
3 | Benin | BEN | Adequacy of social protection and labor programs (% of total welfare of beneficiary households) | per_allsp.adq_pop_tot | .. | .. | .. | .. | .. | .. | 39.4935883219468 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
4 | Benin | BEN | Adequacy of social safety net programs (% of total welfare of beneficiary households) | per_sa_allsa.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
5 | Benin | BEN | Adequacy of unemployment benefits and ALMP (% of total welfare of beneficiary households) | per_lm_alllm.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
6 | Benin | BEN | Adjusted net national income (annual % growth) | NY.ADJ.NNTY.KD.ZG | 7.460076894498769 | 4.1488429126705455 | 10.642323188506552 | 8.783816959373695 | 7.515878476376599 | 8.281848698089632 | 5.118679760267611 | 6.5949077140947026 | 0.612001105702987 | 3.8514044536322274 | 5.561371164219736 | 5.268831202594626 | 2.3055405356641643 | 1.94547552773507 | 4.798355271718947 | 6.285692089732592 | 10.005816434423664 | 6.268409687834264 | 3.2625503876265753 | 4.484886262378126 | 3.6839093626205965 | 6.288557458163041 | 7.964898457719656 | 3.0223722710386056 | .. |
7 | Benin | BEN | Adjusted net national income (constant 2015 US$) | NY.ADJ.NNTY.KD | 3808265840.898681 | 3966264808.3344593 | 4388367527.749413 | 4773833698.891514 | 5132629238.364514 | 5557705826.119774 | 5842186989.376579 | 6227473829.810812 | 6265586038.5066185 | 6506899098.239821 | 6868771908.374205 | 7230675905.917679 | 7397382069.931113 | 7541296327.794685 | 7903154517.695371 | 8399922476.053493 | 9240403299.6413 | 9819629635.270973 | 10140000000 | 10594767467.005142 | 10985069097.670025 | 11675871479.695915 | 12605842787.107544 | 12986838284.035803 | .. |
8 | Benin | BEN | Adjusted net national income (current US$) | NY.ADJ.NNTY.CD | 1655000000 | 1816000000 | 2906000000 | 2810000000 | 3003000000 | 3511000000 | 4521000000 | 5259000000 | 5627000000 | 6025000000 | 7014000000 | 8416000000 | 8298000000 | 8093000000 | 9176000000 | 9660000000 | 11030000000 | 11770000000 | 10140000000 | 10530000000 | 11210000000 | 12580000000 | 12670000000 | 13740000000 | .. |
9 | Benin | BEN | Adjusted net national income per capita (annual % growth) | NY.ADJ.NNTY.PC.KD.ZG | 4.25470429970099 | 1.1125422318710463 | 7.424264764932204 | 5.5858074279343555 | 4.313492868648353 | 5.036213308870586 | 1.971558528791789 | 3.439053220841487 | -2.315017958631131 | 0.885464762908029 | 2.591133758458696 | 2.3381120044734303 | -0.5286597716745263 | -0.8753296469350857 | 1.9008681931342153 | 3.3533257542266597 | 6.9783071224961475 | 3.3526716955955607 | 0.43958465120262247 | 1.6391527470782847 | 0.8715490375364539 | 3.4211072929254556 | 5.07285582214449 | 0.28563185627585597 | .. |
10 | Benin | BEN | Adjusted net national income per capita (constant 2015 US$) | NY.ADJ.NNTY.PC.KD | 606.2530510959681 | 612.9978723214175 | 658.5084573659606 | 695.2914716910843 | 725.2828197387994 | 761.8096096334367 | 776.82913196532 | 803.5446992486083 | 784.9424951553744 | 791.8928843590663 | 812.4118882165263 | 831.4069881006861 | 827.0116738157069 | 819.7725954511839 | 835.3553919741463 | 863.3675794725364 | 923.6160207641909 | 954.581833668338 | 958.7780288923126 | 974.4938652912841 | 982.9870571950822 | 1016.6160990972962 | 1068.1875680692115 | 1071.2386520483954 | .. |
11 | Benin | BEN | Adjusted net national income per capita (current US$) | NY.ADJ.NNTY.PC.CD | 263.4660607955497 | 280.66813234367936 | 436.0677552654506 | 409.26625406025624 | 424.3486537846304 | 481.26216519998906 | 601.1523616073067 | 678.5803824850133 | 704.9414680597122 | 733.2455223647187 | 829.5889075896622 | 967.6994658450726 | 927.6988540604937 | 879.7452489082267 | 969.8938644805862 | 992.8818797412422 | 1102.493514479448 | 1144.180442602436 | 958.7780288923126 | 968.5366322077338 | 1003.1147563281239 | 1095.3384121162887 | 1073.6240897180282 | 1133.3643152574098 | .. |
12 | Benin | BEN | Adjusted net savings, excluding particulate emission damage (% of GNI) | NY.ADJ.SVNX.GN.ZS | -7.8563738 | -7.9152741 | -6.3923992 | -5.2833986 | -2.7004878 | -0.3975237 | -1.5541854 | 1.2348543 | 0.77333878 | 0.67165407 | 2.333743 | 1.4537194 | -0.05124708 | 0.05147239 | 1.466368 | 4.2638314 | 8.3423977 | 10.842891 | 4.796483 | 8.1240124 | 7.5772256 | 9.7765162 | 11.367239 | .. | .. |
13 | Benin | BEN | Adjusted net savings, excluding particulate emission damage (current US$) | NY.ADJ.SVNX.CD | -175900000 | -193300000 | -234300000 | -185300000 | -98611918 | -16561117 | -82544016 | 75983096 | 50652832 | 47041791 | 189500000 | 142100000 | -4973784.8 | 4880513.4 | 156600000 | 472200000 | 1039000000 | 1434000000 | 541800000 | 952000000 | 951800000 | 1379000000 | 1620000000 | .. | .. |
14 | Benin | BEN | Adjusted net savings, including particulate emission damage (% of GNI) | NY.ADJ.SVNG.GN.ZS | -11.81893 | -11.620987 | -9.8926358 | -8.6533954 | -5.9602956 | -3.6292742 | -4.7421801 | -1.9218607 | -2.3445833 | -2.3496343 | -0.54236603 | -1.3409455 | -2.8717367 | -2.7892416 | -1.3388214 | 1.5071753 | 5.7536198 | 8.3991596 | 2.2765619 | 5.6249858 | 5.1581021 | 7.524271 | 9.2280612 | .. | .. |
15 | Benin | BEN | Adjusted net savings, including particulate emission damage (current US$) | NY.ADJ.SVNG.CD | -264600000 | -283700000 | -362600000 | -303500000 | -217600000 | -151200000 | -251900000 | -118300000 | -153600000 | -164600000 | -44042970 | -131100000 | -278700000 | -264500000 | -143000000 | 166900000 | 716300000 | 1111000000 | 257200000 | 659200000 | 647900000 | 1061000000 | 1315000000 | .. | .. |
16 | Benin | BEN | Adjusted savings: carbon dioxide damage (% of GNI) | NY.ADJ.DCO2.GN.ZS | 0.91768323 | 0.91452214 | 0.69041468 | 0.81902865 | 0.98129066 | 1.0272022 | 0.94891348 | 0.90691805 | 0.98732206 | 1.3462082 | 1.4035137 | 1.1974573 | 1.3382211 | 1.5382325 | 1.3892496 | 1.3382896 | 1.3060932 | 1.4049983 | 1.8491761 | 2.211708 | 2.1923467 | 2.1970357 | 2.4567584 | 2.4787804 | .. |
17 | Benin | BEN | Adjusted savings: carbon dioxide damage (current US$) | NY.ADJ.DCO2.CD | 20542169 | 22329912 | 25304050 | 28729015 | 35833139 | 42793965 | 50397546 | 55804513 | 64668499 | 94286698 | 114000000 | 117100000 | 129900000 | 145900000 | 148300000 | 148200000 | 162600000 | 185800000 | 208900000 | 259200000 | 275400000 | 309900000 | 350000000 | 383900000 | .. |
18 | Benin | BEN | Adjusted savings: consumption of fixed capital (% of GNI) | NY.ADJ.DKAP.GN.ZS | 18.157611 | 18.105248 | 17.504345 | 16.535564 | 15.997088 | 15.199311 | 14.858532 | 14.524671 | 14.082907 | 13.979484 | 13.620828 | 13.914113 | 14.50512 | 14.649934 | 14.059719 | 12.769928 | 11.41334 | 10.989202 | 10.2238 | 10.114359 | 10.688633 | 10.72171 | 10.965227 | 11.249337 | .. |
19 | Benin | BEN | Adjusted savings: consumption of fixed capital (current US$) | NY.ADJ.DKAP.CD | 406500000 | 442100000 | 641500000 | 580000000 | 584200000 | 633200000 | 789100000 | 893700000 | 922400000 | 979100000 | 1106000000 | 1360000000 | 1408000000 | 1389000000 | 1501000000 | 1414000000 | 1421000000 | 1453000000 | 1155000000 | 1185000000 | 1343000000 | 1512000000 | 1562000000 | 1742000000 | .. |
20 | Benin | BEN | Adjusted savings: education expenditure (% of GNI) | NY.ADJ.AEDU.GN.ZS | 2.7130914 | 2.7196042 | 2.52 | 2.69 | 2.71 | 2.65 | 2.82 | 3.33 | 3.62 | 3.48 | 3.23 | 3.91 | 4.3 | 4.79 | 4.775 | 4.76 | 4.69 | 4.55 | 2.9331393 | 2.9331393 | 2.9331393 | 2.9331393 | 2.9331393 | 2.9331393 | .. |
21 | Benin | BEN | Adjusted savings: education expenditure (current US$) | NY.ADJ.AEDU.CD | 60732049 | 66404651 | 92359284 | 94356956 | 98959269 | 110400000 | 149800000 | 204900000 | 237100000 | 243700000 | 262300000 | 382300000 | 417300000 | 454200000 | 509900000 | 527200000 | 583900000 | 601700000 | 331300000 | 343700000 | 368400000 | 413700000 | 417900000 | 454300000 | .. |
22 | Benin | BEN | Adjusted savings: energy depletion (% of GNI) | NY.ADJ.DNGY.GN.ZS | 0.08659066 | 0.03937341 | 0.05772929 | 0.07477026 | 0.04941262 | 0.05319417 | 0.01449184 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.03924884 | 0.03795196 | 0.06833618 | 0.09225986 | 0.08206466 | 0.03883475 | .. |
23 | Benin | BEN | Adjusted savings: energy depletion (current US$) | NY.ADJ.DNGY.CD | 1938315.8 | 961381.57 | 2115807.9 | 2622711.5 | 1804367.7 | 2216106.6 | 769673.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4433408.5 | 4447327.7 | 8583992.2 | 13014145 | 11692738 | 6015050.7 | .. |
24 | Benin | BEN | Adjusted savings: gross savings (% of GNI) | NY.ADJ.ICTR.GN.ZS | 16.403499 | 15.885212 | 12.498482 | 12.728348 | 13.331974 | 13.705673 | 11.448099 | 13.336726 | 12.223996 | 12.518683 | 14.129116 | 12.656423 | 11.493484 | 11.451556 | 12.143275 | 13.614717 | 16.37343 | 18.688322 | 13.975569 | 17.554892 | 17.593402 | 19.854382 | 21.93815 | .. | .. |
25 | Benin | BEN | Adjusted savings: mineral depletion (% of GNI) | NY.ADJ.DMIN.GN.ZS | 0 | 0.02866775 | 0.00037464 | 0 | 0.00061317 | 0.00121215 | 0.00034751 | 0.00028287 | 0.00042801 | 0.00133693 | 0.00103137 | 0.00113241 | 0.00139054 | 0.00191784 | 0.00293903 | 0.00266813 | 0.00159958 | 0.00123001 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
26 | Benin | BEN | Adjusted savings: mineral depletion (current US$) | NY.ADJ.DMIN.CD | 0 | 699981.25 | 13730.818 | 0 | 22390.736 | 50498.914 | 18456.266 | 17405.569 | 28034.224 | 93636.926 | 83752.299 | 110709.05 | 134958.37 | 181845.83 | 313824.21 | 295484.89 | 199129.36 | 162647.7 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
27 | Benin | BEN | Adjusted savings: natural resources depletion (% of GNI) | NY.ADJ.DRES.GN.ZS | 7.8976694599999995 | 7.50031976 | 3.21612203 | 3.34715446 | 1.76408309 | 0.52668388 | 0.014839350000000001 | 0.00028287 | 0.00042801 | 0.00133693 | 0.00103137 | 0.00113241 | 0.00139054 | 0.00191784 | 0.00293903 | 0.00266813 | 0.00159958 | 0.00123001 | 0.03924884 | 0.03795196 | 0.06833618 | 0.09225986 | 0.08206466 | 0.03883475 | .. |
28 | Benin | BEN | Adjusted savings: net forest depletion (% of GNI) | NY.ADJ.DFOR.GN.ZS | 7.8110788 | 7.4322786 | 3.1580181 | 3.2723842 | 1.7140573 | 0.47227756 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
29 | Benin | BEN | Adjusted savings: net forest depletion (current US$) | NY.ADJ.DFOR.CD | 174800000 | 181500000 | 115700000 | 114800000 | 62591090 | 19675416 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
30 | Benin | BEN | Adjusted savings: net national savings (% of GNI) | NY.ADJ.NNAT.GN.ZS | -1.7541125 | -2.2200364 | -5.0058625 | -3.8072154 | -2.6651141 | -1.4936377 | -3.4104326 | -1.1879448 | -1.8589112 | -1.4608008 | 0.5082881 | -1.2576909 | -3.0116355 | -3.1983773 | -1.9164433 | 0.84478913 | 4.9600904 | 7.6991198 | 3.7517687 | 7.4405331 | 6.9047692 | 9.1326725 | 10.972923 | .. | .. |
31 | Benin | BEN | Adjusted savings: net national savings (current US$) | NY.ADJ.NNAT.CD | -39265483 | -54206691 | -183500000 | -133500000 | -97320200 | -62225996 | -181100000 | -73096661 | -121800000 | -102300000 | 41275663 | -123000000 | -292300000 | -303300000 | -204600000 | 93557222 | 617500000 | 1018000000 | 423800000 | 871900000 | 867300000 | 1288000000 | 1563000000 | .. | .. |
32 | Benin | BEN | Adjusted savings: particulate emission damage (% of GNI) | NY.ADJ.DPEM.GN.ZS | 3.962556 | 3.7057132 | 3.5002366 | 3.3699968 | 3.2598078 | 3.2317505 | 3.1879947 | 3.156715 | 3.1179221 | 3.0212884 | 2.876109 | 2.7946649 | 2.8204897 | 2.840714 | 2.8051894 | 2.7566561 | 2.5887779 | 2.4437319 | 2.519921 | 2.4990266 | 2.4191234 | 2.2522453 | 2.139178 | 2.0635697 | .. |
33 | Benin | BEN | Adjusted savings: particulate emission damage (current US$) | NY.ADJ.DPEM.CD | 88701082 | 90482501 | 128300000 | 118200000 | 119000000 | 134600000 | 169300000 | 194200000 | 204200000 | 211600000 | 233600000 | 273200000 | 273700000 | 269400000 | 299500000 | 305300000 | 322300000 | 323100000 | 284600000 | 292800000 | 303900000 | 317700000 | 304800000 | 319600000 | .. |
34 | Benin | BEN | Agriculture, forestry, and fishing, value added (annual % growth) | NV.AGR.TOTL.KD.ZG | 6.083006752761392 | 5.246946549090879 | 5.982777428264384 | 4.570041300937831 | 8.74080530160822 | 3.037345065464251 | 1.7739885597203084 | 7.118103039707037 | 1.426646302700945 | 7.067705607612339 | 6.03157949139927 | 2.0955690772555045 | 7.7823524832687525 | -0.8338778557617985 | 0.9518949108689156 | 5.4444408498339385 | 6.1095239574537885 | 8.257282707352687 | 0.022744418812919776 | 8.966194504004093 | 7.564112603053431 | 7.329068917347996 | 5.159579593200931 | 1.7533296607470845 | .. |
35 | Benin | BEN | Agriculture, forestry, and fishing, value added (constant 2015 US$) | NV.AGR.TOTL.KD | 1372701953.2935493 | 1444726891.0611882 | 1531161685.3996627 | 1601136406.8065631 | 1741088622.7386904 | 1793971492.1068034 | 1825796341.1414218 | 1955758405.9990692 | 1983660160.988018 | 2123859421.4221401 | 2251961690.710789 | 2299153103.5329647 | 2478081302.179913 | 2457417130.953261 | 2480809159.561626 | 2615875346.851221 | 2775692877.864224 | 3004889685.8773265 | 3005573130.5723486 | 3275058663.41955 | 3522787788.536661 | 3780975333.3704324 | 3976057765.094974 | 4045771165.218822 | .. |
36 | Benin | BEN | Agriculture, forestry, and fishing, value added per worker (constant 2015 US$) | NV.AGR.EMPL.KD | 1126.2916443183994 | 1155.9865032555165 | 1198.3674013893465 | 1226.684844192859 | 1307.6616275145896 | 1319.815679088329 | 1309.7511120902832 | 1369.5684958695006 | 1354.669726935603 | 1422.7836227189955 | 1484.2465339358514 | 1490.0594340761584 | 1577.7477798931047 | 1535.2728553281547 | 1549.2770083844466 | 1606.4001212415449 | 1683.3039468511593 | 1796.2675315189167 | 1760.6038451816657 | 1881.7264858736896 | 1996.3663114326446 | 2117.9377553591444 | 2203.838507313441 | .. | .. |
37 | Benin | BEN | Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%) | SI.SPR.PC40.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -5.19 | .. | .. | .. | .. | .. | .. |
38 | Benin | BEN | Annualized average growth rate in per capita real survey mean consumption or income, total population (%) | SI.SPR.PCAP.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.07 | .. | .. | .. | .. | .. | .. |
39 | Benin | BEN | Average working hours of children, study and work, ages 7-14 (hours per week) | SL.TLF.0714.SW.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
40 | Benin | BEN | Average working hours of children, study and work, female, ages 7-14 (hours per week) | SL.TLF.0714.SW.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.2 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
41 | Benin | BEN | Average working hours of children, study and work, male, ages 7-14 (hours per week) | SL.TLF.0714.SW.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
42 | Benin | BEN | Average working hours of children, working only, ages 7-14 (hours per week) | SL.TLF.0714.WK.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
43 | Benin | BEN | Average working hours of children, working only, female, ages 7-14 (hours per week) | SL.TLF.0714.WK.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 15.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
44 | Benin | BEN | Average working hours of children, working only, male, ages 7-14 (hours per week) | SL.TLF.0714.WK.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 25.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
45 | Benin | BEN | Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits) | per_si_allsi.ben_q1_tot | .. | .. | .. | .. | .. | .. | 2.46715882110261 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
46 | Benin | BEN | Benefit incidence of social protection and labor programs to poorest quintile (% of total SPL benefits) | per_allsp.ben_q1_tot | .. | .. | .. | .. | .. | .. | 2.46715882110261 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
47 | Benin | BEN | Benefit incidence of social safety net programs to poorest quintile (% of total safety net benefits) | per_sa_allsa.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
48 | Benin | BEN | Benefit incidence of unemployment benefits and ALMP to poorest quintile (% of total U/ALMP benefits) | per_lm_alllm.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
49 | Benin | BEN | Child employment in agriculture (% of economically active children ages 7-14) | SL.AGR.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
50 | Benin | BEN | Child employment in agriculture, female (% of female economically active children ages 7-14) | SL.AGR.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
51 | Benin | BEN | Child employment in agriculture, male (% of male economically active children ages 7-14) | SL.AGR.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
52 | Benin | BEN | Child employment in manufacturing (% of economically active children ages 7-14) | SL.MNF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
53 | Benin | BEN | Child employment in manufacturing, female (% of female economically active children ages 7-14) | SL.MNF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
54 | Benin | BEN | Child employment in manufacturing, male (% of male economically active children ages 7-14) | SL.MNF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
55 | Benin | BEN | Child employment in services (% of economically active children ages 7-14) | SL.SRV.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
56 | Benin | BEN | Child employment in services, female (% of female economically active children ages 7-14) | SL.SRV.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
57 | Benin | BEN | Child employment in services, male (% of male economically active children ages 7-14) | SL.SRV.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
58 | Benin | BEN | Children in employment, female (% of female children ages 7-14) | SL.TLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 76.1 | .. | .. | .. | .. | .. | 23.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
59 | Benin | BEN | Children in employment, male (% of male children ages 7-14) | SL.TLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 72.8 | .. | .. | .. | .. | .. | 24.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
60 | Benin | BEN | Children in employment, self-employed (% of children in employment, ages 7-14) | SL.SLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
61 | Benin | BEN | Children in employment, self-employed, female (% of female children in employment, ages 7-14) | SL.SLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
62 | Benin | BEN | Children in employment, self-employed, male (% of male children in employment, ages 7-14) | SL.SLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
63 | Benin | BEN | Children in employment, study and work (% of children in employment, ages 7-14) | SL.TLF.0714.SW.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 63.9 | .. | .. | .. | .. | .. | 67.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
64 | Benin | BEN | Children in employment, study and work, female (% of female children in employment, ages 7-14) | SL.TLF.0714.SW.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 63.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
65 | Benin | BEN | Children in employment, study and work, male (% of male children in employment, ages 7-14) | SL.TLF.0714.SW.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 71.2 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
66 | Benin | BEN | Children in employment, total (% of children ages 7-14) | SL.TLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 74.4 | .. | .. | .. | .. | .. | 24.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
67 | Benin | BEN | Children in employment, unpaid family workers (% of children in employment, ages 7-14) | SL.FAM.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 80.48 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
68 | Benin | BEN | Children in employment, unpaid family workers, female (% of female children in employment, ages 7-14) | SL.FAM.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 80.57 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
69 | Benin | BEN | Children in employment, unpaid family workers, male (% of male children in employment, ages 7-14) | SL.FAM.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 80.39 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
70 | Benin | BEN | Children in employment, wage workers (% of children in employment, ages 7-14) | SL.WAG.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.79 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
71 | Benin | BEN | Children in employment, wage workers, female (% of female children in employment, ages 7-14) | SL.WAG.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.42 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
72 | Benin | BEN | Children in employment, wage workers, male (% of male children in employment, ages 7-14) | SL.WAG.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.14 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
73 | Benin | BEN | Children in employment, work only (% of children in employment, ages 7-14) | SL.TLF.0714.WK.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 36.1 | .. | .. | .. | .. | .. | 32.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
74 | Benin | BEN | Children in employment, work only, female (% of female children in employment, ages 7-14) | SL.TLF.0714.WK.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 36.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
75 | Benin | BEN | Children in employment, work only, male (% of male children in employment, ages 7-14) | SL.TLF.0714.WK.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 28.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
76 | Benin | BEN | Community health workers (per 1,000 people) | SH.MED.CMHW.P3 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
77 | Benin | BEN | Contributing family workers, female (% of female employment) (modeled ILO estimate) | SL.FAM.WORK.FE.ZS | 22.2700004577637 | 22.6299991607666 | 21.7800006866455 | 21.6100006103516 | 20.5400009155273 | 20.2700004577637 | 19.9500007629395 | 20.5900001525879 | 20.0400009155273 | 20.3999996185303 | 20.9899997711182 | 22.0300006866455 | 21.6299991607666 | 21.0799999237061 | 21.2099990844727 | 21.5100002288818 | 21.0100002288818 | 20.2800006866455 | 18.9099998474121 | 19.6200008392334 | 18.25 | 17.8700008392334 | 16.3600006103516 | .. | .. |
78 | Benin | BEN | Contributing family workers, male (% of male employment) (modeled ILO estimate) | SL.FAM.WORK.MA.ZS | 17.7299995422363 | 17.6800003051758 | 16.9300003051758 | 16.5699996948242 | 15.7399997711182 | 15.3299999237061 | 14.8599996566772 | 14.8599996566772 | 14.2200002670288 | 14 | 13.9399995803833 | 14.1000003814697 | 13.5900001525879 | 13 | 12.7399997711182 | 12.539999961853 | 12.1000003814697 | 11.6499996185303 | 10.8800001144409 | 10.9399995803833 | 10.210000038147 | 9.90999984741211 | 9.22999954223633 | .. | .. |
79 | Benin | BEN | Contributing family workers, total (% of total employment) (modeled ILO estimate) | SL.FAM.WORK.ZS | 19.7399997711182 | 19.8999996185303 | 19.1399993896484 | 18.8899993896484 | 17.9799995422363 | 17.6599998474121 | 17.2800006866455 | 17.6000003814697 | 17.0200004577637 | 17.1100006103516 | 17.3899993896484 | 18 | 17.5699996948242 | 17.0200004577637 | 16.8899993896484 | 16.9300003051758 | 16.4599990844727 | 15.8800001144409 | 14.8199996948242 | 15.1999998092651 | 14.1499996185303 | 13.8199996948242 | 12.7399997711182 | .. | .. |
80 | Benin | BEN | Coverage of social insurance programs (% of population) | per_si_allsi.cov_pop_tot | .. | .. | .. | .. | .. | .. | 6.62698090721438 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
81 | Benin | BEN | Coverage of social insurance programs in 2nd quintile (% of population) | per_si_allsi.cov_q2_tot | .. | .. | .. | .. | .. | .. | 3.53466922326565 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
82 | Benin | BEN | Coverage of social insurance programs in 3rd quintile (% of population) | per_si_allsi.cov_q3_tot | .. | .. | .. | .. | .. | .. | 6.61650964344154 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
83 | Benin | BEN | Coverage of social insurance programs in 4th quintile (% of population) | per_si_allsi.cov_q4_tot | .. | .. | .. | .. | .. | .. | 7.18552810158589 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
84 | Benin | BEN | Coverage of social insurance programs in poorest quintile (% of population) | per_si_allsi.cov_q1_tot | .. | .. | .. | .. | .. | .. | 3.60006406603271 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
85 | Benin | BEN | Coverage of social insurance programs in richest quintile (% of population) | per_si_allsi.cov_q5_tot | .. | .. | .. | .. | .. | .. | 12.1946319212424 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
86 | Benin | BEN | Coverage of social protection and labor programs (% of population) | per_allsp.cov_pop_tot | .. | .. | .. | .. | .. | .. | 6.62698090721438 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
87 | Benin | BEN | Coverage of social safety net programs (% of population) | per_sa_allsa.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
88 | Benin | BEN | Coverage of social safety net programs in 2nd quintile (% of population) | per_sa_allsa.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
89 | Benin | BEN | Coverage of social safety net programs in 3rd quintile (% of population) | per_sa_allsa.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
90 | Benin | BEN | Coverage of social safety net programs in 4th quintile (% of population) | per_sa_allsa.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
91 | Benin | BEN | Coverage of social safety net programs in poorest quintile (% of population) | per_sa_allsa.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
92 | Benin | BEN | Coverage of social safety net programs in richest quintile (% of population) | per_sa_allsa.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
93 | Benin | BEN | Coverage of unemployment benefits and ALMP (% of population) | per_lm_alllm.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
94 | Benin | BEN | Coverage of unemployment benefits and ALMP in 2nd quintile (% of population) | per_lm_alllm.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
95 | Benin | BEN | Coverage of unemployment benefits and ALMP in 3rd quintile (% of population) | per_lm_alllm.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
96 | Benin | BEN | Coverage of unemployment benefits and ALMP in 4th quintile (% of population) | per_lm_alllm.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
97 | Benin | BEN | Coverage of unemployment benefits and ALMP in poorest quintile (% of population) | per_lm_alllm.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
98 | Benin | BEN | Coverage of unemployment benefits and ALMP in richest quintile (% of population) | per_lm_alllm.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
99 | Benin | BEN | Current health expenditure (% of GDP) | SH.XPD.CHEX.GD.ZS | .. | .. | .. | 3.10270309 | 3.24910021 | 3.04335403 | 3.0376544 | 3.0760572 | 2.93478322 | 2.97331023 | 2.8938241 | 2.69675088 | 2.82528329 | 2.99710441 | 3.09628272 | 3.41449857 | 2.85861206 | 2.66743827 | 2.90741682 | 2.73950028 | 2.61910868 | 2.50416446 | 2.38842916 | .. | .. |
100 | Benin | BEN | Current health expenditure per capita (current US$) | SH.XPD.CHEX.PC.CD | .. | .. | .. | 15.90676403 | 16.83250046 | 17.49715614 | 21.60637474 | 24.56986427 | 24.14694977 | 25.45315742 | 27.96020699 | 30.34991455 | 30.76049805 | 31.06598282 | 34.99642563 | 39.10080719 | 35.76725006 | 34.44753647 | 31.30697823 | 29.78626442 | 29.76860428 | 31.07242012 | 29.12529182 | .. | .. |
101 | Benin | BEN | Current health expenditure per capita, PPP (current international $) | SH.XPD.CHEX.PP.CD | .. | .. | .. | 54.59894562 | 59.7120285 | 57.67155075 | 58.83573914 | 62.00225067 | 60.23723984 | 63.48798752 | 65.35675049 | 63.31762695 | 66.49680328 | 70.8550415 | 74.81626129 | 85.31114197 | 76.31606293 | 75.57946777 | 83.93218231 | 82.31678009 | 79.73914337 | 81.07919312 | 81.98957825 | .. | .. |
102 | Benin | BEN | Domestic general government health expenditure (% of current health expenditure) | SH.XPD.GHED.CH.ZS | .. | .. | .. | 26.01166344 | 28.53469849 | 23.84386253 | 21.88357353 | 23.7856369 | 23.26777649 | 24.19742012 | 20.59366989 | 20.87325668 | 26.45173454 | 24.17091942 | 25.70649338 | 21.86915207 | 26.74820328 | 21.56858063 | 20.13637733 | 20.98593903 | 31.09478951 | 19.60268784 | 22.65070915 | .. | .. |
103 | Benin | BEN | Domestic general government health expenditure (% of GDP) | SH.XPD.GHED.GD.ZS | .. | .. | .. | 0.80706477 | 0.92712092 | 0.72565317 | 0.66474736 | 0.73165977 | 0.68285877 | 0.71946436 | 0.59594458 | 0.56289971 | 0.74733645 | 0.7244277 | 0.7959457 | 0.74672192 | 0.7646274 | 0.57532859 | 0.58544844 | 0.57490981 | 0.81440628 | 0.4908835 | 0.54099613 | .. | .. |
104 | Benin | BEN | Domestic general government health expenditure (% of general government expenditure) | SH.XPD.GHED.GE.ZS | .. | .. | .. | 5.15978622 | 6.00176048 | 4.74779558 | 4.85716248 | 5.47668171 | 4.82977295 | 5.53186369 | 3.76954269 | 3.86888194 | 4.39692497 | 5.1466217 | 5.40438175 | 5.24533272 | 5.1337862 | 4.04461384 | 3.22514915 | 3.72646332 | 4.57916498 | 2.96292353 | 3.70517755 | .. | .. |
105 | Benin | BEN | Domestic general government health expenditure per capita (current US$) | SH.XPD.GHED.PC.CD | .. | .. | .. | 4.13761427 | 4.80310303 | 4.17199789 | 4.72824725 | 5.84409875 | 5.61845783 | 6.15900737 | 5.75803293 | 6.33501556 | 8.13668494 | 7.50893353 | 8.99635359 | 8.5510144 | 9.56709618 | 7.42984444 | 6.30409164 | 6.25092677 | 9.25648525 | 6.09102944 | 6.59708499 | .. | .. |
106 | Benin | BEN | Domestic general government health expenditure per capita, PPP (current international $) | SH.XPD.GHED.PP.CD | .. | .. | .. | 14.20209477 | 17.03864644 | 13.75112553 | 12.87536295 | 14.74763114 | 14.01586586 | 15.36245543 | 13.45935385 | 13.21645015 | 17.58955851 | 17.12631411 | 19.23263826 | 18.65682176 | 20.41317617 | 16.30141783 | 16.9009011 | 17.27494906 | 24.79471854 | 15.89370181 | 18.57121843 | .. | .. |
107 | Benin | BEN | Domestic private health expenditure (% of current health expenditure) | SH.XPD.PVTD.CH.ZS | .. | .. | .. | 57.24701691 | 54.43483734 | 57.72973251 | 58.15346146 | 56.0488205 | 56.47822571 | 55.7960701 | 54.41661072 | 53.18040848 | 51.54034424 | 50.07919693 | 48.43403244 | 41.89283371 | 47.81689453 | 49.83951187 | 45.6293869 | 48.45129013 | 49.42943573 | 50.35248566 | 53.01073074 | .. | .. |
108 | Benin | BEN | Domestic private health expenditure per capita (current US$) | SH.XPD.PVTD.PC.CD | .. | .. | .. | 9.10614845 | 9.16274386 | 10.10106241 | 12.56485486 | 13.77111926 | 13.63776869 | 14.20185973 | 15.21499703 | 16.14020927 | 15.85406611 | 15.55759509 | 16.95017944 | 16.38043606 | 17.10278844 | 17.16848281 | 14.28518296 | 14.43182868 | 14.71445462 | 15.64573608 | 15.43953105 | .. | .. |
109 | Benin | BEN | Domestic private health expenditure per capita, PPP (current international $) | SH.XPD.PVTD.PP.CD | .. | .. | .. | 31.25626871 | 32.50414408 | 33.29363556 | 34.21501843 | 34.75153241 | 34.02092572 | 35.42379866 | 35.56492838 | 33.67257257 | 34.27268296 | 35.48363551 | 36.23653365 | 35.73925401 | 36.49197487 | 37.66843493 | 38.2977403 | 39.88354278 | 39.41461051 | 40.8253919 | 43.46327264 | .. | .. |
110 | Benin | BEN | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 0.550000011920929 | 0.550000011920929 | 0.600000023841858 | 0.610000014305115 | 0.620000004768372 | 0.629999995231628 | 0.620000004768372 | 0.629999995231628 | 0.629999995231628 | 0.629999995231628 | 0.649999976158142 | 0.649999976158142 | 0.639999985694885 | 0.649999976158142 | 0.649999976158142 | 0.660000026226044 | 0.680000007152557 | 0.699999988079071 | 0.680000007152557 | 0.699999988079071 | 0.709999978542328 | 0.720000028610229 | 0.730000019073486 | .. | .. |
111 | Benin | BEN | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 1.5 | 1.51999998092651 | 1.66999995708466 | 1.67999994754791 | 1.70000004768372 | 1.73000001907349 | 1.71000003814697 | 1.74000000953674 | 1.75999999046326 | 1.75999999046326 | 1.78999996185303 | 1.78999996185303 | 1.77999997138977 | 1.80999994277954 | 1.83000004291534 | 1.8400000333786 | 1.85000002384186 | 1.88999998569489 | 1.85000002384186 | 1.91999995708466 | 1.91999995708466 | 1.91999995708466 | 1.9099999666214 | .. | .. |
112 | Benin | BEN | Employers, total (% of total employment) (modeled ILO estimate) | SL.EMP.MPYR.ZS | 1.08000004291534 | 1.08000004291534 | 1.17999994754791 | 1.19000005722046 | 1.19000005722046 | 1.21000003814697 | 1.19000005722046 | 1.21000003814697 | 1.22000002861023 | 1.22000002861023 | 1.23000001907349 | 1.23000001907349 | 1.22000002861023 | 1.23000001907349 | 1.25 | 1.26999998092651 | 1.27999997138977 | 1.30999994277954 | 1.27999997138977 | 1.33000004291534 | 1.32000005245209 | 1.33000004291534 | 1.33000004291534 | .. | .. |
113 | Benin | BEN | Employment in agriculture (% of total employment) (modeled ILO estimate) | SL.AGR.EMPL.ZS | 49.5099983215332 | 49.25 | 48.8499984741211 | 48.3899993896484 | 47.9099998474121 | 47.4599990844727 | 47.0699996948242 | 46.6500015258789 | 46.3199996948242 | 45.8800010681152 | 45.3400001525879 | 44.8499984741211 | 44.4500007629395 | 44.0699996948242 | 43.6100006103516 | 43.0299987792969 | 42.2700004577637 | 41.560001373291 | 41.0800018310547 | 40.5900001525879 | 39.8699989318848 | 39.0800018310547 | 38.2700004577637 | .. | .. |
114 | Benin | BEN | Employment in agriculture, female (% of female employment) (modeled ILO estimate) | SL.AGR.EMPL.FE.ZS | 43.25 | 42.9099998474121 | 42.5 | 42.0499992370605 | 41.5400009155273 | 40.9099998474121 | 40.5299987792969 | 39.8499984741211 | 39.4500007629395 | 38.8800010681152 | 38.2799987792969 | 37.7400016784668 | 37.2700004577637 | 36.8600006103516 | 36.1199989318848 | 35.4000015258789 | 34.5699996948242 | 33.7599983215332 | 33.1699981689453 | 32.3199996948242 | 31.4799995422363 | 30.6299991607666 | 29.7600002288818 | .. | .. |
115 | Benin | BEN | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 54.5099983215332 | 54.4300003051758 | 54.1399993896484 | 53.810001373291 | 53.4799995422363 | 53.2999992370605 | 52.9900016784668 | 52.8800010681152 | 52.7099990844727 | 52.4900016784668 | 52.0900001525879 | 51.7400016784668 | 51.5 | 51.2000007629395 | 50.810001373291 | 50.3499984741211 | 49.6599998474121 | 49.060001373291 | 48.689998626709 | 48.5400009155273 | 47.9500007629395 | 47.25 | 46.4900016784668 | .. | .. |
116 | Benin | BEN | Employment in industry (% of total employment) (modeled ILO estimate) | SL.IND.EMPL.ZS | 20.1800003051758 | 20.0599994659424 | 20.0100002288818 | 19.9099998474121 | 19.7999992370605 | 19.7099990844727 | 19.6000003814697 | 19.4400005340576 | 19.3700008392334 | 19.2399997711182 | 19.0499992370605 | 18.8600006103516 | 18.7600002288818 | 18.6499996185303 | 18.5499992370605 | 18.4599990844727 | 18.4400005340576 | 18.3899993896484 | 18.4300003051758 | 18.2800006866455 | 18.2800006866455 | 18.2800006866455 | 18.3099994659424 | .. | .. |
117 | Benin | BEN | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 20.3600006103516 | 20.1599998474121 | 19.9799995422363 | 19.7199993133545 | 19.4500007629395 | 19.2900009155273 | 19.0499992370605 | 18.8299999237061 | 18.7099990844727 | 18.5 | 18.1399993896484 | 17.7999992370605 | 17.6399993896484 | 17.4500007629395 | 17.2700004577637 | 17.0699996948242 | 16.8799991607666 | 16.7000007629395 | 16.7099990844727 | 16.5100002288818 | 16.4099998474121 | 16.2700004577637 | 16.1599998474121 | .. | .. |
118 | Benin | BEN | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 20.0300006866455 | 19.9899997711182 | 20.0400009155273 | 20.0799999237061 | 20.1000003814697 | 20.0799999237061 | 20.1000003814697 | 20.0100002288818 | 19.9799995422363 | 19.9400005340576 | 19.9200000762939 | 19.8899993896484 | 19.8600006103516 | 19.8500003814697 | 19.7800006866455 | 19.7999992370605 | 19.9300003051758 | 20.0100002288818 | 20.0799999237061 | 19.9699993133545 | 20.0799999237061 | 20.2199993133545 | 20.3799991607666 | .. | .. |
119 | Benin | BEN | Employment in services (% of total employment) (modeled ILO estimate) | SL.SRV.EMPL.ZS | 30.3099994659424 | 30.6900005340576 | 31.1399993896484 | 31.7000007629395 | 32.2900009155273 | 32.8400001525879 | 33.3300018310547 | 33.9099998474121 | 34.310001373291 | 34.8800010681152 | 35.6100006103516 | 36.2900009155273 | 36.7900009155273 | 37.2799987792969 | 37.8400001525879 | 38.5 | 39.2900009155273 | 40.0499992370605 | 40.4900016784668 | 41.1399993896484 | 41.8499984741211 | 42.6399993896484 | 43.4199981689453 | .. | .. |
120 | Benin | BEN | Employment in services, female (% of female employment) (modeled ILO estimate) | SL.SRV.EMPL.FE.ZS | 36.3899993896484 | 36.939998626709 | 37.5299987792969 | 38.2400016784668 | 39.0099983215332 | 39.810001373291 | 40.4199981689453 | 41.3199996948242 | 41.8400001525879 | 42.6300010681152 | 43.5800018310547 | 44.4599990844727 | 45.0999984741211 | 45.689998626709 | 46.6100006103516 | 47.5299987792969 | 48.5400009155273 | 49.5400009155273 | 50.1300010681152 | 51.1699981689453 | 52.0999984741211 | 53.0999984741211 | 54.0800018310547 | .. | .. |
121 | Benin | BEN | Employment in services, male (% of male employment) (modeled ILO estimate) | SL.SRV.EMPL.MA.ZS | 25.4599990844727 | 25.5900001525879 | 25.8199996948242 | 26.1200008392334 | 26.4200000762939 | 26.6200008392334 | 26.9099998474121 | 27.1100006103516 | 27.3099994659424 | 27.5699996948242 | 27.9899997711182 | 28.3700008392334 | 28.6399993896484 | 28.9500007629395 | 29.4099998474121 | 29.8500003814697 | 30.4200000762939 | 30.9300003051758 | 31.2299995422363 | 31.4899997711182 | 31.9799995422363 | 32.5299987792969 | 33.1199989318848 | .. | .. |
122 | Benin | BEN | Employment to population ratio, 15+, female (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.FE.ZS | 60.632999420166 | 61.4620018005371 | 62.3190002441406 | 63.201000213623 | 64.109001159668 | 65.0479965209961 | 65.4449996948242 | 65.8470001220703 | 66.2470016479492 | 66.6600036621094 | 67.0770034790039 | 67.4889984130859 | 67.8980026245117 | 68.3140029907227 | 67.5950012207031 | 67.7480010986328 | 67.911003112793 | 68.0589981079102 | 68.193000793457 | 68.3560028076172 | 68.5289993286133 | 68.7020034790039 | 68.7610015869141 | 68.0210037231445 | 68.0439987182617 |
123 | Benin | BEN | Employment to population ratio, 15+, female (%) (national estimate) | SL.EMP.TOTL.SP.FE.NE.ZS | .. | .. | .. | .. | .. | .. | 75.129997253418 | .. | .. | .. | .. | .. | .. | 73.7900009155273 | 67.7099990844727 | .. | .. | .. | .. | .. | .. | 55.6399993896484 | .. | .. | .. |
124 | Benin | BEN | Employment to population ratio, 15+, male (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.MA.ZS | 82.6039962768555 | 81.697998046875 | 80.786003112793 | 79.8460006713867 | 78.8740005493164 | 77.8759994506836 | 77.3899993896484 | 76.9130020141602 | 76.4260025024414 | 75.9599990844727 | 75.4929962158203 | 75.0149993896484 | 74.5309982299805 | 74.0530014038086 | 72.4619979858398 | 72.4929962158203 | 72.5039978027344 | 72.4789962768555 | 72.4240036010742 | 72.431999206543 | 72.4219970703125 | 72.3880004882813 | 72.2089996337891 | 71.4449996948242 | 71.6579971313477 |
125 | Benin | BEN | Employment to population ratio, 15+, male (%) (national estimate) | SL.EMP.TOTL.SP.MA.NE.ZS | .. | .. | .. | .. | .. | .. | 73.9599990844727 | .. | .. | .. | .. | .. | .. | 75.370002746582 | 72.5800018310547 | .. | .. | .. | .. | .. | .. | 68.8600006103516 | .. | .. | .. |
126 | Benin | BEN | Employment to population ratio, 15+, total (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.ZS | 71.1669998168945 | 71.1790008544922 | 71.2009963989258 | 71.2210006713867 | 71.2379989624023 | 71.254997253418 | 71.2369995117188 | 71.2239990234375 | 71.2009963989258 | 71.1910018920898 | 71.1800003051758 | 71.1600036621094 | 71.1360015869141 | 71.1179962158203 | 69.9749984741211 | 70.0709991455078 | 70.1630020141602 | 70.2300033569336 | 70.2730026245117 | 70.3610000610352 | 70.4459991455078 | 70.5189971923828 | 70.4619979858398 | 69.7119979858398 | 69.8300018310547 |
127 | Benin | BEN | Employment to population ratio, 15+, total (%) (national estimate) | SL.EMP.TOTL.SP.NE.ZS | .. | .. | .. | .. | .. | .. | 74.5500030517578 | .. | .. | .. | .. | .. | .. | 74.5199966430664 | 69.9800033569336 | .. | .. | .. | .. | .. | .. | 61.8199996948242 | .. | .. | .. |
128 | Benin | BEN | Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate) | SL.EMP.1524.SP.FE.ZS | 55.6399993896484 | 56.0709991455078 | 56.5509986877441 | 57.0789985656738 | 57.6559982299805 | 58.2820014953613 | 56.9679985046387 | 55.6780014038086 | 54.3969993591309 | 53.1370010375977 | 51.8899993896484 | 50.6479988098145 | 49.4099998474121 | 48.1879997253418 | 45.6300010681152 | 45.6199989318848 | 45.6049995422363 | 45.5429992675781 | 45.398998260498 | 45.3289985656738 | 45.2550010681152 | 45.1559982299805 | 44.9179992675781 | 44.0279998779297 | 44.5880012512207 |
129 | Benin | BEN | Employment to population ratio, ages 15-24, female (%) (national estimate) | SL.EMP.1524.SP.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 43.5400009155273 | 44.5299987792969 | .. | .. | .. | .. | .. | .. | 32.3800010681152 | .. | .. | .. |
130 | Benin | BEN | Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate) | SL.EMP.1524.SP.MA.ZS | 67.6679992675781 | 65.7190017700195 | 63.7229995727539 | 61.6749992370605 | 59.5730018615723 | 57.4220008850098 | 55.4099998474121 | 53.3819999694824 | 51.3349990844727 | 49.2789993286133 | 47.2220001220703 | 45.1650009155273 | 43.1160011291504 | 41.0810012817383 | 37.6549987792969 | 37.5769996643066 | 37.4739990234375 | 37.3209991455078 | 37.0950012207031 | 36.935001373291 | 36.7490005493164 | 36.5289993286133 | 36.1520004272461 | 35.4150009155273 | 35.5340003967285 |
131 | Benin | BEN | Employment to population ratio, ages 15-24, male (%) (national estimate) | SL.EMP.1524.SP.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 35.8499984741211 | 36.439998626709 | .. | .. | .. | .. | .. | .. | 30.4799995422363 | .. | .. | .. |
132 | Benin | BEN | Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) | SL.EMP.1524.SP.ZS | 61.640998840332 | 60.8880004882813 | 60.1360015869141 | 59.3779983520508 | 58.6160011291504 | 57.8499984741211 | 56.1860008239746 | 54.523998260498 | 52.8569984436035 | 51.1959991455078 | 49.5419998168945 | 47.8899993896484 | 46.2430000305176 | 44.6100006103516 | 41.6129989624023 | 41.5660018920898 | 41.5040016174316 | 41.3930015563965 | 41.2050018310547 | 41.0880012512207 | 40.9570007324219 | 40.7960014343262 | 40.4869995117188 | 39.6730003356934 | 40.0099983215332 |
133 | Benin | BEN | Employment to population ratio, ages 15-24, total (%) (national estimate) | SL.EMP.1524.SP.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 39.6100006103516 | 40.6199989318848 | .. | .. | .. | .. | .. | .. | 31.4699993133545 | .. | .. | .. |
134 | Benin | BEN | Exports of goods and services (annual % growth) | NE.EXP.GNFS.KD.ZG | 9.462931858317674 | 11.085520698149935 | 13.788380510865522 | -10.568548284730085 | 4.78823107072634 | 10.02367153780375 | 1.797845922115627 | -5.209084538266339 | 10.032760982166678 | -0.2951079133922718 | 27.234900381710858 | 10.09265441472516 | -4.86468263369585 | 4.79778894126548 | -9.7106909750689 | 24.09569717685926 | 22.732218510660445 | 24.94269044919386 | -20.095907018424 | 13.481280138814284 | 7 | 4.999999999999986 | 8.614557869393707 | -24.96500563428792 | .. |
135 | Benin | BEN | Exports of goods and services (constant 2015 US$) | NE.EXP.GNFS.KD | 1064221200.290861 | 1182195661.7232041 | 1345201297.944544 | 1203033049.2444592 | 1260637051.4994888 | 1386999168.8256514 | 1411935276.822161 | 1338386374.6268897 | 1472663480.6110914 | 1468317534.14217 | 1868212351.8529832 | 2056764568.258714 | 1956709499.490623 | 2050588291.469875 | 1851461999.3142903 | 2297584676.0136857 | 2819876645.0325665 | 3523229747.652153 | 2815204773.518522 | 3194730415.517826 | 3418361544.604074 | 3589279621.834277 | 3898480191.9515467 | 2925224392.379245 | .. |
136 | Benin | BEN | External health expenditure (% of current health expenditure) | SH.XPD.EHEX.CH.ZS | .. | .. | .. | 16.74131584 | 17.03046417 | 18.42640114 | 19.96296501 | 20.1655426 | 20.2539959 | 20.00651169 | 24.98971939 | 25.94633675 | 22.00792122 | 25.74988365 | 25.85947418 | 36.23801041 | 25.43489838 | 28.5919075 | 34.23423767 | 30.56277275 | 19.47577095 | 30.0448246 | 24.3385601 | .. | .. |
137 | Benin | BEN | External health expenditure per capita (current US$) | SH.XPD.EHEX.PC.CD | .. | .. | .. | 2.66300172 | 2.86665288 | 3.22409654 | 4.31327319 | 4.95464653 | 4.89072187 | 5.09228891 | 6.9871776 | 7.87469103 | 6.76974596 | 7.99945414 | 9.04989209 | 14.16935487 | 9.09736367 | 9.84920765 | 10.71770635 | 9.10350812 | 5.79766576 | 9.33565419 | 7.08867711 | .. | .. |
138 | Benin | BEN | External health expenditure per capita, PPP (current international $) | SH.XPD.EHEX.PP.CD | .. | .. | .. | 9.14058206 | 10.1692353 | 10.62679259 | 11.74535826 | 12.50309115 | 12.20044783 | 12.70173207 | 16.33246924 | 16.42860391 | 14.63456474 | 18.24508952 | 19.34709424 | 30.91506056 | 19.41091462 | 21.60961115 | 28.73354409 | 25.15829168 | 15.52981361 | 24.3601029 | 19.95508184 | .. | .. |
139 | Benin | BEN | Female share of employment in senior and middle management (%) | SL.EMP.SMGT.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
140 | Benin | BEN | Final consumption expenditure (annual % growth) | NE.CON.TOTL.KD.ZG | 4.86003606891137 | 5.410049105222896 | 4.839962915998356 | 7.336851676776362 | 4.899031611920208 | 4.225322285184802 | 3.796294702629851 | 4.256224413987852 | 2.301727410164318 | 4.8659355503682775 | 3.7945482339471113 | 5.450350582560134 | 3.646895673960657 | 1.9445328021803192 | 3.696475993801542 | 2.264556901123086 | 4.5324885166816244 | 2.909101422654217 | 6.277071884981169 | 0.8547375087678972 | 3.9251414445440815 | 3.81523332336036 | 3.799440064982491 | 4.701574763080885 | .. |
141 | Benin | BEN | Final consumption expenditure (constant 2015 US$) | NE.CON.TOTL.KD | 4670986947.315151 | 4923689634.863453 | 5161994387.289699 | 5540722259.048664 | 5812163994.048158 | 6057746654.540161 | 6287716569.885206 | 6555335897.61502 | 6706221860.798766 | 7032542294.409942 | 7299395503.844058 | 7697238149.211191 | 7977948394.289224 | 8133082217.757195 | 8433719649.492732 | 8624706029.836693 | 9015619840.236588 | 9277893365.270006 | 9860273401.219902 | 9944552856.447193 | 10334890622.090195 | 10729190813.037024 | 11136839987.435974 | 11660446845.689964 | .. |
142 | Benin | BEN | GDP (constant 2015 US$) | NY.GDP.MKTP.KD | 5364793307.033675 | 5577293421.121404 | 5875201725.540954 | 6219354251.615792 | 6551040853.893792 | 6855207703.095186 | 7091272043.499816 | 7405393025.882269 | 7532259594.997867 | 7829312241.283452 | 8298002221.539256 | 8704320296.77356 | 8906198913.181185 | 9094481722.875242 | 9364019690.408699 | 9814543589.039257 | 10520349986.307781 | 11189200078.415228 | 11388160958.248966 | 11768488343.51553 | 12435944687.833479 | 13268812169.989193 | 14179807326.715624 | 14725558673.483627 | 15697445694.850372 |
143 | Benin | BEN | GDP growth (annual %) | NY.GDP.MKTP.KD.ZG | 5.734688375213068 | 3.9610121383264527 | 5.341449372044167 | 5.857714205432686 | 5.333135706039371 | 4.643030870744823 | 3.4435767759165827 | 4.429684553850819 | 1.7131645636118407 | 3.9437388281579757 | 5.986349321776089 | 4.896577084296467 | 2.319292139128379 | 2.1140647264839174 | 2.963752919042008 | 4.811223315687997 | 7.191433721449457 | 6.357679097919316 | 1.7781510603027755 | 3.339673426296926 | 5.671555469447526 | 6.697259460879863 | 6.865687335501505 | 3.8487924003013347 | 6.600001011281336 |
144 | Benin | BEN | GDP per capita (constant 2015 US$) | NY.GDP.PCAP.KD | 854.0428758830769 | 861.9870749112524 | 881.6194178211789 | 905.8262694777663 | 925.7160730063091 | 939.6616639382606 | 942.918587867681 | 955.534214100597 | 943.6293116589034 | 952.8312272392317 | 981.4557453868465 | 1000.8514854719817 | 995.6942065308507 | 988.6107854914368 | 989.7673544684825 | 1008.7663030525523 | 1051.5519156807145 | 1087.719957356699 | 1076.7966978558513 | 1082.4512883575026 | 1112.817094134354 | 1155.3131679606718 | 1201.5613838612542 | 1214.6595868089944 | 1260.7346086320379 |
145 | Benin | BEN | GDP per capita growth (annual %) | NY.GDP.PCAP.KD.ZG | 2.5807815269038628 | 0.9301873772977984 | 2.277568130815382 | 2.7457257822669305 | 2.1957636026618985 | 1.506465247671727 | 0.34660602367988247 | 1.3379337723572746 | -1.2458897092344472 | 0.9751621178607905 | 3.0041540756963343 | 1.9762215643752938 | -0.5152891329025806 | -0.7114052680986873 | 0.11698931409804914 | 1.9195367980460816 | 4.241380040024296 | 3.439491777500251 | -1.0042345391356378 | 0.5251307431487078 | 2.8052815035148484 | 3.81878334277161 | 4.0030891348896205 | 1.0900985271055106 | 3.793245640458508 |
146 | Benin | BEN | GDP per capita, PPP (constant 2017 international $) | NY.GDP.PCAP.PP.KD | 2336.545872151399 | 2358.280126918924 | 2411.9915635249827 | 2478.218237750791 | 2532.634051809852 | 2570.7873036510673 | 2579.697807301519 | 2614.212455490166 | 2581.6422515296886 | 2606.8174487852953 | 2685.130261418942 | 2738.19438467667 | 2724.084766574683 | 2704.705484037796 | 2707.8697004319442 | 2759.8482557748766 | 2876.903908830271 | 2975.8547822210717 | 2945.9702206634875 | 2961.440415976197 | 3044.517156203191 | 3160.7806702321027 | 3287.3095378198554 | 3323.144450673027 | 3449.199482674322 |
147 | Benin | BEN | GDP per capita, PPP (current international $) | NY.GDP.PCAP.PP.CD | 1580.2181203446 | 1612.8684298891378 | 1672.849347533297 | 1757.7210108805411 | 1836.7865619831832 | 1893.5152625587164 | 1937.5782328771745 | 2016.2101451969522 | 2053.5274821362677 | 2137.5338925418414 | 2261.2515478017317 | 2350.1652509058217 | 2353.0409796091285 | 2364.378795752749 | 2416.3273623235905 | 2498.495772564701 | 2669.6882195341595 | 2833.4127527948467 | 2886.8291371897285 | 3004.807804990861 | 3044.517156203191 | 3236.2920647484116 | 3426.049089352308 | 3505.138454730403 | 3789.2733465788333 |
148 | Benin | BEN | GDP per person employed (constant 2017 PPP $) | SL.GDP.PCAP.EM.KD | 6014.513395578372 | 6062.929804062878 | 6188.481567090813 | 6342.578926329808 | 6472.012250221801 | 6554.456453154398 | 6561.269475598712 | 6629.332305244774 | 6525.8375574117945 | 6582.450819613224 | 6769.84227296095 | 6890.809103025795 | 6839.903172082991 | 6772.670065582832 | 6878.94907010438 | 6983.8452364071745 | 7248.503340361299 | 7465.525032170293 | 7359.490462136412 | 7366.778908316032 | 7538.228642083291 | 7787.990363276699 | 8072.33680959514 | 8211.053151668526 | 8475.927001307513 |
149 | Benin | BEN | GDP, PPP (constant 2017 international $) | NY.GDP.MKTP.PP.KD | 14677349358.524605 | 15258720948.200342 | 16073757802.469963 | 17015312596.612093 | 17922762308.196228 | 18754921695.055996 | 19400761822.888283 | 20260154372.686153 | 20607244157.932064 | 21419940047.20175 | 22702212482.942257 | 23813843817.0103 | 24366156424.68253 | 24881272742.856632 | 25618692190.067852 | 26851264681.89074 | 28782255584.85988 | 30612139032.088226 | 31156469106.86866 | 32196993426.203167 | 34023063767.86465 | 36301676624.939156 | 38794036239.55232 | 40287138158.110344 | 42946089683.961945 |
150 | Benin | BEN | GDP, PPP (current international $) | NY.GDP.MKTP.PP.CD | 9926367674.353935 | 10435702280.200941 | 11148038682.59534 | 12068417543.771208 | 12998438893.210129 | 13813951246.47086 | 14571665604.733831 | 15625634673.906815 | 16391714299.040207 | 17563887278.88981 | 19118406973.838604 | 20439187423.081604 | 21047276239.842506 | 21750521094.34366 | 22860459982.96453 | 24308499989.208206 | 26709146743.022137 | 29146860808.54739 | 30530995255.411354 | 32668486802.0226 | 34023063767.86465 | 37168927633.85777 | 40431322636.85908 | 42493487504.11071 | 47180359905.7268 |
151 | Benin | BEN | General government final consumption expenditure (annual % growth) | NE.CON.GOVT.KD.ZG | 3.980576783278437 | 5.188154735908938 | 2.170407483378284 | 5.307674422722812 | 10.326603466308299 | 3.2812063496390493 | 14.807984104662026 | 6.1947491241406425 | 4.273006114967998 | 9.231373821308253 | 4.071256570494981 | 14.659118554229323 | 9.779717972255625 | 1.2118968027155432 | 3.347349025819682 | 4.766898374637222 | 7.896822216359013 | -2.287457545346271 | 13.56991897560178 | -6.25622309831877 | 6.970439575696986 | 5.999999994808178 | 5.82580347791162 | 14.441116703181464 | .. |
152 | Benin | BEN | General government final consumption expenditure (constant 2015 US$) | NE.CON.GOVT.KD | 422187166.7965975 | 444090890.28515494 | 453729472.2009052 | 477811955.3452679 | 527153701.2883878 | 544450702.0074196 | 625072875.4183991 | 663794571.8936211 | 692158554.5414611 | 756054298.1473471 | 786835208.4371808 | 902178314.4684045 | 990408809.230264 | 1002411541.9231386 | 1035965754.9064066 | 1085349189.6388383 | 1171057285.5713105 | 1144269847.3321824 | 1299546338.4774017 | 1218243820.2762227 | 1303160769.6532395 | 1381350415.764776 | 1461825176.328547 | 1672929056.0386407 | .. |
153 | Benin | BEN | Gini index | SI.POV.GINI | .. | .. | .. | .. | .. | .. | 38.6 | .. | .. | .. | .. | .. | .. | .. | 43.4 | .. | .. | .. | 47.8 | .. | .. | 37.8 | .. | .. | .. |
154 | Benin | BEN | GNI (constant 2015 US$) | NY.GNP.MKTP.KD | 5296175357.454694 | 5548049142.7991905 | 5856561966.58909 | 6198461839.040575 | 6526105696.371284 | 6810454018.584043 | 7041935649.790013 | 7361499569.002461 | 7512477977.694331 | 7796653858.103053 | 8250483386.765519 | 8694565190.445131 | 8876666210.773588 | 9044595876.921253 | 9350651112.791376 | 9756513987.330122 | 10462531167.50929 | 11138112526.922348 | 11295642491.513617 | 11665097397.83669 | 12298520507.80483 | 13134215770.285667 | 14037049458.074389 | 14571769578.622074 | .. |
155 | Benin | BEN | GNI growth (annual %) | NY.GNP.MKTP.KD.ZG | 6.403730423213318 | 4.755767480205677 | 5.560744251703653 | 5.837893877021671 | 5.285889722948141 | 4.357090360501914 | 3.3989162921343308 | 4.53801248839838 | 2.050919208466766 | 3.78271831548102 | 5.82082438084386 | 5.382494368656722 | 2.094423543210368 | 1.8918100800484012 | 3.3838464430574646 | 4.340477145848581 | 7.236367221899215 | 6.4571502688664 | 1.4143326727082126 | 3.270773721819225 | 5.430071334728922 | 6.795087766455254 | 6.873906319030155 | 3.8093484114648106 | .. |
156 | Benin | BEN | GNI per capita (constant 2015 US$) | NY.GNP.PCAP.KD | 843.1193103994262 | 857.4672858262115 | 878.8223779571637 | 902.7833657649761 | 922.1925297074133 | 933.5271566444667 | 936.3583822512609 | 949.8705444375262 | 941.151102605669 | 948.8566856235141 | 975.8354006149791 | 999.7298111393674 | 992.3925128479347 | 983.1879712117149 | 988.354309415314 | 1002.8018579153265 | 1045.7726887777046 | 1082.7536551240228 | 1068.0487024739325 | 1072.941514537127 | 1100.519839641666 | 1143.5938828471717 | 1189.4644393648034 | 1201.974064815412 | .. |
157 | Benin | BEN | GNI per capita growth (annual %) | NY.GNP.PCAP.KD.ZG | 3.229867056098243 | 1.7017728392423948 | 2.490484766468427 | 2.726488128751356 | 2.1499248522363956 | 1.2290955057562343 | 0.3032826186836388 | 1.443054544327211 | -0.917961071950117 | 0.8187402635465588 | 2.843286599570831 | 2.4486107502689407 | -0.7339281283480545 | -0.9275101854411503 | 0.5254680035631196 | 1.461778267406899 | 4.2850769095809085 | 3.536233709597198 | -1.3581069507824566 | 0.4581075799129195 | 2.5703474728943263 | 3.913972438655037 | 4.01108795750369 | 1.0517023491084103 | .. |
158 | Benin | BEN | GNI per capita, Atlas method (current US$) | NY.GNP.PCAP.CD | 380 | 370 | 410 | 480 | 530 | 530 | 600 | 730 | 820 | 860 | 920 | 1030 | 1090 | 1080 | 1090 | 1120 | 1220 | 1270 | 1180 | 1110 | 1090 | 1200 | 1250 | 1280 | 1370 |
159 | Benin | BEN | GNI per capita, PPP (constant 2017 international $) | NY.GNP.PCAP.PP.KD | 2306.6829390761714 | 2345.937442820808 | 2404.3626574651394 | 2469.917319893057 | 2523.0186861831285 | 2554.028995464395 | 2561.7749214837786 | 2598.742730903685 | 2574.887284273855 | 2595.9689232111464 | 2669.7797597338313 | 2735.1522739391785 | 2715.078222047587 | 2689.8955949954016 | 2704.0301356763557 | 2743.5570605438056 | 2861.120590646345 | 2962.296501445008 | 2922.0653467560983 | 2935.4515495995956 | 3010.9028543227664 | 3128.7487621956375 | 3254.2456270166126 | 3288.4706047217037 | .. |
160 | Benin | BEN | GNI per capita, PPP (current international $) | NY.GNP.PCAP.PP.CD | 1560 | 1600 | 1670 | 1750 | 1830 | 1880 | 1920 | 2000 | 2050 | 2130 | 2250 | 2350 | 2350 | 2350 | 2410 | 2480 | 2650 | 2820 | 2860 | 2980 | 3010 | 3200 | 3390 | 3470 | 3750 |
161 | Benin | BEN | GNI, Atlas method (current US$) | NY.GNP.ATLS.CD | 2374740872.3346543 | 2403760082.8455544 | 2762941305.014988 | 3285462983.738861 | 3783167939.56175 | 3890714803.505188 | 4536166269.090279 | 5655950088.028883 | 6571349689.228374 | 7082441203.245932 | 7808105611.528251 | 8977721470.295006 | 9725278675.047094 | 9953915777.32779 | 10357314482.521622 | 10942496193.15717 | 12214954488.215845 | 13069577667.613976 | 12462818879.021112 | 12104023692.227474 | 12203345013.654915 | 13728467799.974922 | 14803390762.056602 | 15498937116.153795 | 17115172179.930758 |
162 | Benin | BEN | GNI, PPP (constant 2017 international $) | NY.GNP.MKTP.PP.KD | 14489761044.150198 | 15178860387.847403 | 16022917994.338749 | 16958318942.850454 | 17854716981.03536 | 18632663133.51095 | 19265971756.41436 | 20140263960.73175 | 20553324502.938305 | 21330798873.351208 | 22572427214.8 | 23787386838.50575 | 24285595468.765938 | 24745032811.843826 | 25582366724.4808 | 26692763505.524063 | 28624349894.456882 | 30472667180.628063 | 30903652068.80932 | 31914440599.758373 | 33647417490.404945 | 35933789040.023575 | 38403844035.512726 | 39866780258.22095 | .. |
163 | Benin | BEN | GNI, PPP (current international $) | NY.GNP.MKTP.PP.CD | 9795871419.588245 | 10378787003.366848 | 11110619768.640963 | 12026254072.20153 | 12946713962.052547 | 13720836586.498295 | 14467663511.747097 | 15532068457.821648 | 16347374768.451363 | 17488379961.14955 | 19004845069.46989 | 20415476948.704983 | 20975678924.41697 | 21628404646.418938 | 22827277379.614964 | 24162896617.311043 | 26561886938.35518 | 29012509444.384842 | 30282958642.714123 | 32384504143.62986 | 33647417490.404945 | 36761232957.09144 | 40028224270.22609 | 42051740112.98021 | 46687572086.8494 |
164 | Benin | BEN | Gross capital formation (annual % growth) | NE.GDI.TOTL.KD.ZG | 16.7119839986847 | -6.146444738423156 | 17.553824984644677 | -5.827670294196466 | 22.51967669465394 | -12.121439147042878 | 6.42348197584937 | 6.688436087711565 | -22.651410361966867 | 10.452639178669429 | 30.94743060372744 | -8.792979232774272 | 11.800735687455216 | 8.670832422154092 | 5.1134795139159905 | 4.984521512855039 | 40.668409951804904 | 9.232290939470218 | 13.945512387041475 | 1.5687350537813245 | 24.741443718325357 | 15.917037135523842 | 10.020438429028715 | 1.860966958489783 | .. |
165 | Benin | BEN | Gross capital formation (constant 2015 US$) | NE.GDI.TOTL.KD | 776064223.0185907 | 728363864.4160799 | 856219582.4270732 | 806321928.1688777 | 987903019.5106087 | 868154956.1688311 | 923920733.300779 | 985716581.0487176 | 762437873.2694229 | 842132753.1237966 | 1102751202.4880428 | 1005786518.2641008 | 1124476726.8645058 | 1221978219.4770505 | 1284463825.3945248 | 1348488201.0961556 | 1896896910.8696597 | 2072023952.5029697 | 2360978309.4617376 | 2398015803.8144374 | 2991319534.2717338 | 3467448975.3839445 | 3814902565.0202794 | 3885896641.253886 | .. |
166 | Benin | BEN | Gross fixed capital formation (annual % growth) | NE.GDI.FTOT.KD.ZG | 8.339351527484126 | 4.250105714764629 | 7.47404551179514 | -0.4425775781812007 | 16.355839779283613 | -4.856567096160703 | 8.115378853029753 | -1.953838218981943 | -8.3892650816845 | -1.6702574353276702 | 24.801548239830254 | 1.0117114236272613 | 7.80014294428608 | 9.948920512997404 | 4.070996195866002 | -0.43785430745806764 | 46.319305429969376 | 12.18253199009456 | 4.967039870262539 | 0.32436192877950987 | 25.336900693144244 | 16.222676034674933 | 10.409132717314606 | 2.1096116156788014 | .. |
167 | Benin | BEN | Gross fixed capital formation (constant 2015 US$) | NE.GDI.FTOT.KD | 742063906.7190316 | 773602407.2257028 | 831421803.2220945 | 827742116.7409238 | 963126291.14072 | 916351416.5907068 | 990716805.6721476 | 971359802.0810481 | 889869853.3875431 | 875006735.9965982 | 1092021953.7265587 | 1103070064.5809278 | 1189111106.393869 | 1307414825.180219 | 1360639632.9774938 | 1354682013.7355201 | 1982161313.282535 | 2223638749.3684583 | 2334087772.620197 | 2341658664.7388744 | 2934962395.1961713 | 3411091836.308382 | 3766156912.6592054 | 3845608196.353354 | .. |
168 | Benin | BEN | Gross national expenditure (constant 2015 US$) | NE.DAB.TOTL.KD | 5447051170.333742 | 5652053499.279532 | 6018213969.716772 | 6347044187.217542 | 6800067013.558766 | 6925901610.708992 | 7211637303.185986 | 7541052478.663737 | 7468659734.068189 | 7874675047.533738 | 8402146706.332101 | 8703024667.475292 | 9102425121.153728 | 9355060437.234245 | 9718183474.887257 | 9973194230.932848 | 10912516751.106247 | 11349917317.772976 | 12221251710.68164 | 12342568660.261631 | 13326210156.361929 | 14196639788.420967 | 14951742552.456253 | 15546343486.943851 | .. |
169 | Benin | BEN | Gross value added at basic prices (GVA) (constant 2015 US$) | NY.GDP.FCST.KD | .. | .. | 4899801845.092038 | 5355779912.677643 | 5844818725.847274 | 5992662450.523223 | 6202773753.970026 | 6442787727.137337 | 6712818148.727437 | 7076263534.0268135 | 7461544327.8609 | 7854478849.454434 | 8039982632.786193 | 8167420883.416212 | 8566059069.872942 | 9014583996.392494 | 9696660337.236223 | 10253788212.073612 | 10479166768.857924 | 10869125221.980553 | 11437652385.769766 | 12130758163.784645 | 12926859500.581598 | 13438451662.57704 | .. |
170 | Benin | BEN | Hospital beds (per 1,000 people) | SH.MED.BEDS.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 0.5 | .. | .. | .. | .. | 0.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
171 | Benin | BEN | Households and NPISHs Final consumption expenditure (annual % growth) | NE.CON.PRVT.KD.ZG | 5.01934108425408 | 5.449845428716827 | 5.317554240780112 | 7.532400891380803 | 4.386804737463194 | 4.319493191635075 | 2.708864955189938 | 4.042239695890743 | 2.079625241717281 | 4.363517250693178 | 3.761216455131617 | 4.337764665843451 | 2.8326424637504175 | 2.048376096673607 | 3.7455553771806365 | 1.91413431197212 | 4.04816645195784 | 3.684857650552047 | 5.251085741339608 | 1.9342045624735107 | 3.499999999999986 | 3.499999999999986 | 3.4999999992581223 | 3.2300000015000023 | .. |
172 | Benin | BEN | Households and NPISHs Final consumption expenditure (constant 2015 US$) | NE.CON.PRVT.KD | 4239495497.2981772 | 4470541448.858337 | 4708264915.2579365 | 5062910303.703395 | 5285010292.759768 | 5513295952.532739 | 5662643694.466804 | 5891541325.7213955 | 6014063306.257302 | 6276487996.093448 | 6512560295.406875 | 6795059834.7427845 | 6987539585.058957 | 7130670675.664911 | 7397753894.586322 | 7539356840.197852 | 7844562554.496131 | 8133623517.937822 | 8560727062.7425 | 8726309036.17097 | 9031729852.436954 | 9347840397.272247 | 9675014811.107426 | 9987517789.651321 | .. |
173 | Benin | BEN | Households and NPISHs Final consumption expenditure per capita (constant 2015 US$) | NE.CON.PRVT.PC.KD | 674.9022249214804 | 690.9353101859241 | 706.511534685996 | 737.3944276549271 | 746.8155213530722 | 755.7222320017871 | 752.9554615096974 | 760.1985890618606 | 753.4321362331241 | 763.8517402515522 | 770.280553110104 | 781.3184166948469 | 781.1921532756431 | 775.1357555728976 | 781.9350629664464 | 774.9162336520873 | 784.0960444036251 | 790.6824968965004 | 809.4513853164742 | 802.6353270975283 | 808.1946049120277 | 813.914840413635 | 819.8365434118768 | 823.8352474101197 | .. |
174 | Benin | BEN | Households and NPISHs Final consumption expenditure per capita growth (annual %) | NE.CON.PRVT.PC.KD.ZG | 1.8867719705572625 | 2.3756160036824525 | 2.254367995157253 | 4.371180292570415 | 1.2776193235018383 | 1.1926252727819389 | -0.3661094480125371 | 0.961959627418139 | -0.8900901588211099 | 1.382951896705947 | 0.8416309762460799 | 1.4329666691150607 | -0.01616030244593958 | -0.7752763103610789 | 0.8771763326184754 | -0.8976230440072186 | 1.1846197502244138 | 0.8400058309036496 | 2.3737579235209267 | -0.8420589973147088 | 0.6926280998124952 | 0.7077794712858889 | 0.7275580569623656 | 0.48774405463819903 | .. |
175 | Benin | BEN | Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $) | NE.CON.PRVT.PP.KD | 11455857796.675444 | 12080184339.127861 | 12722554693.74721 | 13680868516.905436 | 14281021505.131155 | 14897889256.741238 | 15301452957.88011 | 15919974363.391586 | 16251050168.727596 | 16960167546.258825 | 17598076158.826603 | 18361439288.312405 | 18881553214.548893 | 19268318437.27642 | 19990023974.596123 | 20372659882.465317 | 21197379065.198753 | 21978472309.399246 | 23132580735.002384 | 23580012166.996666 | 24405312592.84155 | 25259498533.591 | 26143580982.079292 | 26988018648.19261 | .. |
176 | Benin | BEN | Households and NPISHs Final consumption expenditure, PPP (current international $) | NE.CON.PRVT.PP.CD | 4646624395.031343 | 4984706820.78808 | 8775358513.111977 | 9625004243.490437 | 10302096315.589432 | 10932894504.421629 | 11549995563.990093 | 12142717574.46766 | 12993263707.48619 | 13725990697.466894 | 14456399437.212017 | 15611542307.392593 | 16007773010.325539 | 16351567390.400532 | 17444373382.966843 | 19223422661.049805 | 20001428170.576492 | 21324866707.192722 | 22798548817.37805 | 23752060888.109287 | 24405312592.84155 | 25883076075.742874 | 27446117998.72419 | 28647968176.895004 | .. |
177 | Benin | BEN | Imports of goods and services (annual % growth) | NE.IMP.GNFS.KD.ZG | 11.43522128371059 | 9.877952823405622 | 16.611566963401486 | -10.582553456297504 | 13.446827802009409 | -3.442545938884251 | 5.118192917035387 | -3.8017516322924365 | -4.408372583715661 | 7.424462249517049 | 30.302179826583682 | 4.213806279801773 | 4.741797402443467 | 7.349621070436669 | -4.566596877496366 | 11.362289463728231 | 30.77100511119434 | 14.691695892791174 | -0.9677731468014912 | 3.303329060255038 | 14.323232345898987 | 4.838686171030801 | 3.393947941261885 | -19.79280491100944 | .. |
178 | Benin | BEN | Imports of goods and services (constant 2015 US$) | NE.IMP.GNFS.KD | 1161484126.9210339 | 1276214981.0296383 | 1488214287.2003384 | 1330723214.7131057 | 1509663273.916941 | 1457692422.189886 | 1532299932.4945705 | 1474045694.7993422 | 1409064268.518367 | 1513679713.2059467 | 1972357661.9001286 | 2055468992.9174275 | 2152935168.231617 | 2311167744.988809 | 2205626030.912447 | 2456235645.032059 | 3212044040.907851 | 3683947783.3405538 | 3648295525.9511952 | 3768810732.263925 | 4308626250.123264 | 4517107152.649382 | 4670415417.861319 | 3746009205.6703215 | .. |
179 | Benin | BEN | Income share held by fourth 20% | SI.DST.04TH.20 | .. | .. | .. | .. | .. | .. | 20.9 | .. | .. | .. | .. | .. | .. | .. | 20.2 | .. | .. | .. | 20.8 | .. | .. | 21.4 | .. | .. | .. |
180 | Benin | BEN | Income share held by highest 10% | SI.DST.10TH.10 | .. | .. | .. | .. | .. | .. | 31.1 | .. | .. | .. | .. | .. | .. | .. | 34.5 | .. | .. | .. | 37.6 | .. | .. | 29.9 | .. | .. | .. |
181 | Benin | BEN | Income share held by highest 20% | SI.DST.05TH.20 | .. | .. | .. | .. | .. | .. | 46.2 | .. | .. | .. | .. | .. | .. | .. | 50.7 | .. | .. | .. | 52.1 | .. | .. | 45.4 | .. | .. | .. |
182 | Benin | BEN | Income share held by lowest 10% | SI.DST.FRST.10 | .. | .. | .. | .. | .. | .. | 2.9 | .. | .. | .. | .. | .. | .. | .. | 2.5 | .. | .. | .. | 1 | .. | .. | 2.9 | .. | .. | .. |
183 | Benin | BEN | Income share held by lowest 20% | SI.DST.FRST.20 | .. | .. | .. | .. | .. | .. | 7 | .. | .. | .. | .. | .. | .. | .. | 6.1 | .. | .. | .. | 3.2 | .. | .. | 7 | .. | .. | .. |
184 | Benin | BEN | Income share held by second 20% | SI.DST.02ND.20 | .. | .. | .. | .. | .. | .. | 10.9 | .. | .. | .. | .. | .. | .. | .. | 9.6 | .. | .. | .. | 9.6 | .. | .. | 11.1 | .. | .. | .. |
185 | Benin | BEN | Income share held by third 20% | SI.DST.03RD.20 | .. | .. | .. | .. | .. | .. | 15 | .. | .. | .. | .. | .. | .. | .. | 13.4 | .. | .. | .. | 14.2 | .. | .. | 15 | .. | .. | .. |
186 | Benin | BEN | Industry (including construction), value added (annual % growth) | NV.IND.TOTL.KD.ZG | 3.5084405657811857 | -0.1876472508719047 | 1.7497358686556765 | 9.208547035482553 | 13.357503381409813 | 1.8587843072578352 | 1.1770368330604981 | 1.0754844774410373 | 6.595173593140217 | 3.048635753309199 | -1.7701910521123523 | -8.902815787490141 | 1.5319870428817808 | 3.367779982989177 | 0.17532428421259283 | 3.6641718765372673 | 6.199581910934299 | 3.891504544287173 | 13.786875453777526 | 0.8916058877171338 | 0.46905155730297565 | 4.8409764498529455 | 13.558394443142618 | 5.1751269198812935 | .. |
187 | Benin | BEN | Industry (including construction), value added (constant 2015 US$) | NV.IND.TOTL.KD | 1059378712.2277858 | 1057390817.1979682 | 1075892363.5983524 | 1174966417.9514716 | 1331912596.9597692 | 1356669979.2984476 | 1372638484.6578646 | 1387400998.4917417 | 1478902502.7752326 | 1523988853.231423 | 1497011338.9163306 | 1363735177.09477 | 1384627423.3070827 | 1431258628.5081975 | 1433767972.4538605 | 1486303695.2753136 | 1578448310.30915 | 1639873698.0340545 | 1865961042.3812656 | 1882598060.897645 | 1891428416.4200408 | 1982992020.6247616 | 2251853900.557111 | 2368390197.961239 | .. |
188 | Benin | BEN | Industry (including construction), value added per worker (constant 2015 US$) | NV.IND.EMPL.KD | 2132.5420104519226 | 2077.197825174946 | 2055.6786216553983 | 2187.834572866494 | 2420.5342076540555 | 2403.3281995093703 | 2364.725475824756 | 2331.449131716606 | 2415.1527671870936 | 2434.5193875905516 | 2348.3168248606617 | 2101.7762117083385 | 2088.7857168998707 | 2112.949065001953 | 2105.022734925616 | 2127.5702038647996 | 2194.283909382931 | 2215.3723221404803 | 2436.3631975334806 | 2401.8056741280398 | 2337.8340306708546 | 2374.699619223924 | 2608.779829020369 | .. | .. |
189 | Benin | BEN | International migrant stock (% of population) | SM.POP.TOTL.ZS | .. | .. | .. | 1.9243482067285 | .. | .. | .. | .. | 2.09595957744231 | .. | .. | .. | .. | 2.20054095786262 | .. | .. | .. | .. | 2.25554096484421 | .. | .. | .. | .. | .. | .. |
190 | Benin | BEN | International migrant stock, total | SM.POP.TOTL | .. | .. | .. | 133730 | .. | .. | .. | .. | 171499 | .. | .. | .. | .. | 209267 | .. | .. | .. | .. | 245399 | .. | .. | .. | .. | .. | .. |
191 | Benin | BEN | Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.FE.ZS | 56.0149993896484 | 56.4440002441406 | 56.9189987182617 | 57.4420013427734 | 58.0149993896484 | 58.6349983215332 | 57.4589996337891 | 56.2970008850098 | 55.1459999084473 | 54.0029983520508 | 52.8699989318848 | 51.7449989318848 | 50.6279983520508 | 49.515998840332 | 48.4070014953613 | 48.2799987792969 | 48.1459999084473 | 47.9799995422363 | 47.7480010986328 | 47.5620002746582 | 47.367000579834 | 47.1539993286133 | 46.9189987182617 | 46.1020011901855 | 46.7190017700195 |
192 | Benin | BEN | Labor force participation rate for ages 15-24, female (%) (national estimate) | SL.TLF.ACTI.1524.FE.NE.ZS | .. | .. | .. | .. | 52.25 | 58.6599998474121 | 61.8300018310547 | .. | .. | .. | .. | .. | .. | 44.939998626709 | 47.3499984741211 | .. | .. | .. | .. | .. | .. | 33.9199981689453 | .. | .. | .. |
193 | Benin | BEN | Labor force participation rate for ages 15-24, male (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.MA.ZS | 68.8619995117188 | 66.7919998168945 | 64.6740036010742 | 62.507999420166 | 60.2929992675781 | 58.0320014953613 | 56.0340003967285 | 54.0120010375977 | 51.9710006713867 | 49.9140014648438 | 47.8530006408691 | 45.7939987182617 | 43.7410011291504 | 41.6990013122559 | 39.6609992980957 | 39.4519996643066 | 39.2169990539551 | 38.943000793457 | 38.6020011901855 | 38.3139991760254 | 38 | 37.6549987792969 | 37.2789993286133 | 36.5900001525879 | 36.6800003051758 |
194 | Benin | BEN | Labor force participation rate for ages 15-24, male (%) (national estimate) | SL.TLF.ACTI.1524.MA.NE.ZS | .. | .. | .. | .. | 38.0800018310547 | 57.5 | 46.2599983215332 | .. | .. | .. | .. | .. | .. | 36.4000015258789 | 38.439998626709 | .. | .. | .. | .. | .. | .. | 31.4699993133545 | .. | .. | .. |
195 | Benin | BEN | Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.ZS | 62.423999786377 | 61.6100006103516 | 60.7949981689453 | 59.9770011901855 | 59.1559982299805 | 58.3330001831055 | 56.7430000305176 | 55.1479988098145 | 53.548999786377 | 51.9459991455078 | 50.3470001220703 | 48.7519989013672 | 47.1629981994629 | 45.5810012817383 | 44.0019989013672 | 43.8310012817383 | 43.6419982910156 | 43.4179992675781 | 43.1290016174316 | 42.8899993896484 | 42.6339988708496 | 42.3540000915527 | 42.0460014343262 | 41.2929992675781 | 41.6430015563965 |
196 | Benin | BEN | Labor force participation rate for ages 15-24, total (%) (national estimate) | SL.TLF.ACTI.1524.NE.ZS | .. | .. | .. | .. | 45.3400001525879 | 58.1199989318848 | 53.9099998474121 | .. | .. | .. | .. | .. | .. | 40.5800018310547 | 43.0400009155273 | .. | .. | .. | .. | .. | .. | 32.75 | .. | .. | .. |
197 | Benin | BEN | Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.FE.ZS | 60.9420013427734 | 61.7669982910156 | 62.617000579834 | 63.4930000305176 | 64.3949966430664 | 65.3270034790039 | 65.7839965820313 | 66.2460021972656 | 66.7119979858398 | 67.1849975585938 | 67.661003112793 | 68.140998840332 | 68.6230010986328 | 69.1070022583008 | 69.5940017700195 | 69.6259994506836 | 69.6650009155273 | 69.7089996337891 | 69.7570037841797 | 69.7979965209961 | 69.8460006713867 | 69.9010009765625 | 69.9619979858398 | 69.2959976196289 | 69.3339996337891 |
198 | Benin | BEN | Labor force participation rate, female (% of female population ages 15+) (national estimate) | SL.TLF.CACT.FE.NE.ZS | .. | .. | .. | .. | 68.6999969482422 | 65.5999984741211 | 78.3000030517578 | .. | .. | .. | .. | .. | .. | 74.6399993896484 | 69.6999969482422 | .. | .. | .. | .. | .. | .. | 56.6199989318848 | .. | .. | .. |
199 | Benin | BEN | Labor force participation rate, female (% of female population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.FE.ZS | 62.91 | 63.71 | 64.49 | 65.27 | 66.03 | 66.78 | 67.5 | 68.14 | 68.73 | 69.24 | 69.68 | 70.06 | 70.4 | 70.69 | 69.47 | 69.52 | 69.58 | 69.65 | 69.76 | 69.85 | 69.95 | 70.05 | 70.15 | .. | .. |
200 | Benin | BEN | Labor force participation rate, male (% of male population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.MA.ZS | 83.9140014648438 | 82.8990020751953 | 81.8619995117188 | 80.8010025024414 | 79.713996887207 | 78.6019973754883 | 78.1169967651367 | 77.6340026855469 | 77.1529998779297 | 76.6750030517578 | 76.1969985961914 | 75.7170028686523 | 75.2360000610352 | 74.7529983520508 | 74.2669982910156 | 74.1600036621094 | 74.0309982299805 | 73.8870010375977 | 73.7330017089844 | 73.6039962768555 | 73.4560012817383 | 73.2890014648438 | 73.1060028076172 | 72.4100036621094 | 72.5989990234375 |
201 | Benin | BEN | Labor force participation rate, male (% of male population ages 15+) (national estimate) | SL.TLF.CACT.MA.NE.ZS | .. | .. | .. | .. | 66.6100006103516 | 78.9300003051758 | 76.3899993896484 | .. | .. | .. | .. | .. | .. | 76.0800018310547 | 74.379997253418 | .. | .. | .. | .. | .. | .. | 69.7300033569336 | .. | .. | .. |
202 | Benin | BEN | Labor force participation rate, male (% of male population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.MA.ZS | 84.85 | 83.74 | 82.58 | 81.38 | 80.14 | 78.85 | 78.2 | 77.52 | 76.83 | 76.11 | 75.37 | 74.62 | 73.88 | 73.14 | 74.03 | 73.94 | 73.81 | 73.68 | 73.6 | 73.54 | 73.44 | 73.32 | 73.17 | .. | .. |
203 | Benin | BEN | Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.ZS | 71.9550018310547 | 71.9140014648438 | 71.8730010986328 | 71.8320007324219 | 71.7910003662109 | 71.75 | 71.7639999389648 | 71.7789993286133 | 71.7929992675781 | 71.8079986572266 | 71.8219985961914 | 71.8369979858398 | 71.8509979248047 | 71.8659973144531 | 71.879997253418 | 71.8460006713867 | 71.8059997558594 | 71.7610015869141 | 71.7119979858398 | 71.6709976196289 | 71.6240005493164 | 71.5709991455078 | 71.5130004882813 | 70.8339996337891 | 70.9469985961914 |
204 | Benin | BEN | Labor force participation rate, total (% of total population ages 15+) (national estimate) | SL.TLF.CACT.NE.ZS | .. | .. | .. | .. | 67.6800003051758 | 71.75 | 77.3600006103516 | .. | .. | .. | .. | .. | .. | 75.3099975585938 | 71.879997253418 | .. | .. | .. | .. | .. | .. | 62.7400016784668 | .. | .. | .. |
205 | Benin | BEN | Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.ZS | 73.53 | 73.42 | 73.28 | 73.11 | 72.91 | 72.67 | 72.74 | 72.74 | 72.71 | 72.61 | 72.48 | 72.31 | 72.11 | 71.9 | 71.72 | 71.71 | 71.68 | 71.65 | 71.66 | 71.68 | 71.68 | 71.67 | 71.66 | .. | .. |
206 | Benin | BEN | Labor force with advanced education (% of total working-age population with advanced education) | SL.TLF.ADVN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 66.1699981689453 | .. | .. | .. | .. | .. | .. | 42.4300003051758 | .. | .. | .. |
207 | Benin | BEN | Labor force with advanced education, female (% of female working-age population with advanced education) | SL.TLF.ADVN.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 56.0900001525879 | .. | .. | .. | .. | .. | .. | 32.060001373291 | .. | .. | .. |
208 | Benin | BEN | Labor force with advanced education, male (% of male working-age population with advanced education) | SL.TLF.ADVN.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 69.879997253418 | .. | .. | .. | .. | .. | .. | 47.9500007629395 | .. | .. | .. |
209 | Benin | BEN | Labor force with basic education (% of total working-age population with basic education) | SL.TLF.BASC.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 78.0100021362305 | .. | .. | .. | .. | .. | .. | 74.7200012207031 | .. | .. | .. |
210 | Benin | BEN | Labor force with basic education, female (% of female working-age population with basic education) | SL.TLF.BASC.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 72.25 | .. | .. | .. | .. | .. | .. | 68.0800018310547 | .. | .. | .. |
211 | Benin | BEN | Labor force with basic education, male (% of male working-age population with basic education) | SL.TLF.BASC.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 82.7099990844727 | .. | .. | .. | .. | .. | .. | 80.6399993896484 | .. | .. | .. |
212 | Benin | BEN | Labor force with intermediate education (% of total working-age population with intermediate education) | SL.TLF.INTM.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 45.0699996948242 | .. | .. | .. | .. | .. | .. | 51.5999984741211 | .. | .. | .. |
213 | Benin | BEN | Labor force with intermediate education, female (% of female working-age population with intermediate education) | SL.TLF.INTM.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 41.2799987792969 | .. | .. | .. | .. | .. | .. | 47.6599998474121 | .. | .. | .. |
214 | Benin | BEN | Labor force with intermediate education, male (% of male working-age population with intermediate education) | SL.TLF.INTM.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 47.4599990844727 | .. | .. | .. | .. | .. | .. | 54.8600006103516 | .. | .. | .. |
215 | Benin | BEN | Labor force, female (% of total labor force) | SL.TLF.TOTL.FE.ZS | 44.08888427754066 | 44.647132667797216 | 45.21854911853394 | 45.802107899281786 | 46.39027938525926 | 46.99366045206329 | 47.218182477399814 | 47.45160072247856 | 47.69848077086753 | 47.9840209657798 | 48.28111650070825 | 48.583753037967895 | 48.885221581369805 | 49.18056058372768 | 49.46319587704321 | 49.44973074412739 | 49.443017061255205 | 49.44492125743701 | 49.45680755520578 | 49.46672662557295 | 49.48933028480177 | 49.52362974853586 | 49.56708203801018 | 49.52682020772573 | 49.43977898470418 |
216 | Benin | BEN | Labor force, total | SL.TLF.TOTL.IN | 2467343 | 2542712 | 2621882 | 2705727 | 2790770 | 2881278 | 2978736 | 3079953 | 3184049 | 3282301 | 3383679 | 3488763 | 3598159 | 3712416 | 3825604 | 3942161 | 4063769 | 4189856 | 4320200 | 4451938 | 4588876 | 4730774 | 4877483 | 4985420 | 5147879 |
217 | Benin | BEN | Manufacturing, value added (annual % growth) | NV.IND.MANF.KD.ZG | 4.230071427713696 | 0.7095320875177151 | 3.967035906838774 | 10.60024841099569 | 9.210284853874214 | 2.6063528151573507 | 1.0817134901752468 | 0.061871118174110507 | 6.6232005288496225 | 3.0743968004214963 | -4.119913869676921 | -12.471552155767512 | 0.7870975110567713 | -0.3791341236227197 | 0.36826761549164644 | 0.3401493852181119 | 4.401151870229427 | 8.625262328757557 | 6.246369000506505 | 6.431714280217207 | -0.5629094294442893 | 3.7929333481169607 | 11.25680305283565 | 3.36721654807522 | .. |
218 | Benin | BEN | Manufacturing, value added (constant 2015 US$) | NV.IND.MANF.KD | 774893141.1540064 | 780391256.634468 | 811349657.9989877 | 897354737.2286445 | 980003664.677137 | 1005546017.7800949 | 1016423144.7043421 | 1017052017.0693511 | 1084413411.642564 | 1117752582.8734446 | 1071702139.1829695 | 938044247.9402894 | 945427570.8684386 | 941843132.3331391 | 945311635.5782541 | 948527107.2950689 | 990273225.8174188 | 1075686889.315621 | 1142878261.7123444 | 1216384926.0763955 | 1209537780.6291726 | 1255414742.4687302 | 1396734307.5246994 | 1443765376.260315 | .. |
219 | Benin | BEN | Multidimensional poverty headcount ratio (% of total population) | SI.POV.MDIM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
220 | Benin | BEN | Multidimensional poverty headcount ratio, children (% of population ages 0-17) | SI.POV.MDIM.17 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
221 | Benin | BEN | Multidimensional poverty headcount ratio, female (% of female population) | SI.POV.MDIM.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
222 | Benin | BEN | Multidimensional poverty headcount ratio, household (% of total households) | SI.POV.MDIM.HH | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
223 | Benin | BEN | Multidimensional poverty headcount ratio, male (% of male population) | SI.POV.MDIM.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
224 | Benin | BEN | Multidimensional poverty index (scale 0-1) | SI.POV.MDIM.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
225 | Benin | BEN | Multidimensional poverty index, children (population ages 0-17) (scale 0-1) | SI.POV.MDIM.17.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
226 | Benin | BEN | Multidimensional poverty intensity (average share of deprivations experienced by the poor) | SI.POV.MDIM.IT | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
227 | Benin | BEN | Net bilateral aid flows from DAC donors, Australia (current US$) | DC.DAC.AUSL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 159999.99642372102 | 379999.99523162795 | 529999.971389771 | 109999.999403954 | 310000.002384186 | 50000.0007450581 | 29999.999329447703 | 39999.9991059303 | 9999.99977648258 | 29999.999329447703 | .. | .. | .. |
228 | Benin | BEN | Net bilateral aid flows from DAC donors, Austria (current US$) | DC.DAC.AUTL.CD | 9999.99977648258 | 19999.9995529652 | 29999.999329447703 | 29999.999329447703 | 189999.99761581398 | 9999.99977648258 | 29999.999329447703 | 50000.0007450581 | 39999.9991059303 | 19999.9995529652 | 9999.99977648258 | 19999.9995529652 | 9999.99977648258 | 90000.0035762787 | 50000.0007450581 | 29999.999329447703 | 39999.9991059303 | 39999.9991059303 | 29999.999329447703 | 59999.9986588955 | 39999.9991059303 | 19999.9995529652 | .. | 19999.9995529652 | .. |
229 | Benin | BEN | Net bilateral aid flows from DAC donors, Belgium (current US$) | DC.DAC.BELL.CD | 17780000.6866455 | 3710000.03814697 | 4050000.1907348596 | 4630000.11444092 | 4380000.11444092 | 9800000.19073486 | 10560000.4196167 | 13409999.8474121 | 13119999.8855591 | 14229999.5422363 | 14890000.3433228 | 21920000.0762939 | 25579999.9237061 | 28969999.3133545 | 28389999.3896484 | 25590000.1525879 | 24149999.6185303 | 21149999.6185303 | 19559999.4659424 | 19940000.5340576 | 25270000.4577637 | 27680000.3051758 | 22809999.4659424 | 20100000.3814697 | .. |
230 | Benin | BEN | Net bilateral aid flows from DAC donors, Canada (current US$) | DC.DAC.CANL.CD | 4150000.09536743 | 3759999.99046326 | 3559999.94277954 | 3319999.9332428 | 1750000 | 2400000.09536743 | 5590000.15258789 | 6360000.1335144 | 10840000.1525879 | 5960000.03814697 | 6989999.771118159 | 6969999.79019165 | 7039999.96185303 | 6369999.88555908 | 7739999.771118159 | 5579999.92370605 | 4800000.19073486 | 5429999.82833862 | 6630000.11444092 | 7980000.01907349 | 14520000.4577637 | 18090000.1525879 | 16989999.7711182 | 21040000.915527303 | .. |
231 | Benin | BEN | Net bilateral aid flows from DAC donors, Czech Republic (current US$) | DC.DAC.CZEL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | 9999.99977648258 | 39999.9991059303 | .. | 19999.9995529652 | 19999.9995529652 | 19999.9995529652 | 29999.999329447703 | 19999.9995529652 | 9999.99977648258 | 9999.99977648258 | 9999.99977648258 | .. | .. | .. | .. |
232 | Benin | BEN | Net bilateral aid flows from DAC donors, Denmark (current US$) | DC.DAC.DNKL.CD | 18950000.762939498 | 14609999.6566772 | 9050000.19073486 | 19520000.4577637 | 22930000.3051758 | 23610000.6103516 | 21389999.3896484 | 32200000.7629395 | 35869998.9318848 | 32849998.4741211 | 44639999.3896484 | 48150001.5258789 | 51360000.6103516 | 39110000.6103516 | 36229999.5422363 | 31739999.7711182 | 16700000.7629395 | -4639999.8664856 | -680000.007152557 | 0 | 0 | -170000.00178813902 | .. | 409999.99642372096 | .. |
233 | Benin | BEN | Net bilateral aid flows from DAC donors, European Union institutions (current US$) | DC.DAC.CECL.CD | 31969999.3133545 | 29680000.3051758 | 25309999.4659424 | 2809999.94277954 | 43409999.8474121 | 27850000.3814697 | 51000000 | 88680000.3051758 | 37830001.8310547 | 35119998.9318848 | 81830001.8310547 | 127620002.746582 | 146639999.38964802 | 122750000 | 63130001.0681152 | 79089996.3378906 | 78949996.9482422 | 72180000.3051758 | 48270000.4577637 | 47779998.779296905 | 81370002.746582 | 90569999.6948242 | 45950000.762939505 | 144210006.71386698 | .. |
234 | Benin | BEN | Net bilateral aid flows from DAC donors, Finland (current US$) | DC.DAC.FINL.CD | .. | 9999.99977648258 | .. | 90000.0035762787 | 140000.000596046 | 140000.000596046 | 300000.011920929 | 39999.9991059303 | .. | 100000.00149011599 | 209999.993443489 | 170000.00178813902 | 449999.988079071 | 689999.997615814 | 370000.00476837205 | 259999.990463257 | 159999.99642372102 | 109999.999403954 | 70000.0002980232 | 39999.9991059303 | 9999.99977648258 | 0 | 29999.999329447703 | .. | .. |
235 | Benin | BEN | Net bilateral aid flows from DAC donors, France (current US$) | DC.DAC.FRAL.CD | 26579999.9237061 | 28770000.4577637 | 27579999.9237061 | 74250000 | 42520000.4577637 | 40490001.6784668 | 36759998.3215332 | 62860000.6103516 | 42720001.220703095 | 73750000 | 56400001.5258789 | 66410003.662109405 | 50389999.3896484 | 48790000.9155273 | 41540000.9155273 | 41409999.8474121 | 37889999.3896484 | 36509998.3215332 | 27860000.6103516 | 27620000.8392334 | 42330001.8310547 | 47540000.9155273 | 38110000.6103516 | 68480003.3569336 | .. |
236 | Benin | BEN | Net bilateral aid flows from DAC donors, Germany (current US$) | DC.DAC.DEUL.CD | 20260000.2288818 | 32349998.4741211 | 27350000.3814697 | 21719999.3133545 | 21870000.8392334 | 24010000.2288818 | 31260000.2288818 | 24450000.762939498 | 27600000.3814697 | 26469999.3133545 | 29579999.9237061 | 46610000.6103516 | 43119998.9318848 | 34669998.1689453 | 49500000 | 47630001.0681152 | 50970001.220703095 | 77709999.0844727 | 38380001.0681152 | 39840000.1525879 | 37270000.4577637 | 42099998.4741211 | 45139999.3896484 | 65379997.253418 | .. |
237 | Benin | BEN | Net bilateral aid flows from DAC donors, Greece (current US$) | DC.DAC.GRCL.CD | .. | .. | .. | .. | 59999.9986588955 | 29999.999329447703 | 29999.999329447703 | 39999.9991059303 | 180000.00715255702 | 19999.9995529652 | 140000.000596046 | 100000.00149011599 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
238 | Benin | BEN | Net bilateral aid flows from DAC donors, Hungary (current US$) | DC.DAC.HUNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0 | 0 | 0 | .. | 0 | 0 | .. |
239 | Benin | BEN | Net bilateral aid flows from DAC donors, Iceland (current US$) | DC.DAC.ISLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
240 | Benin | BEN | Net bilateral aid flows from DAC donors, Ireland (current US$) | DC.DAC.IRLL.CD | 59999.9986588955 | 79999.9982118607 | 19999.9995529652 | 59999.9986588955 | 59999.9986588955 | .. | .. | 9999.99977648258 | 29999.999329447703 | 109999.999403954 | 90000.0035762787 | 59999.9986588955 | 39999.9991059303 | 119999.997317791 | 259999.990463257 | 159999.99642372102 | 159999.99642372102 | 150000.005960464 | 29999.999329447703 | 19999.9995529652 | 50000.0007450581 | 109999.999403954 | .. | 19999.9995529652 | .. |
241 | Benin | BEN | Net bilateral aid flows from DAC donors, Italy (current US$) | DC.DAC.ITAL.CD | 360000.01430511504 | 270000.010728836 | 300000.011920929 | 19069999.6948242 | 209999.993443489 | 2539999.96185303 | 19999.9995529652 | 9579999.92370605 | 19999.9995529652 | 109999.999403954 | 1490000.0095367401 | 1139999.98569489 | 1789999.96185303 | 2109999.89509583 | 1200000.04768372 | 769999.980926514 | 1909999.9666214 | 1419999.95708466 | 2369999.8855590797 | 1340000.0333786 | 4809999.94277954 | 2680000.0667572 | 3750000 | 4980000.01907349 | .. |
242 | Benin | BEN | Net bilateral aid flows from DAC donors, Japan (current US$) | DC.DAC.JPNL.CD | 18809999.4659424 | 32950000.7629395 | 14159999.8474121 | 6159999.84741211 | 8260000.22888184 | 4530000.20980835 | 6269999.98092651 | 11149999.6185303 | 17860000.6103516 | 10060000.4196167 | 6809999.94277954 | 27209999.084472697 | 25840000.1525879 | 29129999.1607666 | 26309999.4659424 | 19889999.3896484 | 33520000.4577637 | 10199999.8092651 | 12899999.6185303 | 10920000.076293899 | 20350000.3814697 | 14260000.2288818 | 10390000.3433228 | 18409999.8474121 | .. |
243 | Benin | BEN | Net bilateral aid flows from DAC donors, Korea, Rep. (current US$) | DC.DAC.KORL.CD | 59999.9986588955 | 29999.999329447703 | .. | 9999.99977648258 | 29999.999329447703 | 59999.9986588955 | 70000.0002980232 | 79999.9982118607 | 79999.9982118607 | 209999.993443489 | 19999.9995529652 | 2440000.05722046 | 19999.9995529652 | 150000.005960464 | 129999.995231628 | 140000.000596046 | 100000.00149011599 | 100000.00149011599 | 119999.997317791 | 230000.004172325 | 19999.9995529652 | 180000.00715255702 | 90000.0035762787 | 200000.00298023198 | .. |
244 | Benin | BEN | Net bilateral aid flows from DAC donors, Luxembourg (current US$) | DC.DAC.LUXL.CD | 379999.99523162795 | 379999.99523162795 | 310000.002384186 | 779999.971389771 | .. | 730000.019073486 | 1470000.02861023 | 1419999.95708466 | 1580000.04291534 | 5250000 | 4280000.20980835 | 860000.014305115 | 1159999.9666214 | 1960000.03814697 | 1450000.04768372 | 1259999.9904632599 | 1320000.05245209 | 1440000.0572204601 | 1039999.96185303 | 980000.019073486 | 870000.004768372 | 1419999.95708466 | 1250000 | 1190000.0572204601 | .. |
245 | Benin | BEN | Net bilateral aid flows from DAC donors, Netherlands (current US$) | DC.DAC.NLDL.CD | 11060000.4196167 | 10079999.923706101 | 4639999.8664856 | 4380000.11444092 | 8010000.22888184 | 2400000.09536743 | 19770000.4577637 | 10399999.6185303 | 22700000.762939498 | 24489999.7711182 | 34720001.220703095 | 35330001.8310547 | 41970001.220703095 | 31260000.2288818 | 27809999.4659424 | 20639999.3896484 | 37779998.779296905 | 42580001.8310547 | 17750000 | 29729999.5422363 | 31729999.5422363 | 26329999.9237061 | 31600000.3814697 | 38720001.220703095 | .. |
246 | Benin | BEN | Net bilateral aid flows from DAC donors, New Zealand (current US$) | DC.DAC.NZLL.CD | .. | .. | .. | .. | 59999.9986588955 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
247 | Benin | BEN | Net bilateral aid flows from DAC donors, Norway (current US$) | DC.DAC.NORL.CD | -79999.9982118607 | -1139999.98569489 | .. | .. | 100000.00149011599 | 129999.995231628 | 209999.993443489 | 219999.998807907 | 59999.9986588955 | .. | .. | .. | .. | 50000.0007450581 | 9999.99977648258 | .. | .. | .. | 19999.9995529652 | 19999.9995529652 | .. | .. | 310000.002384186 | 709999.978542328 | .. |
248 | Benin | BEN | Net bilateral aid flows from DAC donors, Poland (current US$) | DC.DAC.POLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | .. | .. | .. | .. | .. | .. | 9999.99977648258 | .. | .. | 19999.9995529652 | 9999.99977648258 | 9999.99977648258 | .. |
249 | Benin | BEN | Net bilateral aid flows from DAC donors, Portugal (current US$) | DC.DAC.PRTL.CD | .. | .. | .. | .. | .. | 19999.9995529652 | 9999.99977648258 | 9999.99977648258 | .. | .. | .. | .. | .. | .. | 9999.99977648258 | .. | .. | .. | .. | .. | .. | 0 | 0 | .. | .. |
250 | Benin | BEN | Net bilateral aid flows from DAC donors, Slovak Republic (current US$) | DC.DAC.SVKL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29999.999329447703 | 19999.9995529652 | 19999.9995529652 | 9999.99977648258 | .. | .. | .. | .. | .. | .. |
251 | Benin | BEN | Net bilateral aid flows from DAC donors, Slovenia (current US$) | DC.DAC.SVNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
252 | Benin | BEN | Net bilateral aid flows from DAC donors, Spain (current US$) | DC.DAC.ESPL.CD | 839999.973773956 | 430000.00715255697 | 529999.971389771 | 479999.989271164 | 589999.973773956 | 319999.99284744303 | 1669999.95708466 | 310000.002384186 | 449999.988079071 | 2190000.05722046 | 2109999.89509583 | 2009999.9904632599 | 3450000.04768372 | 1090000.0333786 | 1220000.02861023 | 550000.011920929 | 620000.004768372 | 610000.014305115 | 159999.99642372102 | 660000.026226044 | 230000.004172325 | 310000.002384186 | 219999.998807907 | 560000.002384186 | .. |
253 | Benin | BEN | Net bilateral aid flows from DAC donors, Sweden (current US$) | DC.DAC.SWEL.CD | 9999.99977648258 | .. | 230000.004172325 | 180000.00715255702 | 90000.0035762787 | 90000.0035762787 | 219999.998807907 | 90000.0035762787 | 1419999.95708466 | 230000.004172325 | 300000.011920929 | 469999.998807907 | 879999.995231628 | 1879999.99523163 | 349999.99403953605 | 680000.007152557 | 889999.985694885 | 860000.014305115 | 649999.976158142 | 860000.014305115 | 699999.988079071 | 660000.026226044 | 259999.990463257 | 860000.014305115 | .. |
254 | Benin | BEN | Net bilateral aid flows from DAC donors, Switzerland (current US$) | DC.DAC.CHEL.CD | 6800000.19073486 | 8140000.34332275 | 6309999.94277954 | 6000000 | 5730000.01907349 | 5360000.1335144 | 6980000.01907349 | 9439999.5803833 | 8699999.80926514 | 9989999.77111816 | 10260000.2288818 | 10579999.923706101 | 13470000.2670288 | 13250000 | 12149999.6185303 | 21059999.4659424 | 19049999.237060502 | 19590000.1525879 | 21610000.6103516 | 23489999.7711182 | 23659999.8474121 | 28309999.4659424 | 25290000.915527303 | 28010000.2288818 | .. |
255 | Benin | BEN | Net bilateral aid flows from DAC donors, Total (current US$) | DC.DAC.TOTL.CD | 180000001.06915838 | 173659999.7095765 | 144579999.7169525 | 193349998.7013638 | 187890002.31213877 | 167960002.75388357 | 247209999.33965498 | 298740001.65611523 | 245520003.4230948 | 263719996.7447669 | 319980004.22306365 | 432680010.67079616 | 472300001.32694805 | 463100000.38146925 | 486999998.0963767 | 338909995.1833486 | 332989997.44839966 | 324699997.3021448 | 232450000.6847085 | 269699999.1964549 | 404100008.09840834 | 357769999.8077006 | 342339999.8024107 | 510710007.2409954 | .. |
256 | Benin | BEN | Net bilateral aid flows from DAC donors, United Kingdom (current US$) | DC.DAC.GBRL.CD | .. | .. | 1570000.05245209 | 140000.000596046 | 70000.0002980232 | 59999.9986588955 | 21129999.1607666 | .. | .. | 2279999.97138977 | -140000.000596046 | .. | 29999.999329447703 | .. | 70000.0002980232 | 610000.014305115 | .. | .. | .. | .. | 409999.99642372096 | 519999.980926514 | 219999.998807907 | 19999.9995529652 | .. |
257 | Benin | BEN | Net bilateral aid flows from DAC donors, United States (current US$) | DC.DAC.USAL.CD | 22000000 | 9529999.73297119 | 19579999.9237061 | 29719999.3133545 | 27430000.3051758 | 23379999.1607666 | 32470001.220703095 | 27940000.5340576 | 24409999.8474121 | 20270000.4577637 | 25329999.9237061 | 34560001.373291 | 58900001.5258789 | 100260002.13623 | 188529998.779297 | 41659999.8474121 | 23620000.8392334 | 39169998.1689453 | 35619998.9318848 | 58139999.3896484 | 120440002.441406 | 57110000.6103516 | 99919998.1689453 | 97379997.253418 | .. |
258 | Benin | BEN | Net migration | SM.POP.NETM | -2851 | .. | .. | .. | .. | 25005 | .. | .. | .. | .. | -48776 | .. | .. | .. | .. | -42268 | .. | .. | .. | .. | -10000 | .. | .. | .. | .. |
259 | Benin | BEN | Net ODA provided to the least developed countries (% of GNI) | DC.ODA.TLDC.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
260 | Benin | BEN | Net ODA provided, to the least developed countries (current US$) | DC.ODA.TLDC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
261 | Benin | BEN | Net ODA provided, total (% of GNI) | DC.ODA.TOTL.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
262 | Benin | BEN | Net ODA provided, total (constant 2020 US$) | DC.ODA.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
263 | Benin | BEN | Net ODA provided, total (current US$) | DC.ODA.TOTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
264 | Benin | BEN | Net ODA received (% of central government expense) | DT.ODA.ODAT.XP.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
265 | Benin | BEN | Net ODA received (% of GNI) | DT.ODA.ODAT.GN.ZS | 9.87946497939251 | 8.405199833978415 | 5.796372427269806 | 6.978089813805438 | 7.679303275608331 | 5.31772087862949 | 5.686038199623279 | 6.367252632537852 | 5.3295557527446045 | 5.715552783533516 | 5.852946694709436 | 6.51283905462634 | 6.981197111838293 | 7.26939370345912 | 6.299143707338906 | 4.584444386420962 | 5.303310112311597 | 4.532304901111709 | 3.864764559616221 | 4.273313534121435 | 5.413402154575786 | 4.073524241887823 | 4.162700507791413 | 6.773458722281244 | .. |
266 | Benin | BEN | Net ODA received (% of gross capital formation) | DT.ODA.ODAT.GI.ZS | 52.572988990984804 | 46.0439900101091 | 31.69411820959497 | 43.437878700767314 | 43.08491754921917 | 35.607219334948795 | 37.229843748812385 | 41.58807923599851 | 43.977491150890586 | 44.20706868974979 | 35.5268213106483 | 47.34413886016774 | 46.801967911689054 | 46.31303815144238 | 38.20791761112338 | 29.830394932389563 | 27.961542886194866 | 23.426682339248885 | 18.49021594325849 | 20.89659595417826 | 22.343651156023117 | 15.268569166544738 | 16.079713803078242 | 26.1491969361573 | .. |
267 | Benin | BEN | Net ODA received (% of imports of goods, services and primary income) | DT.ODA.ODAT.MP.ZS | 27.831269566212193 | 25.384560748612127 | 23.872856908731375 | 32.84071760378547 | 35.88628122143941 | 23.59981098381045 | 26.582084318115612 | 32.89128828322445 | 29.378079425908904 | 27.545048598307865 | 21.68980420567601 | 25.821149889721873 | 29.217188819970435 | 28.778503536599853 | 27.720043755222278 | 18.48883608284243 | 18.44656623698962 | 13.674874966756933 | 11.941848320032662 | 12.959227745856952 | 16.312921366935026 | 11.89533013060441 | 13.176130566652445 | 24.537800704813527 | .. |
268 | Benin | BEN | Net ODA received per capita (current US$) | DT.ODA.ODAT.PC.ZS | 35.205750898408766 | 31.71889845911325 | 31.87826393434644 | 35.64985863163809 | 39.62565940470426 | 30.36707970586027 | 40.15527445502367 | 50.553529920559 | 43.73217668464863 | 48.71792751330631 | 56.21547176747406 | 73.21216439428521 | 75.74977504125555 | 74.92672987736289 | 71.09419114874214 | 52.183856177984254 | 65.98968555915722 | 58.26085227193883 | 41.277567732653445 | 46.059298518775904 | 60.849066396353635 | 50.03119148975715 | 50.258655732102994 | 86.53904727802103 | .. |
269 | Benin | BEN | Net official aid received (constant 2020 US$) | DT.ODA.OATL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
270 | Benin | BEN | Net official aid received (current US$) | DT.ODA.OATL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
271 | Benin | BEN | Net official development assistance and official aid received (constant 2020 US$) | DT.ODA.ALLD.KD | 306869995.11718804 | 278540008.544922 | 296160003.66210896 | 382929992.675781 | 439799987.792969 | 333579986.57226604 | 384390014.64843804 | 455540008.544922 | 396720001.220703 | 441820007.324219 | 480429992.675781 | 604030029.296875 | 661989990.234375 | 689130004.882813 | 655219970.703125 | 493179992.675781 | 625570007.324219 | 568099975.585938 | 465690002.441406 | 533330017.089844 | 708780029.296875 | 574619995.117188 | 612289978.027344 | .. | .. |
272 | Benin | BEN | Net official development assistance and official aid received (current US$) | DT.ODA.ALLD.CD | 221149993.89648402 | 205229995.727539 | 212440002.44140598 | 244770004.272461 | 280420013.42773396 | 221539993.28613302 | 301989990.234375 | 391790008.544922 | 349079986.57226604 | 400309997.558594 | 475290008.544922 | 636719970.703125 | 677559997.558594 | 689270019.53125 | 672609985.351563 | 507709991.455078 | 660200012.207031 | 599320007.324219 | 436549987.792969 | 500760009.765625 | 680000000 | 574609985.351563 | 593109985.351563 | 1049130004.88281 | .. |
273 | Benin | BEN | Net official development assistance received (constant 2020 US$) | DT.ODA.ODAT.KD | 310350006.10351604 | 283070007.324219 | 299950012.207031 | 386420013.42773396 | 444160003.66210896 | 336459991.455078 | 389250000 | 459459991.455078 | 401179992.675781 | 446600006.10351604 | 484529998.779297 | 609739990.234375 | 668809997.558594 | 697400024.414063 | 665510009.765625 | 498589996.33789104 | 633210021.972656 | 575219970.703125 | 471399993.89648396 | 540150024.414063 | 717900024.414063 | 579830017.089844 | 609789978.027344 | 1049130004.88281 | .. |
274 | Benin | BEN | Net official development assistance received (current US$) | DT.ODA.ODAT.CD | 221149993.89648402 | 205229995.727539 | 212440002.44140598 | 244770004.272461 | 280420013.42773396 | 221539993.28613302 | 301989990.234375 | 391790008.544922 | 349079986.57226604 | 400309997.558594 | 475290008.544922 | 636719970.703125 | 677559997.558594 | 689270019.53125 | 672609985.351563 | 507709991.455078 | 660200012.207031 | 599320007.324219 | 436549987.792969 | 500760009.765625 | 680000000 | 574609985.351563 | 593109985.351563 | 1049130004.88281 | .. |
275 | Benin | BEN | Net official flows from UN agencies, FAO (current US$) | DT.NFL.FAOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 730363.667011261 | .. | .. | .. | .. | 494055.00292778 | 534642.87519455 | .. | .. |
276 | Benin | BEN | Net official flows from UN agencies, IAEA (current US$) | DT.NFL.IAEA.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | 239999.994635582 | 300000.011920929 | 270000.010728836 | 300000.011920929 | 289999.99165535 | 180000.00715255702 | 409999.99642372096 | 519999.980926514 | 280000.001192093 | 353477.53763198905 | 435783.14781189 | 521373.03352356004 | 343037.009239197 | 389500.617980957 | 332713.782787323 | .. |
277 | Benin | BEN | Net official flows from UN agencies, IFAD (current US$) | DT.NFL.IFAD.CD | 280000.001192093 | 1289999.96185303 | 1230000.01907349 | 1700000.04768372 | 2059999.94277954 | 2490000.00953674 | 4829999.92370605 | 6369999.88555908 | 6340000.15258789 | 2819999.9332428 | 1250000 | 689999.997615814 | 1570000.05245209 | 1649999.97615814 | 850000.023841858 | 639999.985694885 | 1820000.05245209 | 3680000.0667572 | 1943029.99973297 | 369576.156139374 | 777830.123901367 | -669225.513935089 | 2367526.53121948 | 3747330.4271698 | .. |
278 | Benin | BEN | Net official flows from UN agencies, ILO (current US$) | DT.NFL.ILOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 236328.24420929 | 322596.75860405003 | 265480.011701584 | 326950.013637543 | 238480.001688004 | 266880.005598068 | 216829.165816307 | 281019.985675812 | 101952.10576057399 | .. |
279 | Benin | BEN | Net official flows from UN agencies, UNAIDS (current US$) | DT.NFL.UNAI.CD | .. | .. | .. | .. | .. | .. | .. | .. | 100000.00149011599 | 239999.994635582 | 170000.00178813902 | 469999.998807907 | 490000.009536743 | 469999.998807907 | 600000.023841858 | 385794.997215271 | 379293.739795685 | 369347.393512726 | 482244.01473999 | 480904.102325439 | 436300.009489059 | 134205.69896698 | 531637.0129585271 | .. | .. |
280 | Benin | BEN | Net official flows from UN agencies, UNDP (current US$) | DT.NFL.UNDP.CD | 5510000.228881841 | 4460000.03814697 | 3359999.89509583 | 2970000.02861023 | 860000.014305115 | 2839999.91416931 | 5019999.98092651 | 2250000 | 3240000.00953674 | 2440000.05722046 | 2920000.07629395 | 5840000.15258789 | 5849999.90463257 | 5000000 | 3859999.89509583 | 3988340.85464478 | 3956039.9055481004 | 4242110.25238037 | 3781036.6153717 | 3898795.60470581 | 3400936.1267089797 | 3788172.0066070603 | 4462170.124053961 | 4759504.3182373 | .. |
281 | Benin | BEN | Net official flows from UN agencies, UNECE (current US$) | DT.NFL.UNEC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
282 | Benin | BEN | Net official flows from UN agencies, UNEP (current US$) | DT.NFL.UNEP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
283 | Benin | BEN | Net official flows from UN agencies, UNFPA (current US$) | DT.NFL.UNFP.CD | 2940000.05722046 | 2609999.89509583 | 1440000.0572204601 | 720000.028610229 | 1870000.00476837 | 3579999.92370605 | 1690000.0572204601 | 1870000.00476837 | 2190000.05722046 | 1759999.9904632599 | 2039999.96185303 | 2690000.05722046 | 2079999.9237060498 | 2000000 | 2089999.9141693101 | 2390358.92486572 | 2201914.07203674 | 1819869.9951171898 | 1832405.32875061 | 1641820.5499649 | 1449267.98343658 | 1559370.04089355 | 2312926.29241943 | 2298830.03234863 | .. |
284 | Benin | BEN | Net official flows from UN agencies, UNHCR (current US$) | DT.NFL.UNCR.CD | 1340000.0333786 | 2230000.01907349 | 1450000.04768372 | 769999.980926514 | 610000.014305115 | 1139999.98569489 | 750000 | 899999.976158142 | 430000.00715255697 | 319999.99284744303 | 579999.983310699 | 740000.009536743 | 610000.014305115 | 370000.00476837205 | .. | .. | .. | .. | 480592.310428619 | .. | .. | 164666.667580605 | 259661.34667396502 | .. | .. |
285 | Benin | BEN | Net official flows from UN agencies, UNICEF (current US$) | DT.NFL.UNCF.CD | 1399999.97615814 | 1690000.0572204601 | 1730000.01907349 | 1980000.01907349 | 1840000.0333786 | 1570000.05245209 | 1759999.9904632599 | 2089999.9141693101 | 3109999.89509583 | 4260000.228881841 | 5349999.90463257 | 5409999.84741211 | 4920000.07629395 | 6389999.8664856 | 7289999.96185303 | 5178220.74890137 | 5313139.91546631 | 5618047.23739624 | 5305165.29083252 | 6778899.6696472205 | 8121789.93225098 | 6963368.41583252 | 7986000.06103516 | 8895000.45776367 | .. |
286 | Benin | BEN | Net official flows from UN agencies, UNIDIR (current US$) | DT.NFL.UNID.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
287 | Benin | BEN | Net official flows from UN agencies, UNPBF (current US$) | DT.NFL.UNPB.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 490000.009536743 | .. |
288 | Benin | BEN | Net official flows from UN agencies, UNRWA (current US$) | DT.NFL.UNRW.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
289 | Benin | BEN | Net official flows from UN agencies, UNTA (current US$) | DT.NFL.UNTA.CD | 1679999.94754791 | 1070000.05245209 | 1830000.04291534 | 1870000.00476837 | 1039999.96185303 | 2390000.10490417 | 1799999.95231628 | 1960000.03814697 | 2920000.07629395 | 1429999.94754791 | 1909999.9666214 | 839999.973773956 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
290 | Benin | BEN | Net official flows from UN agencies, UNWTO (current US$) | DT.NFL.UNWT.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
291 | Benin | BEN | Net official flows from UN agencies, WFP (current US$) | DT.NFL.WFPG.CD | 3869999.8855590797 | 4289999.96185303 | 819999.992847443 | 1899999.97615814 | 1759999.9904632599 | 1370000.00476837 | 2500000 | 2309999.94277954 | 2660000.08583069 | 2519999.98092651 | 1299999.95231628 | 2029999.97138977 | 2119999.8855590797 | 1269999.98092651 | -39999.9991059303 | 823812.5443458561 | 346343.994140625 | 230900.004506111 | 1496691.94221497 | 1544464.94579315 | 2774169.921875 | 2399442.19589233 | 28559.9995404482 | .. | .. |
292 | Benin | BEN | Net official flows from UN agencies, WHO (current US$) | DT.NFL.WHOL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1070000.05245209 | 1346047.28221893 | 1190485.47744751 | 1511163.71154785 | 1405311.1076355001 | 1206724.52449799 | 1361762.52365112 | 1500711.20262146 | 944777.369499207 | 1254536.0326767 | .. |
293 | Benin | BEN | Number of surgical procedures (per 100,000 population) | SH.SGR.PROC.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
294 | Benin | BEN | Nurses and midwives (per 1,000 people) | SH.MED.NUMW.P3 | .. | .. | .. | .. | .. | .. | .. | 0.747 | .. | .. | .. | 0.8197 | .. | 0.452 | 0.4247 | 0.6802 | 0.582 | .. | .. | 0.7596 | .. | 0.3888 | 0.3029 | .. | .. |
295 | Benin | BEN | Out-of-pocket expenditure (% of current health expenditure) | SH.XPD.OOPC.CH.ZS | .. | .. | .. | 52.36999512 | 49.88695526 | 52.65975571 | 53.0214653 | 51.0565033 | 51.10164261 | 50.49408722 | 49.00123596 | 47.32984543 | 46.01295471 | 44.99471283 | 43.57491302 | 37.40644836 | 42.31209183 | 44.01254272 | 40.49658966 | 43.00109863 | 43.86722565 | 44.68420029 | 47.04356766 | .. | .. |
296 | Benin | BEN | Out-of-pocket expenditure per capita (current US$) | SH.XPD.OOPC.PC.CD | .. | .. | .. | 8.33037177 | 8.3972218 | 9.21395976 | 11.45601704 | 12.54451451 | 12.33948779 | 12.85233832 | 13.70084789 | 14.36456871 | 14.15381337 | 13.97804988 | 15.24966244 | 14.626222 | 15.13387123 | 15.16123604 | 12.6782589 | 12.80842055 | 13.05866075 | 13.88446199 | 13.70157679 | .. | .. |
297 | Benin | BEN | Out-of-pocket expenditure per capita, PPP (current international $) | SH.XPD.OOPC.PP.CD | .. | .. | .. | 28.59346514 | 29.78851221 | 30.36969835 | 31.19557198 | 31.65618527 | 30.7822201 | 32.05767791 | 32.02561742 | 29.96813575 | 30.59714492 | 31.88102172 | 32.60112426 | 31.91186494 | 32.29092441 | 33.26444391 | 33.98967087 | 35.39712118 | 34.97934789 | 36.22958992 | 38.57081966 | .. | .. |
298 | Benin | BEN | Part time employment, female (% of total female employment) | SL.TLF.PART.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29.8799991607666 | 31.6900005340576 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
299 | Benin | BEN | Part time employment, male (% of total male employment) | SL.TLF.PART.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.2099990844727 | 20.1800003051758 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
300 | Benin | BEN | Part time employment, total (% of total employment) | SL.TLF.PART.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 25.3099994659424 | 26.1299991607666 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
301 | Benin | BEN | Physicians (per 1,000 people) | SH.MED.PHYS.ZS | .. | .. | .. | .. | .. | .. | .. | 0.0401 | .. | .. | .. | 0.0623 | .. | 0.0558 | 0.0577 | .. | .. | .. | .. | 0.0481 | .. | 0.0791 | 0.0647 | .. | .. |
302 | Benin | BEN | Poverty gap at $1.90 a day (2011 PPP) (%) | SI.POV.GAPS | .. | .. | .. | .. | .. | .. | 17.5 | .. | .. | .. | .. | .. | .. | .. | 19.1 | .. | .. | .. | 22.4 | .. | .. | 4.5 | .. | .. | .. |
303 | Benin | BEN | Poverty gap at $3.20 a day (2011 PPP) (%) | SI.POV.LMIC.GP | .. | .. | .. | .. | .. | .. | 38.1 | .. | .. | .. | .. | .. | .. | .. | 38.5 | .. | .. | .. | 39.6 | .. | .. | 17.2 | .. | .. | .. |
304 | Benin | BEN | Poverty gap at $5.50 a day (2011 PPP) (%) | SI.POV.UMIC.GP | .. | .. | .. | .. | .. | .. | 59.2 | .. | .. | .. | .. | .. | .. | .. | 57.8 | .. | .. | .. | 59.3 | .. | .. | 38.3 | .. | .. | .. |
305 | Benin | BEN | Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) | SI.POV.DDAY | .. | .. | .. | .. | .. | .. | 51.4 | .. | .. | .. | .. | .. | .. | .. | 53.2 | .. | .. | .. | 49.6 | .. | .. | 19.2 | .. | .. | .. |
306 | Benin | BEN | Poverty headcount ratio at $3.20 a day (2011 PPP) (% of population) | SI.POV.LMIC | .. | .. | .. | .. | .. | .. | 79.8 | .. | .. | .. | .. | .. | .. | .. | 76.8 | .. | .. | .. | 76.2 | .. | .. | 51.3 | .. | .. | .. |
307 | Benin | BEN | Poverty headcount ratio at $5.50 a day (2011 PPP) (% of population) | SI.POV.UMIC | .. | .. | .. | .. | .. | .. | 93.8 | .. | .. | .. | .. | .. | .. | .. | 90.1 | .. | .. | .. | 90.6 | .. | .. | 79.3 | .. | .. | .. |
308 | Benin | BEN | Poverty headcount ratio at national poverty lines (% of population) | SI.POV.NAHC | .. | .. | .. | .. | .. | .. | .. | .. | .. | 37.5 | 33 | .. | .. | 35.2 | 36.2 | .. | .. | .. | 40.1 | .. | .. | .. | 38.5 | .. | .. |
309 | Benin | BEN | PPP conversion factor, GDP (LCU per international $) | PA.NUS.PPP | 133.375897501819 | 138.791453532355 | 203.025667961988 | 207.146130876974 | 206.573498714727 | 210.632783342373 | 212.880331195101 | 208.910874222034 | 211.256183265881 | 209.22475427275 | 204.514006075421 | 213.576494487756 | 217.605924292001 | 216.915906498762 | 220.433578491211 | 234.004196166992 | 231.47721862793 | 225.044235229492 | 220.523895263672 | 214.433868408203 | 216.77360534668 | 213.135125504233 | 208.557300547294 | 212.004495284801 | 209.042140897802 |
310 | Benin | BEN | PPP conversion factor, private consumption (LCU per international $) | PA.NUS.PRVT.PP | 206.859714834669 | 215.417129894559 | 211.4934135656 | 213.106661764563 | 215.506867989612 | 217.422789613367 | 215.758471446469 | 211.969051714755 | 216.011453918456 | 217.175431355212 | 213.892853841643 | 222.355121822667 | 225.148090229367 | 226.405835245701 | 225.412475585938 | 226.481079101563 | 229.217330932617 | 224.445343017578 | 221.996673583984 | 215.950271606445 | 219.476272583008 | 215.624651809854 | 210.293480934838 | 214.010071707099 | 207.950812633461 |
311 | Benin | BEN | Price level ratio of PPP conversion factor (GDP) to market exchange rate | PA.NUS.PPPC.RF | 0.2285127462598159 | 0.23525897121147016 | 0.32986917216715655 | 0.29166966702286373 | 0.28205099321683696 | 0.30363092895215626 | 0.3670999925074695 | 0.39616123666800807 | 0.40066916575607137 | 0.4004871780264022 | 0.42728710091959893 | 0.4788710638738924 | 0.46270248379416123 | 0.4383961304703025 | 0.4677649514316032 | 0.4583318160347683 | 0.468672618135204 | 0.45577905426308024 | 0.37300326645036286 | 0.36184921034867545 | 0.37332483723032267 | 0.3837185498589567 | 0.3559538915420499 | 0.3683280956882221 | 0.37697126759222166 |
312 | Benin | BEN | Proportion of people living below 50 percent of median income (%) | SI.DST.50MD | .. | .. | .. | .. | .. | .. | 11 | .. | .. | .. | .. | .. | .. | .. | 11.8 | .. | .. | .. | 20.1 | .. | .. | 10.9 | .. | .. | .. |
313 | Benin | BEN | Proportion of seats held by women in national parliaments (%) | SG.GEN.PARL.ZS | 7.2289156626506 | 7.2289156626506 | 6.02409638554217 | 6.02409638554217 | 6.02409638554217 | 6.02409638554217 | 6.02409638554217 | 7.2289156626506 | 7.2289156626506 | 7.2289156626506 | 10.8433734939759 | 10.8433734939759 | 10.8433734939759 | 10.8433734939759 | 8.43373493975904 | 8.43373493975904 | 8.43373493975904 | 8.43373493975904 | 7.2289156626506 | 7.2289156626506 | 7.2289156626506 | 7.2289156626506 | 7.2289156626506 | 7.2289156626506 | 8.43373493975904 |
314 | Benin | BEN | Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day) | SG.TIM.UWRK.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
315 | Benin | BEN | Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day) | SG.TIM.UWRK.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
316 | Benin | BEN | Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of ever-partnered women ages 15-49) | SG.VAW.1549.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
317 | Benin | BEN | Ratio of female to male labor force participation rate (%) (modeled ILO estimate) | SL.TLF.CACT.FM.ZS | 72.62435383719051 | 74.50873562384808 | 76.49092491427622 | 78.57947063045307 | 80.78254655099462 | 83.11112396664853 | 84.2121424352945 | 85.33116921150143 | 86.46714721577969 | 87.62307777574138 | 88.79746493869764 | 89.99431601715332 | 91.21032623074379 | 92.44713092689598 | 93.70784247575898 | 93.88618664033 | 94.10247407323884 | 94.34541753605265 | 94.60757349809586 | 94.82908544592682 | 95.085492611413 | 95.37720473663909 | 95.69938896802903 | 95.69948089353572 | 95.50269365477844 |
318 | Benin | BEN | Ratio of female to male labor force participation rate (%) (national estimate) | SL.TLF.CACT.FM.NE.ZS | .. | .. | .. | .. | 103.13766149037656 | 83.11161563472008 | 102.50033208190892 | .. | .. | .. | .. | .. | .. | 98.1072523570596 | 93.70798537511274 | .. | .. | .. | .. | .. | .. | 81.19890464088841 | .. | .. | .. |
319 | Benin | BEN | Refugee population by country or territory of asylum | SM.POP.REFG | 2914 | 2898 | 3652 | 4290 | 4794 | 5014 | 5032 | 4800 | 30288 | 10785 | 7611 | 6927 | 7204 | 7136 | 7213 | 4960 | 190 | 414 | 526 | 804 | 1056 | 1167 | 1238 | 1396 | 1736 |
320 | Benin | BEN | Refugee population by country or territory of origin | SM.POP.REFG.OR | 41 | 45 | 44 | 47 | 52 | 228 | 274 | 299 | 402 | 207 | 265 | 315 | 409 | 438 | 460 | 451 | 294 | 330 | 400 | 479 | 572 | 659 | 721 | 606 | 730 |
321 | Benin | BEN | Self-employed, female (% of female employment) (modeled ILO estimate) | SL.EMP.SELF.FE.ZS | 95.9599990844727 | 96.0100021362305 | 95.7600021362305 | 95.6999969482422 | 95.5199966430664 | 95.4400024414063 | 95.3899993896484 | 95.4400024414063 | 95.370002746582 | 95.4000015258789 | 95.4000015258789 | 95.5100021362305 | 95.4599990844727 | 95.370002746582 | 95.4199981689453 | 95.4199981689453 | 95.2399978637695 | 94.9899978637695 | 94.7900009155273 | 94.8499984741211 | 94.5199966430664 | 94.3199996948242 | 93.8499984741211 | .. | .. |
322 | Benin | BEN | Self-employed, male (% of male employment) (modeled ILO estimate) | SL.EMP.SELF.MA.ZS | 86.0699996948242 | 86.1100006103516 | 85.9199981689453 | 85.7399978637695 | 85.3000030517578 | 85.120002746582 | 84.9000015258789 | 85 | 84.8399963378906 | 84.8399963378906 | 84.8600006103516 | 85.0100021362305 | 84.8300018310547 | 84.6800003051758 | 84.8499984741211 | 84.870002746582 | 84.5599975585938 | 84.2399978637695 | 83.8000030517578 | 84.0599975585938 | 83.5100021362305 | 83.2200012207031 | 82.5299987792969 | .. | .. |
323 | Benin | BEN | Self-employed, total (% of total employment) (modeled ILO estimate) | SL.EMP.SELF.ZS | 90.4599990844727 | 90.5599975585938 | 90.3899993896484 | 90.3300018310547 | 90.0599975585938 | 89.9899978637695 | 89.8899993896484 | 90 | 89.9100036621094 | 89.9599990844727 | 90.0100021362305 | 90.1800003051758 | 90.0899963378906 | 90 | 90.0199966430664 | 90.0299987792969 | 89.7900009155273 | 89.5100021362305 | 89.1900024414063 | 89.3499984741211 | 88.9100036621094 | 88.6699981689453 | 88.0999984741211 | .. | .. |
324 | Benin | BEN | Services, value added (annual % growth) | NV.SRV.TOTL.KD.ZG | 6.170111146675012 | 4.214635484474741 | 5.896489710740553 | 12.514646935578185 | 7.448235244141216 | 2.5327595634786064 | 5.711356475358855 | 3.1717258465008342 | 4.859523362407401 | 5.481408309433647 | 8.288261991707401 | 12.902628181735082 | -0.3415567740317442 | 2.4291252837945336 | 8.711358192754176 | 5.6094599504924645 | 8.755674640043168 | 4.988389780788623 | -0.024821291929967515 | 1.851688747135256 | 5.462127354415742 | 5.700311558059838 | 5.217024328433382 | 4.856620360034114 | .. |
325 | Benin | BEN | Services, value added (constant 2015 US$) | NV.SRV.TOTL.KD | 2077523794.77605 | 2165083849.8290877 | 2292747796.2631655 | 2579677088.08875 | 2771817506.1488123 | 2842020979.1179705 | 3004338928.339882 | 3099628322.646524 | 3250255485.1333284 | 3428415259.3732495 | 3712571298.2337794 | 4191590568.8266993 | 4177273907.299196 | 4278745123.9547524 | 4651481937.857454 | 4912404954.265959 | 5342519149.062848 | 5609024828.331374 | 5607632595.90431 | 5711468497.66336 | 6023436180.813067 | 6366790809.620313 | 6698947835.098665 | 7024290299.566132 | .. |
326 | Benin | BEN | Services, value added per worker (constant 2015 US$) | NV.SRV.EMPL.KD | 2784.374194484838 | 2780.040138269271 | 2814.9531614978614 | 3016.937805665903 | 3088.8530512736493 | 3021.68786488463 | 3043.646612450782 | 2986.084181514915 | 2996.6185715199476 | 3021.0188794597443 | 3115.5116828429464 | 3357.298890917389 | 3213.342027788153 | 3160.023156825308 | 3347.8193972679 | 3371.641946805001 | 3485.6793352857126 | 3479.3882327637893 | 3332.7025787645157 | 3237.7250993034686 | 3251.9873021215453 | 3268.641682069578 | 3272.6709722172777 | .. | .. |
327 | Benin | BEN | Share of youth not in education, employment or training, female (% of female youth population) | SL.UEM.NEET.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 23.1800003051758 | .. | .. | .. | .. | .. | .. | 40.6800003051758 | .. | .. | .. |
328 | Benin | BEN | Share of youth not in education, employment or training, male (% of male youth population) | SL.UEM.NEET.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.8900003433228 | .. | .. | .. | .. | .. | .. | 28.9599990844727 | .. | .. | .. |
329 | Benin | BEN | Share of youth not in education, employment or training, total (% of youth population) | SL.UEM.NEET.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 17.2299995422363 | .. | .. | .. | .. | .. | .. | 35.0999984741211 | .. | .. | .. |
330 | Benin | BEN | Specialist surgical workforce (per 100,000 population) | SH.MED.SAOP.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.86 | .. | .. | .. | .. | .. | .. | .. |
331 | Benin | BEN | Survey mean consumption or income per capita, bottom 40% of population (2011 PPP $ per day) | SI.SPR.PC40 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.06 | .. | .. | .. | 0.87 | .. | .. | .. | .. | .. | .. |
332 | Benin | BEN | Survey mean consumption or income per capita, total population (2011 PPP $ per day) | SI.SPR.PCAP | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.7 | .. | .. | .. | 2.71 | .. | .. | .. | .. | .. | .. |
333 | Benin | BEN | Unemployment with advanced education (% of total labor force with advanced education) | SL.UEM.ADVN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 12.1000003814697 | .. | .. | .. | .. | .. | .. | 2.25999999046326 | .. | .. | .. |
334 | Benin | BEN | Unemployment with advanced education, female (% of female labor force with advanced education) | SL.UEM.ADVN.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 16.1800003051758 | .. | .. | .. | .. | .. | .. | 3.85999989509583 | .. | .. | .. |
335 | Benin | BEN | Unemployment with advanced education, male (% of male labor force with advanced education) | SL.UEM.ADVN.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.8999996185303 | .. | .. | .. | .. | .. | .. | 1.69000005722046 | .. | .. | .. |
336 | Benin | BEN | Unemployment with basic education (% of total labor force with basic education) | SL.UEM.BASC.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.46000003814697 | .. | .. | .. | .. | .. | .. | 0.829999983310699 | .. | .. | .. |
337 | Benin | BEN | Unemployment with basic education, female (% of female labor force with basic education) | SL.UEM.BASC.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.50999999046326 | .. | .. | .. | .. | .. | .. | 1.35000002384186 | .. | .. | .. |
338 | Benin | BEN | Unemployment with basic education, male (% of male labor force with basic education) | SL.UEM.BASC.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.71000003814697 | .. | .. | .. | .. | .. | .. | 0.439999997615814 | .. | .. | .. |
339 | Benin | BEN | Unemployment with intermediate education (% of total labor force with intermediate education) | SL.UEM.INTM.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.05000019073486 | .. | .. | .. | .. | .. | .. | 2 | .. | .. | .. |
340 | Benin | BEN | Unemployment with intermediate education, female (% of female labor force with intermediate education) | SL.UEM.INTM.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.36999988555908 | .. | .. | .. | .. | .. | .. | 3.25999999046326 | .. | .. | .. |
341 | Benin | BEN | Unemployment with intermediate education, male (% of male labor force with intermediate education) | SL.UEM.INTM.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.76999998092651 | .. | .. | .. | .. | .. | .. | 1.10000002384186 | .. | .. | .. |
342 | Benin | BEN | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS | 0.505999982357025 | 0.493999987840652 | 0.476999998092651 | 0.46000000834465 | 0.444000005722046 | 0.426999986171722 | 0.515999972820282 | 0.601999998092651 | 0.697000026702881 | 0.779999971389771 | 0.864000022411346 | 0.957000017166138 | 1.05599999427795 | 1.14699995517731 | 2.87299990653992 | 2.69799995422363 | 2.51799988746643 | 2.3659999370575 | 2.24300003051758 | 2.06699991226196 | 1.8860000371933 | 1.7150000333786 | 1.71700000762939 | 1.8400000333786 | 1.86000001430511 |
343 | Benin | BEN | Unemployment, female (% of female labor force) (national estimate) | SL.UEM.TOTL.FE.NE.ZS | .. | .. | .. | .. | .. | 0.430000007152557 | .. | .. | .. | .. | .. | .. | .. | 1.13999998569489 | 2.85999989509583 | .. | .. | .. | .. | .. | .. | 1.73000001907349 | .. | .. | .. |
344 | Benin | BEN | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS | 1.56099998950958 | 1.44900000095367 | 1.31400001049042 | 1.182000041008 | 1.05400002002716 | 0.922999978065491 | 0.930999994277954 | 0.929000020027161 | 0.941999971866608 | 0.933000028133392 | 0.924000024795532 | 0.927999973297119 | 0.936999976634979 | 0.935999989509583 | 2.43099999427795 | 2.24900007247925 | 2.06200003623962 | 1.90600001811981 | 1.77600002288818 | 1.59300005435944 | 1.40699994564056 | 1.22899997234344 | 1.22800004482269 | 1.33299994468689 | 1.29499995708466 |
345 | Benin | BEN | Unemployment, male (% of male labor force) (national estimate) | SL.UEM.TOTL.MA.NE.ZS | .. | .. | .. | .. | .. | 0.930000007152557 | .. | .. | .. | .. | .. | .. | .. | 0.930000007152557 | 2.42000007629395 | .. | .. | .. | .. | .. | .. | 1.24000000953674 | .. | .. | .. |
346 | Benin | BEN | Unemployment, total (% of total labor force) (modeled ILO estimate) | SL.UEM.TOTL.ZS | 1.09599995613098 | 1.02300000190735 | 0.935000002384186 | 0.851000010967255 | 0.771000027656555 | 0.689999997615814 | 0.735000014305115 | 0.773999989032745 | 0.824999988079071 | 0.860000014305115 | 0.894999980926514 | 0.941999971866608 | 0.995000004768372 | 1.03999996185303 | 2.65000009536743 | 2.47099995613098 | 2.28699994087219 | 2.13299989700317 | 2.00699996948242 | 1.82799994945526 | 1.64400005340576 | 1.47000002861023 | 1.47000002861023 | 1.58399999141693 | 1.57400000095367 |
347 | Benin | BEN | Unemployment, total (% of total labor force) (national estimate) | SL.UEM.TOTL.NE.ZS | .. | .. | .. | .. | .. | 0.689999997615814 | .. | .. | .. | .. | .. | .. | .. | 1.03999996185303 | 2.65000009536743 | .. | .. | .. | .. | .. | .. | 1.47000002861023 | .. | .. | .. |
348 | Benin | BEN | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS | 0.670000016689301 | 0.660000026226044 | 0.646000027656555 | 0.632000029087067 | 0.617999970912933 | 0.602999985218048 | 0.855000019073486 | 1.10000002384186 | 1.35699999332428 | 1.60300004482269 | 1.85300004482269 | 2.12100005149841 | 2.40499997138977 | 2.68400001525879 | 5.73699998855591 | 5.50899982452393 | 5.27600002288818 | 5.07800006866455 | 4.92000007629395 | 4.69399976730347 | 4.45900011062622 | 4.23699998855591 | 4.26300001144409 | 4.49900007247925 | 4.55999994277954 |
349 | Benin | BEN | Unemployment, youth female (% of female labor force ages 15-24) (national estimate) | SL.UEM.1524.FE.NE.ZS | .. | .. | .. | .. | .. | 0.610000014305115 | .. | .. | .. | .. | .. | .. | .. | 3.10999989509583 | 5.94999980926514 | .. | .. | .. | .. | .. | .. | 4.53999996185303 | .. | .. | .. |
350 | Benin | BEN | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS | 1.73300004005432 | 1.60599994659424 | 1.47000002861023 | 1.33299994468689 | 1.19400000572205 | 1.05200004577637 | 1.11199998855591 | 1.16600000858307 | 1.22399997711182 | 1.27199995517731 | 1.32000005245209 | 1.37300002574921 | 1.42900002002716 | 1.48199999332428 | 5.05800008773804 | 4.75400018692017 | 4.44600009918213 | 4.16300010681152 | 3.90499997138977 | 3.6010000705719 | 3.29299998283386 | 2.9909999370575 | 3.02300000190735 | 3.21199989318848 | 3.12599992752075 |
351 | Benin | BEN | Unemployment, youth male (% of male labor force ages 15-24) (national estimate) | SL.UEM.1524.MA.NE.ZS | .. | .. | .. | .. | .. | 1.07000005245209 | .. | .. | .. | .. | .. | .. | .. | 1.52999997138977 | 5.21000003814697 | .. | .. | .. | .. | .. | .. | 3.16000008583069 | .. | .. | .. |
352 | Benin | BEN | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.ZS | 1.25499999523163 | 1.17200005054474 | 1.08399999141693 | 0.998000025749207 | 0.912000000476837 | 0.827000021934509 | 0.98199999332428 | 1.13199996948242 | 1.29200005531311 | 1.442999958992 | 1.59800004959106 | 1.76800000667572 | 1.95000004768372 | 2.13000011444092 | 5.42799997329712 | 5.16599988937378 | 4.90000009536743 | 4.66400003433228 | 4.46099996566772 | 4.20100021362305 | 3.93400001525879 | 3.67700004577637 | 3.70700001716614 | 3.92199993133545 | 3.9210000038147 |
353 | Benin | BEN | Unemployment, youth total (% of total labor force ages 15-24) (national estimate) | SL.UEM.1524.NE.ZS | .. | .. | .. | .. | .. | 0.819999992847443 | .. | .. | .. | .. | .. | .. | .. | 2.38000011444092 | 5.63000011444092 | .. | .. | .. | .. | .. | .. | 3.91000008583069 | .. | .. | .. |
354 | Benin | BEN | Vulnerable employment, female (% of female employment) (modeled ILO estimate) | SL.EMP.VULN.FE.ZS | 95.4200019836426 | 95.4600009918213 | 95.1599979400635 | 95.0900039672852 | 94.9000015258789 | 94.810001373291 | 94.7700004577637 | 94.810001373291 | 94.73000335693361 | 94.7700023651123 | 94.75000190734869 | 94.8500003814697 | 94.8299961090088 | 94.71999931335449 | 94.7600021362305 | 94.76000022888181 | 94.56999778747561 | 94.290002822876 | 94.1099967956543 | 94.1499996185303 | 93.8099975585938 | 93.5900020599365 | 93.1200027465821 | .. | .. |
355 | Benin | BEN | Vulnerable employment, male (% of male employment) (modeled ILO estimate) | SL.EMP.VULN.MA.ZS | 84.5699958801269 | 84.5999984741211 | 84.25 | 84.05999755859371 | 83.60000038146981 | 83.3999996185303 | 83.1999959945678 | 83.2700033187866 | 83.0800008773804 | 83.0699996948242 | 83.0699968338013 | 83.2200031280517 | 83.0499992370606 | 82.870002746582 | 83.0199985504151 | 83.02000331878659 | 82.69999885559079 | 82.359998703003 | 81.93999767303471 | 82.13000202178961 | 81.5999994277954 | 81.2899971008301 | 80.61999893188472 | .. | .. |
356 | Benin | BEN | Vulnerable employment, total (% of total employment) (modeled ILO estimate) | SL.EMP.VULN.ZS | 89.3799991607666 | 89.4699993133545 | 89.2200012207031 | 89.1399993896484 | 88.8699989318847 | 88.7800025939941 | 88.69999885559079 | 88.790002822876 | 88.689998626709 | 88.75 | 88.7900009155273 | 88.9400024414063 | 88.87999725341801 | 88.7700004577637 | 88.76999664306639 | 88.7600021362305 | 88.5100021362305 | 88.19999980926511 | 87.9099960327148 | 88.0300016403198 | 87.5799999237061 | 87.3300018310547 | 86.7699985504151 | .. | .. |
357 | Benin | BEN | Wage and salaried workers, female (% of female employment) (modeled ILO estimate) | SL.EMP.WORK.FE.ZS | 4.03999996185303 | 3.99000000953674 | 4.23999977111816 | 4.30000019073486 | 4.48000001907349 | 4.55999994277954 | 4.6100001335144 | 4.55999994277954 | 4.6399998664856 | 4.59999990463257 | 4.59999990463257 | 4.48999977111816 | 4.53999996185303 | 4.63000011444092 | 4.59000015258789 | 4.57999992370605 | 4.76000022888184 | 5.01000022888184 | 5.21000003814697 | 5.15000009536743 | 5.48000001907349 | 5.67999982833862 | 6.15000009536743 | .. | .. |
358 | Benin | BEN | Wage and salaried workers, male (% of male employment) (modeled ILO estimate) | SL.EMP.WORK.MA.ZS | 13.9300003051758 | 13.8900003433228 | 14.0799999237061 | 14.2600002288818 | 14.6999998092651 | 14.8800001144409 | 15.1000003814697 | 15 | 15.1700000762939 | 15.1599998474121 | 15.1400003433228 | 14.9899997711182 | 15.1700000762939 | 15.3199996948242 | 15.1499996185303 | 15.1300001144409 | 15.4399995803833 | 15.7600002288818 | 16.2000007629395 | 15.9399995803833 | 16.4899997711182 | 16.7900009155273 | 17.4699993133545 | .. | .. |
359 | Benin | BEN | Wage and salaried workers, total (% of total employment) (modeled ILO estimate) | SL.EMP.WORK.ZS | 9.53999996185303 | 9.4399995803833 | 9.60999965667725 | 9.67000007629395 | 9.9399995803833 | 10.0100002288818 | 10.1099996566772 | 10.0100002288818 | 10.0900001525879 | 10.039999961853 | 9.98999977111816 | 9.81999969482422 | 9.90999984741211 | 10 | 9.97999954223633 | 9.97000026702881 | 10.2200002670288 | 10.4899997711182 | 10.8100004196167 | 10.6499996185303 | 11.0900001525879 | 11.3299999237061 | 11.9099998474121 | .. | .. |
360 | Benin | BEN | Women Business and the Law Index Score (scale 1-100) | SG.LAW.INDX | 40 | 49.375 | 49.375 | 49.375 | 49.375 | 49.375 | 46.875 | 46.875 | 65.625 | 65.625 | 71.875 | 71.875 | 71.875 | 71.875 | 71.875 | 74.375 | 74.375 | 74.375 | 74.375 | 74.375 | 74.375 | 74.375 | 74.375 | 77.5 | 80.625 |
361 | Benin | BEN | Women making their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women age 15-49) | SG.DMK.SRCR.FN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 41.1 | .. | .. | .. | .. | .. | 38.2 | .. | .. | .. | .. | .. | 35.7 | .. | .. | .. |
362 | Benin | BEN | Women participating in the three decisions (own health care, major household purchases, and visiting family) (% of women age 15-49) | SG.DMK.ALLD.FN.ZS | .. | .. | .. | .. | 17.2 | .. | .. | .. | .. | 35.6 | .. | .. | .. | .. | .. | 48.3 | .. | .. | .. | .. | .. | 36.3 | .. | .. | .. |
363 | Benin | BEN | Women who believe a husband is justified in beating his wife (any of five reasons) (%) | SG.VAW.REAS.ZS | .. | .. | .. | .. | 60.4 | .. | .. | .. | .. | 46.5 | .. | .. | .. | .. | .. | 16.2 | .. | 36 | .. | .. | .. | 31.8 | .. | .. | .. |
364 | Benin | BEN | Women who believe a husband is justified in beating his wife when she argues with him (%) | SG.VAW.ARGU.ZS | .. | .. | .. | .. | 39.4 | .. | .. | .. | .. | 34 | .. | .. | .. | .. | .. | 10.6 | .. | .. | .. | .. | .. | 20.8 | .. | .. | .. |
365 | Benin | BEN | Women who believe a husband is justified in beating his wife when she burns the food (%) | SG.VAW.BURN.ZS | .. | .. | .. | .. | 29.2 | .. | .. | .. | .. | 19 | .. | .. | .. | .. | .. | 6 | .. | .. | .. | .. | .. | 13.9 | .. | .. | .. |
366 | Benin | BEN | Women who believe a husband is justified in beating his wife when she goes out without telling him (%) | SG.VAW.GOES.ZS | .. | .. | .. | .. | 44 | .. | .. | .. | .. | 36.7 | .. | .. | .. | .. | .. | 7.7 | .. | .. | .. | .. | .. | 21.2 | .. | .. | .. |
367 | Benin | BEN | Women who believe a husband is justified in beating his wife when she neglects the children (%) | SG.VAW.NEGL.ZS | .. | .. | .. | .. | 51 | .. | .. | .. | .. | 36.4 | .. | .. | .. | .. | .. | 8.8 | .. | .. | .. | .. | .. | 22.6 | .. | .. | .. |
368 | Benin | BEN | Women who believe a husband is justified in beating his wife when she refuses sex with him (%) | SG.VAW.REFU.ZS | .. | .. | .. | .. | 17 | .. | .. | .. | .. | 17.3 | .. | .. | .. | .. | .. | 6.5 | .. | .. | .. | .. | .. | 12.8 | .. | .. | .. |
369 | Ethiopia | ETH | Adequacy of social insurance programs (% of total welfare of beneficiary households) | per_si_allsi.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.9140150847623 | .. | .. | 12.6997838042388 | .. | .. | .. |
370 | Ethiopia | ETH | Adequacy of social protection and labor programs (% of total welfare of beneficiary households) | per_allsp.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.6366160754953 | .. | .. | 8.25348841187211 | .. | .. | .. |
371 | Ethiopia | ETH | Adequacy of social safety net programs (% of total welfare of beneficiary households) | per_sa_allsa.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.52217128949911 | .. | .. | 7.4024416493194 | .. | .. | .. |
372 | Ethiopia | ETH | Adequacy of unemployment benefits and ALMP (% of total welfare of beneficiary households) | per_lm_alllm.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
373 | Ethiopia | ETH | Adjusted net national income (annual % growth) | NY.ADJ.NNTY.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.21881544040319 | 12.144857471835536 | 14.476072948698885 | 11.028752833311643 | 14.85168110168658 | 10.497847399841632 | 19.469782849015445 | 26.336156248078055 | 21.88580222839998 | .. |
374 | Ethiopia | ETH | Adjusted net national income (constant 2015 US$) | NY.ADJ.NNTY.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 31520663398.79651 | 34741701817.110245 | 38961031986.08838 | 44601059397.960434 | 49520000000 | 56874552481.55519 | 62845156210.4117 | 75080971655.7034 | 94854413663.52464 | 115614063042.83205 | .. |
375 | Ethiopia | ETH | Adjusted net national income (current US$) | NY.ADJ.NNTY.CD | 5837000000 | 4952000000 | 5753000000 | 6180000000 | 6208000000 | 5369000000 | 4718000000 | 6420000000 | 8480000000 | 10960000000 | 13670000000 | 19560000000 | 23930000000 | 22240000000 | 23200000000 | 31910000000 | 35390000000 | 42510000000 | 49520000000 | 58230000000 | 65210000000 | 70980000000 | 81900000000 | 92830000000 | .. |
376 | Ethiopia | ETH | Adjusted net national income per capita (annual % growth) | NY.ADJ.NNTY.PC.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.143744719775654 | 9.018899493590823 | 11.315285445614776 | 8.010461281129167 | 11.783150677756836 | 7.593678436143293 | 16.380359064162604 | 23.118744272176997 | 18.82724247671399 | .. |
377 | Ethiopia | ETH | Adjusted net national income per capita (constant 2015 US$) | NY.ADJ.NNTY.PC.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 349.68591719749884 | 374.6665864430943 | 408.4573893104645 | 454.6755088346494 | 491.09711442462606 | 548.9638273913956 | 590.6503751742431 | 687.4010274416077 | 846.3195131001501 | 1005.6581399592603 | .. |
378 | Ethiopia | ETH | Adjusted net national income per capita (current US$) | NY.ADJ.NNTY.PC.CD | 96.16550074440534 | 79.22220940247321 | 89.41142447055009 | 93.31850243614896 | 91.08058457420604 | 76.54462534549512 | 65.37289757997098 | 86.4768661990594 | 111.07282067725343 | 139.6370367109719 | 169.44668517474014 | 235.90072274867856 | 280.7567592541763 | 253.76551395583672 | 257.3776184955462 | 344.12852992454776 | 371.01961295221395 | 433.3586722257277 | 491.09711442462606 | 562.0468605773701 | 612.8763660982246 | 649.8547348527678 | 730.7363510650866 | 807.4730934577778 | .. |
379 | Ethiopia | ETH | Adjusted net savings, excluding particulate emission damage (% of GNI) | NY.ADJ.SVNX.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.3479905 | 7.8459832 | 5.0236968 | 10.278336 | 9.0084576 | 12.04212 | 13.356527 | 20.230523 | 17.433329 | 16.472534 | .. |
380 | Ethiopia | ETH | Adjusted net savings, excluding particulate emission damage (current US$) | NY.ADJ.SVNX.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2662000000 | 3391000000 | 2388000000 | 5700000000 | 5795000000 | 8918000000 | 10860000000 | 16970000000 | 16620000000 | 17630000000 | .. |
381 | Ethiopia | ETH | Adjusted net savings, including particulate emission damage (% of GNI) | NY.ADJ.SVNG.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.9533322 | 6.5334668 | 3.8164815 | 9.1289491 | 7.9434845 | 11.046077 | 12.409725 | 19.320504 | 16.579218 | 15.651063 | .. |
382 | Ethiopia | ETH | Adjusted net savings, including particulate emission damage (current US$) | NY.ADJ.SVNG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2217000000 | 2823000000 | 1814000000 | 5063000000 | 5110000000 | 8180000000 | 10090000000 | 16210000000 | 15800000000 | 16750000000 | .. |
383 | Ethiopia | ETH | Adjusted savings: carbon dioxide damage (% of GNI) | NY.ADJ.DCO2.GN.ZS | 0.5969287 | 0.71571975 | 0.74090315 | 0.81696951 | 1.0475209 | 1.1831063 | 1.2421817 | 1.1677439 | 0.9500201 | 0.87214821 | 0.79905792 | 0.68356347 | 0.59114391 | 0.62282341 | 0.70443545 | 0.61212672 | 0.70035756 | 0.74963786 | 0.69821002 | 0.72368141 | 0.71165269 | 0.76032133 | 0.76853559 | 0.76906447 | .. |
384 | Ethiopia | ETH | Adjusted savings: carbon dioxide damage (current US$) | NY.ADJ.DCO2.CD | 50692772 | 55481244 | 56666815 | 66846597 | 85687941 | 92249255 | 106300000 | 117600000 | 117500000 | 132900000 | 157600000 | 185200000 | 191500000 | 185800000 | 224600000 | 264500000 | 333000000 | 415700000 | 449100000 | 535900000 | 578500000 | 637800000 | 732600000 | 822900000 | .. |
385 | Ethiopia | ETH | Adjusted savings: consumption of fixed capital (% of GNI) | NY.ADJ.DKAP.GN.ZS | 3.8956512 | 4.6515662 | 5.0598519 | 5.884303 | 5.8855951 | 7.798011 | 8.4689733 | 8.255604 | 8.0943806 | 9.2747794 | 8.8485951 | 9.0713847 | 9.7164559 | 9.6364209 | 9.951723 | 11.35723 | 11.693651 | 9.9950851 | 10.796508 | 10.123111 | 9.8684996 | 9.4723878 | 8.5826304 | 8.0846719 | .. |
386 | Ethiopia | ETH | Adjusted savings: consumption of fixed capital (current US$) | NY.ADJ.DKAP.CD | 330800000 | 360600000 | 387000000 | 481500000 | 481400000 | 608000000 | 724700000 | 831100000 | 1001000000 | 1414000000 | 1745000000 | 2457000000 | 3148000000 | 2874000000 | 3173000000 | 4908000000 | 5559000000 | 5543000000 | 6945000000 | 7497000000 | 8022000000 | 7947000000 | 8181000000 | 8651000000 | .. |
387 | Ethiopia | ETH | Adjusted savings: education expenditure (% of GNI) | NY.ADJ.AEDU.GN.ZS | 2.8 | 3.4267446 | 2.3 | 2.43 | 2.38 | 2.33 | 2.645 | 2.96 | 3.275 | 3.59 | 3.69 | 3.82 | 3.14 | 2.96 | 3.66 | 3.64 | 2.88 | 2.8471708 | 3.0744553 | 3.0744553 | 3.0744553 | 3.0744553 | 3.0744553 | 3.0744553 | .. |
388 | Ethiopia | ETH | Adjusted savings: education expenditure (current US$) | NY.ADJ.AEDU.CD | 237800000 | 265600000 | 175900000 | 198800000 | 194700000 | 181700000 | 226300000 | 298000000 | 405000000 | 547200000 | 727700000 | 1035000000 | 1017000000 | 882800000 | 1167000000 | 1573000000 | 1369000000 | 1579000000 | 1978000000 | 2277000000 | 2499000000 | 2579000000 | 2931000000 | 3290000000 | .. |
389 | Ethiopia | ETH | Adjusted savings: energy depletion (% of GNI) | NY.ADJ.DNGY.GN.ZS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5.521e-05 | 0.00021817 | 0.00015073 | 0 | 0 | 0 | 0 | 1.917e-06 | 2.332e-06 | 2.841e-06 | 1.714e-06 | 1.291e-06 | .. |
390 | Ethiopia | ETH | Adjusted savings: energy depletion (current US$) | NY.ADJ.DNGY.CD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 17885.298 | 65069.333 | 48057.939 | 0 | 0 | 0 | 0 | 1419.5364 | 1895.2451 | 2383.7716 | 1634.2711 | 1381.8877 | .. |
391 | Ethiopia | ETH | Adjusted savings: gross savings (% of GNI) | NY.ADJ.ICTR.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 32.629238 | 30.981064 | 28.398421 | 31.53698 | 29.64263 | 31.054655 | 30.772769 | 33.312217 | 29.210011 | 27.391753 | .. |
392 | Ethiopia | ETH | Adjusted savings: mineral depletion (% of GNI) | NY.ADJ.DMIN.GN.ZS | 0.06047211 | 0.04514953 | 0.05871864 | 0.09530946 | 0.08900567 | 0.17170958 | 0.057315 | 0.02989115 | 0.0497452 | 0.10350595 | 0.09810228 | 0.07143858 | 0.08353351 | 0.20727509 | 0.53837337 | 0.42210623 | 0.26448335 | 0.17635782 | 0.08642505 | 0.09158846 | 0.08647975 | 0.02896201 | 0 | 0.03224729 | .. |
393 | Ethiopia | ETH | Adjusted savings: mineral depletion (current US$) | NY.ADJ.DMIN.CD | 5135452.4 | 3499906.3 | 4491003.3 | 7798471 | 7280725.6 | 13388552 | 4904777.4 | 3009338 | 6151170.1 | 15776855 | 19347541 | 19350460 | 27061298 | 61820987 | 171700000 | 182400000 | 125700000 | 97807047 | 55594497 | 67824860 | 70295234 | 24296820 | 0 | 34504600 | .. |
394 | Ethiopia | ETH | Adjusted savings: natural resources depletion (% of GNI) | NY.ADJ.DRES.GN.ZS | 27.37169711 | 31.47054453 | 19.717078639999997 | 18.58681746 | 18.22300267 | 23.34389858 | 36.396100000000004 | 27.97308615 | 23.3243822 | 18.83521395 | 21.85547528 | 18.72274658 | 16.41201872 | 15.78891726 | 17.2850891 | 14.805724230000001 | 13.860715350000001 | 13.36109182 | 12.21391005 | 11.240198377 | 9.910544582 | 5.923439750999999 | 5.4999709139999995 | 5.155870881 | .. |
395 | Ethiopia | ETH | Adjusted savings: net forest depletion (% of GNI) | NY.ADJ.DFOR.GN.ZS | 27.311225 | 31.425395 | 19.65836 | 18.491508 | 18.133997 | 23.172189 | 36.338785 | 27.943195 | 23.274637 | 18.731708 | 21.757373 | 18.651308 | 16.32843 | 15.581424 | 16.746565 | 14.383618 | 13.596232 | 13.184734 | 12.127485 | 11.148608 | 9.8240625 | 5.8944749 | 5.4999692 | 5.1236223 | .. |
396 | Ethiopia | ETH | Adjusted savings: net forest depletion (current US$) | NY.ADJ.DFOR.CD | 2319000000 | 2436000000 | 1504000000 | 1513000000 | 1483000000 | 1807000000 | 3110000000 | 2813000000 | 2878000000 | 2855000000 | 4291000000 | 5052000000 | 5290000000 | 4647000000 | 5339000000 | 6216000000 | 6464000000 | 7312000000 | 7801000000 | 8256000000 | 7986000000 | 4945000000 | 5243000000 | 5482000000 | .. |
397 | Ethiopia | ETH | Adjusted savings: net national savings (% of GNI) | NY.ADJ.NNAT.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 22.677515 | 19.623834 | 16.70477 | 21.541895 | 18.846123 | 20.931545 | 20.904269 | 23.839829 | 20.62738 | 19.323014 | .. |
398 | Ethiopia | ETH | Adjusted savings: net national savings (current US$) | NY.ADJ.NNAT.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7230000000 | 8480000000 | 7942000000 | 11950000000 | 12120000000 | 15500000000 | 16990000000 | 20000000000 | 19660000000 | 20680000000 | .. |
399 | Ethiopia | ETH | Adjusted savings: particulate emission damage (% of GNI) | NY.ADJ.DPEM.GN.ZS | 3.345853 | 3.4366005 | 3.2116814 | 2.9817783 | 2.7539495 | 2.6677037 | 2.6670107 | 2.316795 | 2.1262439 | 1.946719 | 1.8129426 | 1.7284152 | 1.645612 | 1.4972896 | 1.3946583 | 1.3125164 | 1.2072153 | 1.1493866 | 1.064973 | 0.99604273 | 0.94680229 | 0.91001936 | 0.85411115 | 0.82147072 | .. |
400 | Ethiopia | ETH | Adjusted savings: particulate emission damage (current US$) | NY.ADJ.DPEM.CD | 284100000 | 266400000 | 245600000 | 244000000 | 225300000 | 208000000 | 228200000 | 233200000 | 262900000 | 296700000 | 357500000 | 468200000 | 533100000 | 446600000 | 444700000 | 567200000 | 573900000 | 637400000 | 685100000 | 737600000 | 769600000 | 763400000 | 814200000 | 879000000 | .. |
401 | Ethiopia | ETH | Agriculture, forestry, and fishing, value added (annual % growth) | NV.AGR.TOTL.KD.ZG | 2.0021471480415727 | -9.640327399168527 | 3.397766244090363 | 3.0531627146003615 | 9.624306668984019 | -1.8755473297294856 | -10.484884878793139 | 16.944821393816255 | 13.542938005045642 | 10.908781446100122 | 9.44831688479593 | 7.5014730247632 | 6.360960330294205 | 5.130302621278673 | 9.014984816622444 | 4.9220987229010404 | 7.098457639280767 | 5.446729289622283 | 6.377789826996107 | 4.199835314370986 | 6.677348265589856 | 3.5068347770810533 | 3.834364931112134 | 4.253859861622189 | 5.543217093876265 |
402 | Ethiopia | ETH | Agriculture, forestry, and fishing, value added (constant 2015 US$) | NV.AGR.TOTL.KD | 9435421614.991114 | 8525816079.814056 | 8815503380.607206 | 9084655042.92824 | 9958990104.078976 | 9772204531.1139 | 8747600135.9064 | 10229865355.18097 | 11615289678.23277 | 12882376243.56261 | 14099543973.346077 | 15157217461.12126 | 16121362050.999607 | 16948436710.887865 | 18476335707.02927 | 19385759190.903866 | 20761849095.123154 | 21892690810.854404 | 23288960618.24479 | 24267058610.639786 | 25887454627.887016 | 26795284889.678837 | 27822713896.68027 | 29006253155.54513 | 30614132738.756332 |
403 | Ethiopia | ETH | Agriculture, forestry, and fishing, value added per worker (constant 2015 US$) | NV.AGR.EMPL.KD | 499.74533517746397 | 435.4939221224641 | 436.1550638651492 | 431.0014636594273 | 455.33596194649823 | 428.9010049306933 | 367.80001985882666 | 415.69090139825323 | 454.4355655056186 | 493.34523078307467 | 528.8961290719692 | 556.9527651703305 | 580.2991017161797 | 597.8921009652 | 637.5237685837068 | 653.3773626548143 | 684.9924971781484 | 705.9698262241192 | 734.4591300750631 | 749.2433771369044 | 782.2556982392997 | 791.1345979261696 | 803.9777799281034 | .. | .. |
404 | Ethiopia | ETH | Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%) | SI.SPR.PC40.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.92 | .. | .. | .. | .. | .. | .. |
405 | Ethiopia | ETH | Annualized average growth rate in per capita real survey mean consumption or income, total population (%) | SI.SPR.PCAP.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.14 | .. | .. | .. | .. | .. | .. |
406 | Ethiopia | ETH | Average working hours of children, study and work, ages 7-14 (hours per week) | SL.TLF.0714.SW.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 18.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
407 | Ethiopia | ETH | Average working hours of children, study and work, female, ages 7-14 (hours per week) | SL.TLF.0714.SW.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 15.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
408 | Ethiopia | ETH | Average working hours of children, study and work, male, ages 7-14 (hours per week) | SL.TLF.0714.SW.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
409 | Ethiopia | ETH | Average working hours of children, working only, ages 7-14 (hours per week) | SL.TLF.0714.WK.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
410 | Ethiopia | ETH | Average working hours of children, working only, female, ages 7-14 (hours per week) | SL.TLF.0714.WK.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 24 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
411 | Ethiopia | ETH | Average working hours of children, working only, male, ages 7-14 (hours per week) | SL.TLF.0714.WK.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 31.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
412 | Ethiopia | ETH | Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits) | per_si_allsi.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.82762306310195 | .. | .. | 0.828874344167305 | .. | .. | .. |
413 | Ethiopia | ETH | Benefit incidence of social protection and labor programs to poorest quintile (% of total SPL benefits) | per_allsp.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.72177202320577 | .. | .. | 13.8368662486227 | .. | .. | .. |
414 | Ethiopia | ETH | Benefit incidence of social safety net programs to poorest quintile (% of total safety net benefits) | per_sa_allsa.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.66871908066 | .. | .. | 17.2809582588435 | .. | .. | .. |
415 | Ethiopia | ETH | Benefit incidence of unemployment benefits and ALMP to poorest quintile (% of total U/ALMP benefits) | per_lm_alllm.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
416 | Ethiopia | ETH | Child employment in agriculture (% of economically active children ages 7-14) | SL.AGR.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 94.61 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
417 | Ethiopia | ETH | Child employment in agriculture, female (% of female economically active children ages 7-14) | SL.AGR.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 91.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
418 | Ethiopia | ETH | Child employment in agriculture, male (% of male economically active children ages 7-14) | SL.AGR.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 96.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
419 | Ethiopia | ETH | Child employment in manufacturing (% of economically active children ages 7-14) | SL.MNF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 1.48 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
420 | Ethiopia | ETH | Child employment in manufacturing, female (% of female economically active children ages 7-14) | SL.MNF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 2.79 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
421 | Ethiopia | ETH | Child employment in manufacturing, male (% of male economically active children ages 7-14) | SL.MNF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 0.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
422 | Ethiopia | ETH | Child employment in services (% of economically active children ages 7-14) | SL.SRV.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 3.72 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
423 | Ethiopia | ETH | Child employment in services, female (% of female economically active children ages 7-14) | SL.SRV.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 5.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
424 | Ethiopia | ETH | Child employment in services, male (% of male economically active children ages 7-14) | SL.SRV.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 2.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
425 | Ethiopia | ETH | Children in employment, female (% of female children ages 7-14) | SL.TLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 47.1 | .. | .. | .. | .. | .. | 19.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
426 | Ethiopia | ETH | Children in employment, male (% of male children ages 7-14) | SL.TLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 64.3 | .. | .. | .. | .. | .. | 32.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
427 | Ethiopia | ETH | Children in employment, self-employed (% of children in employment, ages 7-14) | SL.SLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
428 | Ethiopia | ETH | Children in employment, self-employed, female (% of female children in employment, ages 7-14) | SL.SLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
429 | Ethiopia | ETH | Children in employment, self-employed, male (% of male children in employment, ages 7-14) | SL.SLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
430 | Ethiopia | ETH | Children in employment, study and work (% of children in employment, ages 7-14) | SL.TLF.0714.SW.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 30.6 | .. | .. | .. | .. | .. | 64.8778981972078 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
431 | Ethiopia | ETH | Children in employment, study and work, female (% of female children in employment, ages 7-14) | SL.TLF.0714.SW.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 65.4493508111309 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
432 | Ethiopia | ETH | Children in employment, study and work, male (% of male children in employment, ages 7-14) | SL.TLF.0714.SW.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 64.5496428302855 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
433 | Ethiopia | ETH | Children in employment, total (% of children ages 7-14) | SL.TLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 56 | .. | .. | .. | .. | .. | 26.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
434 | Ethiopia | ETH | Children in employment, unpaid family workers (% of children in employment, ages 7-14) | SL.FAM.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 90.66 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
435 | Ethiopia | ETH | Children in employment, unpaid family workers, female (% of female children in employment, ages 7-14) | SL.FAM.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 90.37 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
436 | Ethiopia | ETH | Children in employment, unpaid family workers, male (% of male children in employment, ages 7-14) | SL.FAM.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 90.82 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
437 | Ethiopia | ETH | Children in employment, wage workers (% of children in employment, ages 7-14) | SL.WAG.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.28 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
438 | Ethiopia | ETH | Children in employment, wage workers, female (% of female children in employment, ages 7-14) | SL.WAG.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.32 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
439 | Ethiopia | ETH | Children in employment, wage workers, male (% of male children in employment, ages 7-14) | SL.WAG.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.25 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
440 | Ethiopia | ETH | Children in employment, work only (% of children in employment, ages 7-14) | SL.TLF.0714.WK.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 69.4 | .. | .. | .. | .. | .. | 35.1221018027922 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
441 | Ethiopia | ETH | Children in employment, work only, female (% of female children in employment, ages 7-14) | SL.TLF.0714.WK.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34.5506491888691 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
442 | Ethiopia | ETH | Children in employment, work only, male (% of male children in employment, ages 7-14) | SL.TLF.0714.WK.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 35.4503571697145 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
443 | Ethiopia | ETH | Community health workers (per 1,000 people) | SH.MED.CMHW.P3 | .. | .. | .. | .. | .. | .. | 0.185 | 0.211 | .. | .. | 0.218 | 0.296 | 0.363 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
444 | Ethiopia | ETH | Contributing family workers, female (% of female employment) (modeled ILO estimate) | SL.FAM.WORK.FE.ZS | 58.1100006103516 | 57.5499992370605 | 57.1500015258789 | 59.6699981689453 | 60.1399993896484 | 60.9500007629395 | 62.6500015258789 | 63.9700012207031 | 65.379997253418 | 64.8399963378906 | 63.7000007629395 | 63.9599990844727 | 63.5499992370605 | 62.4000015258789 | 61.1800003051758 | 60.1100006103516 | 59.0699996948242 | 57.4799995422363 | 55.6800003051758 | 53.5800018310547 | 52.0499992370605 | 50.1699981689453 | 49.1500015258789 | .. | .. |
445 | Ethiopia | ETH | Contributing family workers, male (% of male employment) (modeled ILO estimate) | SL.FAM.WORK.MA.ZS | 25.5100002288818 | 24.4500007629395 | 23.3999996185303 | 23.8600006103516 | 23.7099990844727 | 23.5400009155273 | 23.5499992370605 | 23.6000003814697 | 23.7900009155273 | 23.6200008392334 | 23.3700008392334 | 23.8700008392334 | 24.0699996948242 | 24.0100002288818 | 23.9699993133545 | 23.9899997711182 | 24.0100002288818 | 23.2900009155273 | 22.6200008392334 | 21.7800006866455 | 21.2900009155273 | 20.6100006103516 | 20.2999992370605 | .. | .. |
446 | Ethiopia | ETH | Contributing family workers, total (% of total employment) (modeled ILO estimate) | SL.FAM.WORK.ZS | 39.7599983215332 | 38.9799995422363 | 38.25 | 39.7299995422363 | 39.9599990844727 | 40.3300018310547 | 41.189998626709 | 41.9000015258789 | 42.75 | 42.4300003051758 | 41.7900009155273 | 42.189998626709 | 42.0999984741211 | 41.5400009155273 | 40.9700012207031 | 40.4900016784668 | 40.0099983215332 | 38.9300003051758 | 37.7900009155273 | 36.4000015258789 | 35.4700012207031 | 34.2700004577637 | 33.6500015258789 | .. | .. |
447 | Ethiopia | ETH | Coverage of social insurance programs (% of population) | per_si_allsi.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.36834901780239 | .. | .. | 1.2535170900859 | .. | .. | .. |
448 | Ethiopia | ETH | Coverage of social insurance programs in 2nd quintile (% of population) | per_si_allsi.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.869569727834499 | .. | .. | 0.303292552014989 | .. | .. | .. |
449 | Ethiopia | ETH | Coverage of social insurance programs in 3rd quintile (% of population) | per_si_allsi.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.79603630508859 | .. | .. | 1.04934856149933 | .. | .. | .. |
450 | Ethiopia | ETH | Coverage of social insurance programs in 4th quintile (% of population) | per_si_allsi.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.04401028589865 | .. | .. | 1.43406157297065 | .. | .. | .. |
451 | Ethiopia | ETH | Coverage of social insurance programs in poorest quintile (% of population) | per_si_allsi.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.338503918404981 | .. | .. | 0.0896354963151229 | .. | .. | .. |
452 | Ethiopia | ETH | Coverage of social insurance programs in richest quintile (% of population) | per_si_allsi.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.78840386945914 | .. | .. | 3.38763381477739 | .. | .. | .. |
453 | Ethiopia | ETH | Coverage of social protection and labor programs (% of population) | per_allsp.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | 0.514473589852514 | .. | .. | .. | .. | .. | 13.2479485078869 | .. | .. | .. | .. | 23.1508611348385 | .. | .. | 21.6635577360575 | .. | .. | .. |
454 | Ethiopia | ETH | Coverage of social safety net programs (% of population) | per_sa_allsa.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | 0.514473589852514 | .. | .. | .. | .. | .. | 13.2479485078869 | .. | .. | .. | .. | 21.1034818238013 | .. | .. | 20.7062597970922 | .. | .. | .. |
455 | Ethiopia | ETH | Coverage of social safety net programs in 2nd quintile (% of population) | per_sa_allsa.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | 0.700932505364392 | .. | .. | .. | .. | .. | 16.2680164050415 | .. | .. | .. | .. | 25.7353160066646 | .. | .. | 24.2910353456234 | .. | .. | .. |
456 | Ethiopia | ETH | Coverage of social safety net programs in 3rd quintile (% of population) | per_sa_allsa.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | 0.66717731695518 | .. | .. | .. | .. | .. | 12.6373211860833 | .. | .. | .. | .. | 25.1533063030421 | .. | .. | 23.1515541114544 | .. | .. | .. |
457 | Ethiopia | ETH | Coverage of social safety net programs in 4th quintile (% of population) | per_sa_allsa.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | 0.229809464791454 | .. | .. | .. | .. | .. | 12.9496824451568 | .. | .. | .. | .. | 20.7183505019502 | .. | .. | 13.3787413285914 | .. | .. | .. |
458 | Ethiopia | ETH | Coverage of social safety net programs in poorest quintile (% of population) | per_sa_allsa.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | 0.595208317551733 | .. | .. | .. | .. | .. | 16.2103107940177 | .. | .. | .. | .. | 21.2264095736936 | .. | .. | 30.0139095711919 | .. | .. | .. |
459 | Ethiopia | ETH | Coverage of social safety net programs in richest quintile (% of population) | per_sa_allsa.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | 0.379344019794808 | .. | .. | .. | .. | .. | 8.18105285008741 | .. | .. | .. | .. | 12.6926155749894 | .. | .. | 12.7142196803755 | .. | .. | .. |
460 | Ethiopia | ETH | Coverage of unemployment benefits and ALMP (% of population) | per_lm_alllm.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
461 | Ethiopia | ETH | Coverage of unemployment benefits and ALMP in 2nd quintile (% of population) | per_lm_alllm.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
462 | Ethiopia | ETH | Coverage of unemployment benefits and ALMP in 3rd quintile (% of population) | per_lm_alllm.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
463 | Ethiopia | ETH | Coverage of unemployment benefits and ALMP in 4th quintile (% of population) | per_lm_alllm.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
464 | Ethiopia | ETH | Coverage of unemployment benefits and ALMP in poorest quintile (% of population) | per_lm_alllm.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
465 | Ethiopia | ETH | Coverage of unemployment benefits and ALMP in richest quintile (% of population) | per_lm_alllm.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
466 | Ethiopia | ETH | Current health expenditure (% of GDP) | SH.XPD.CHEX.GD.ZS | .. | .. | .. | 4.3650465 | 4.72316694 | 4.7126298 | 4.89970922 | 4.31281853 | 4.10098124 | 4.45757294 | 5.00128365 | 4.28063917 | 4.64983416 | 5.46637249 | 4.46897888 | 4.53959608 | 4.07506514 | 4.03363609 | 3.82317114 | 3.60033059 | 3.45336151 | 3.30818701 | 3.23808599 | .. | .. |
467 | Ethiopia | ETH | Current health expenditure per capita (current US$) | SH.XPD.CHEX.PC.CD | .. | .. | .. | 5.38449526 | 5.61692476 | 5.25928497 | 5.84133863 | 5.88065052 | 6.65360308 | 8.66179371 | 11.98231506 | 13.45180225 | 15.63803864 | 16.7058506 | 15.11117077 | 20.66479492 | 19.88365173 | 22.27192688 | 23.91623878 | 25.07559586 | 24.92481232 | 24.29408836 | 26.74220467 | .. | .. |
468 | Ethiopia | ETH | Current health expenditure per capita, PPP (current international $) | SH.XPD.CHEX.PP.CD | .. | .. | .. | 21.06814003 | 24.52791595 | 24.52162361 | 24.6919899 | 24.66906929 | 26.2877903 | 31.72366333 | 39.62515259 | 37.26122284 | 43.13404846 | 56.22169876 | 50.7133255 | 55.09231567 | 52.30632782 | 61.05818176 | 63.36304855 | 67.64360046 | 69.81202698 | 71.2833786 | 75.11408997 | .. | .. |
469 | Ethiopia | ETH | Domestic general government health expenditure (% of current health expenditure) | SH.XPD.GHED.CH.ZS | .. | .. | .. | 41.22624969 | 42.6709938 | 44.16249084 | 46.45885086 | 30.72782516 | 42.14151382 | 25.1286335 | 26.65451813 | 12.01339912 | 19.50625038 | 17.2685585 | 8.52938938 | 23.49618912 | 26.98538589 | 17.72079086 | 25.25154305 | 24.99847794 | 24.93995667 | 23.30263901 | 22.70311928 | .. | .. |
470 | Ethiopia | ETH | Domestic general government health expenditure (% of GDP) | SH.XPD.GHED.GD.ZS | .. | .. | .. | 1.79954505 | 2.01542234 | 2.08121467 | 2.27634859 | 1.32523537 | 1.72821558 | 1.1201272 | 1.33306789 | 0.51425028 | 0.90700835 | 0.94396371 | 0.38117662 | 1.06663215 | 1.0996722 | 0.71479219 | 0.96540976 | 0.90002781 | 0.86126679 | 0.77089483 | 0.73514652 | .. | .. |
471 | Ethiopia | ETH | Domestic general government health expenditure (% of general government expenditure) | SH.XPD.GHED.GE.ZS | .. | .. | .. | 7.02978754 | 8.98226833 | 8.36865616 | 8.41779137 | 5.72478628 | 7.55014706 | 5.07603979 | 6.49598408 | 2.74178743 | 5.30020761 | 5.1071167 | 2.091151 | 6.40685654 | 6.19330263 | 4.08834219 | 5.57211685 | 5.02445269 | 4.7883606 | 4.7883606 | 4.7883606 | .. | .. |
472 | Ethiopia | ETH | Domestic general government health expenditure per capita (current US$) | SH.XPD.GHED.PC.CD | .. | .. | .. | 2.21982536 | 2.39679758 | 2.32263118 | 2.71381866 | 1.8069961 | 2.80392906 | 2.17659026 | 3.19382814 | 1.61601861 | 3.05039505 | 2.88485937 | 1.2888907 | 4.85543904 | 5.36567992 | 3.94676136 | 6.03921965 | 6.26851668 | 6.21623727 | 5.66116337 | 6.07131503 | .. | .. |
473 | Ethiopia | ETH | Domestic general government health expenditure per capita, PPP (current international $) | SH.XPD.GHED.PP.CD | .. | .. | .. | 8.68560354 | 10.46630487 | 10.82935928 | 11.47161381 | 7.580268 | 11.07807272 | 7.97172298 | 10.56189282 | 4.47633929 | 8.41383633 | 9.70867617 | 4.32553701 | 12.94459469 | 14.1150644 | 10.81999178 | 16.00014813 | 16.90986889 | 17.41108924 | 16.61090694 | 17.05324168 | .. | .. |
474 | Ethiopia | ETH | Domestic private health expenditure (% of current health expenditure) | SH.XPD.PVTD.CH.ZS | .. | .. | .. | 42.51675034 | 40.25794983 | 43.13770676 | 39.3457222 | 39.62668991 | 35.61906815 | 42.51520157 | 39.9972496 | 41.2253952 | 46.90293503 | 48.2890625 | 53.94318771 | 48.55955124 | 49.74310303 | 58.84427261 | 56.48738098 | 54.76727295 | 39.70265961 | 40.59890366 | 43.19190979 | .. | .. |
475 | Ethiopia | ETH | Domestic private health expenditure per capita (current US$) | SH.XPD.PVTD.PC.CD | .. | .. | .. | 2.28931226 | 2.26125872 | 2.26873481 | 2.29831663 | 2.33030737 | 2.36995148 | 3.68257868 | 4.79259624 | 5.54555815 | 7.33469943 | 8.06709831 | 8.15144782 | 10.03473096 | 9.89074466 | 13.10575411 | 13.50965767 | 13.73321919 | 9.89581332 | 9.86313314 | 11.55046904 | .. | .. |
476 | Ethiopia | ETH | Domestic private health expenditure per capita, PPP (current international $) | SH.XPD.PVTD.PP.CD | .. | .. | .. | 8.95748784 | 9.87443551 | 10.57806533 | 9.71524045 | 9.77553543 | 9.36346614 | 13.48737869 | 15.84897044 | 15.36108539 | 20.23113711 | 27.14893004 | 27.3563843 | 26.75258079 | 26.01878977 | 35.929244 | 35.79212821 | 37.04655306 | 27.71723172 | 28.94026827 | 32.44320861 | .. | .. |
477 | Ethiopia | ETH | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 0.389999985694885 | 0.360000014305115 | 0.330000013113022 | 0.300000011920929 | 0.310000002384186 | 0.28999999165535 | 0.280000001192093 | 0.270000010728836 | 0.259999990463257 | 0.239999994635582 | 0.230000004172325 | 0.219999998807907 | 0.200000002980232 | 0.189999997615814 | 0.180000007152557 | 0.170000001788139 | 0.159999996423721 | 0.159999996423721 | 0.159999996423721 | 0.159999996423721 | 0.159999996423721 | 0.159999996423721 | 0.170000001788139 | .. | .. |
478 | Ethiopia | ETH | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 1.67999994754791 | 1.58000004291534 | 1.42999994754791 | 1.27999997138977 | 1.30999994277954 | 1.23000001907349 | 1.22000002861023 | 1.13999998569489 | 1.0900000333786 | 1.02999997138977 | 1.00999999046326 | 0.970000028610229 | 0.939999997615814 | 0.889999985694885 | 0.839999973773956 | 0.829999983310699 | 0.790000021457672 | 0.769999980926514 | 0.75 | 0.709999978542328 | 0.699999988079071 | 0.699999988079071 | 0.720000028610229 | .. | .. |
479 | Ethiopia | ETH | Employers, total (% of total employment) (modeled ILO estimate) | SL.EMP.MPYR.ZS | 1.12000000476837 | 1.03999996185303 | 0.949999988079071 | 0.850000023841858 | 0.870000004768372 | 0.810000002384186 | 0.800000011920929 | 0.75 | 0.709999978542328 | 0.670000016689301 | 0.660000026226044 | 0.629999995231628 | 0.600000023841858 | 0.569999992847443 | 0.540000021457672 | 0.529999971389771 | 0.5 | 0.490000009536743 | 0.479999989271164 | 0.449999988079071 | 0.449999988079071 | 0.449999988079071 | 0.46000000834465 | .. | .. |
480 | Ethiopia | ETH | Employment in agriculture (% of total employment) (modeled ILO estimate) | SL.AGR.EMPL.ZS | 76.2399978637695 | 76.4599990844727 | 76.3600006103516 | 76.6999969482422 | 76.9199981689453 | 77.4100036621094 | 78.0100021362305 | 77.9199981689453 | 78.120002746582 | 77.4300003051758 | 76.6500015258789 | 75.8300018310547 | 75.0400009155273 | 74.0400009155273 | 73.0400009155273 | 72.1100006103516 | 71.0299987792969 | 70.2099990844727 | 69.4000015258789 | 68.6399993896484 | 67.9000015258789 | 67.2900009155273 | 66.629997253418 | .. | .. |
481 | Ethiopia | ETH | Employment in agriculture, female (% of female employment) (modeled ILO estimate) | SL.AGR.EMPL.FE.ZS | 66.4599990844727 | 67.0400009155273 | 67.0800018310547 | 68.2300033569336 | 69.2799987792969 | 70.7600021362305 | 72.2300033569336 | 72.5699996948242 | 73.4100036621094 | 72.5800018310547 | 71.6699981689453 | 70.4499969482422 | 69.379997253418 | 68.2300033569336 | 66.870002746582 | 65.2300033569336 | 63.5800018310547 | 62.7599983215332 | 61.939998626709 | 61.0999984741211 | 60.2799987792969 | 59.75 | 58.7099990844727 | .. | .. |
482 | Ethiopia | ETH | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 83.8399963378906 | 83.8300018310547 | 83.6500015258789 | 83.4400024414063 | 83.0699996948242 | 82.8199996948242 | 82.7600021362305 | 82.3600006103516 | 82.0699996948242 | 81.5 | 80.8399963378906 | 80.3600006103516 | 79.8000030517578 | 78.9199981689453 | 78.2300033569336 | 77.8899993896484 | 77.2900009155273 | 76.4899978637695 | 75.7300033569336 | 75.0599975585938 | 74.4100036621094 | 73.7799987792969 | 73.4400024414063 | .. | .. |
483 | Ethiopia | ETH | Employment in industry (% of total employment) (modeled ILO estimate) | SL.IND.EMPL.ZS | 6.53999996185303 | 6.51000022888184 | 6.51000022888184 | 6.59999990463257 | 6.71999979019165 | 6.84000015258789 | 6.98999977111816 | 7.19000005722046 | 7.3600001335144 | 7.42000007629395 | 7.51999998092651 | 7.63000011444092 | 7.76000022888184 | 7.92999982833862 | 8.09000015258789 | 8.25 | 8.40999984741211 | 8.59000015258789 | 8.77000045776367 | 8.96000003814697 | 9.11999988555908 | 9.22000026702881 | 9.31999969482422 | .. | .. |
484 | Ethiopia | ETH | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 8.55000019073486 | 8.47999954223633 | 8.4399995803833 | 8.5 | 8.53999996185303 | 8.61999988555908 | 8.77000045776367 | 8.93000030517578 | 9.06999969482422 | 8.98999977111816 | 8.90999984741211 | 8.93000030517578 | 8.92000007629395 | 8.85999965667725 | 8.85000038146973 | 8.92000007629395 | 8.93000030517578 | 8.92000007629395 | 8.93000030517578 | 9.02000045776367 | 9.06999969482422 | 9.03999996185303 | 9.10000038146973 | .. | .. |
485 | Ethiopia | ETH | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 4.96999979019165 | 4.96000003814697 | 5 | 5.09000015258789 | 5.25 | 5.40000009536743 | 5.53000020980835 | 5.75 | 5.94000005722046 | 6.1100001335144 | 6.34000015258789 | 6.53999996185303 | 6.78999996185303 | 7.15000009536743 | 7.44999980926514 | 7.67999982833862 | 7.96999979019165 | 8.3100004196167 | 8.64000034332275 | 8.90999984741211 | 9.15999984741211 | 9.38000011444092 | 9.51000022888184 | .. | .. |
486 | Ethiopia | ETH | Employment in services (% of total employment) (modeled ILO estimate) | SL.SRV.EMPL.ZS | 17.2199993133545 | 17.0400009155273 | 17.1299991607666 | 16.7000007629395 | 16.3700008392334 | 15.75 | 15 | 14.8900003433228 | 14.5200004577637 | 15.1499996185303 | 15.8400001525879 | 16.5300006866455 | 17.2000007629395 | 18.0400009155273 | 18.8700008392334 | 19.6499996185303 | 20.5599994659424 | 21.2099990844727 | 21.8299999237061 | 22.3999996185303 | 22.9899997711182 | 23.4799995422363 | 24.0499992370605 | .. | .. |
487 | Ethiopia | ETH | Employment in services, female (% of female employment) (modeled ILO estimate) | SL.SRV.EMPL.FE.ZS | 25 | 24.4899997711182 | 24.4899997711182 | 23.2700004577637 | 22.1800003051758 | 20.6299991607666 | 19 | 18.5100002288818 | 17.5300006866455 | 18.4300003051758 | 19.4200000762939 | 20.6200008392334 | 21.7099990844727 | 22.9099998474121 | 24.2800006866455 | 25.8500003814697 | 27.4899997711182 | 28.3299999237061 | 29.1399993896484 | 29.8799991607666 | 30.6499996185303 | 31.2099990844727 | 32.189998626709 | .. | .. |
488 | Ethiopia | ETH | Employment in services, male (% of male employment) (modeled ILO estimate) | SL.SRV.EMPL.MA.ZS | 11.1800003051758 | 11.210000038147 | 11.3599996566772 | 11.4700002670288 | 11.6800003051758 | 11.7799997329712 | 11.710000038147 | 11.8900003433228 | 12 | 12.3900003433228 | 12.8199996948242 | 13.0900001525879 | 13.4099998474121 | 13.9399995803833 | 14.3199996948242 | 14.4399995803833 | 14.7399997711182 | 15.1999998092651 | 15.6300001144409 | 16.0300006866455 | 16.4300003051758 | 16.8400001525879 | 17.0499992370605 | .. | .. |
489 | Ethiopia | ETH | Employment to population ratio, 15+, female (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.FE.ZS | 65.9169998168945 | 66.3730010986328 | 66.8679962158203 | 67.7630004882813 | 68.6579971313477 | 69.5149993896484 | 70.3769989013672 | 71.2870025634766 | 72.1389999389648 | 72.1320037841797 | 72.1289978027344 | 72.1220016479492 | 72.1110000610352 | 72.1129989624023 | 72.1009979248047 | 72.0879974365234 | 72.0859985351563 | 72.1719970703125 | 72.2630004882813 | 72.3349990844727 | 72.4150009155273 | 72.4909973144531 | 72.572998046875 | 68.1569976806641 | 68.9329986572266 |
490 | Ethiopia | ETH | Employment to population ratio, 15+, female (%) (national estimate) | SL.EMP.TOTL.SP.FE.NE.ZS | .. | .. | 51.7200012207031 | .. | .. | .. | .. | .. | 72.3600006103516 | .. | .. | .. | .. | .. | .. | .. | 72.1100006103516 | .. | .. | .. | .. | .. | .. | .. | .. |
491 | Ethiopia | ETH | Employment to population ratio, 15+, male (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.MA.ZS | 87.1019973754883 | 87.1360015869141 | 87.2180023193359 | 87.3499984741211 | 87.4889984130859 | 87.6029968261719 | 87.7279968261719 | 87.8970031738281 | 88.0270004272461 | 87.8960037231445 | 87.765998840332 | 87.6289978027344 | 87.4850006103516 | 87.3489990234375 | 87.1999969482422 | 87.0449981689453 | 86.8980026245117 | 86.5660018920898 | 86.2360000610352 | 85.9629974365234 | 85.681999206543 | 85.3960037231445 | 85.1289978027344 | 81.9710006713867 | 82.2969970703125 |
492 | Ethiopia | ETH | Employment to population ratio, 15+, male (%) (national estimate) | SL.EMP.TOTL.SP.MA.NE.ZS | .. | .. | 77.5599975585938 | .. | .. | .. | .. | .. | 88.2799987792969 | .. | .. | .. | .. | .. | .. | .. | 86.9300003051758 | .. | .. | .. | .. | .. | .. | .. | .. |
493 | Ethiopia | ETH | Employment to population ratio, 15+, total (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.ZS | 76.3629989624023 | 76.6119995117188 | 76.9039993286133 | 77.4229965209961 | 77.943000793457 | 78.4329986572266 | 78.9300003051758 | 79.4739990234375 | 79.9700012207031 | 79.9000015258789 | 79.8349990844727 | 79.7639999389648 | 79.6900024414063 | 79.6279983520508 | 79.5550003051758 | 79.4789962768555 | 79.4120025634766 | 79.2979965209961 | 79.1859970092773 | 79.0910034179688 | 78.9940032958984 | 78.8919982910156 | 78.802001953125 | 75.0120010375977 | 75.5650024414063 |
494 | Ethiopia | ETH | Employment to population ratio, 15+, total (%) (national estimate) | SL.EMP.TOTL.SP.NE.ZS | .. | .. | 64.1600036621094 | .. | .. | .. | .. | .. | 79.9700012207031 | .. | .. | .. | .. | .. | .. | .. | 79.4100036621094 | .. | .. | .. | .. | .. | .. | .. | .. |
495 | Ethiopia | ETH | Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate) | SL.EMP.1524.SP.FE.ZS | 62.8720016479492 | 62.9560012817383 | 63.0929985046387 | 63.806999206543 | 64.5130004882813 | 65.1849975585938 | 65.8629989624023 | 66.5930023193359 | 67.2779998779297 | 67.322998046875 | 67.370002746582 | 67.4120025634766 | 67.4530029296875 | 67.5120010375977 | 67.5719985961914 | 67.6330032348633 | 67.7040023803711 | 67.2249984741211 | 66.7429962158203 | 66.3440017700195 | 65.9229965209961 | 65.4609985351563 | 65.0279998779297 | 58.935001373291 | 60.8300018310547 |
496 | Ethiopia | ETH | Employment to population ratio, ages 15-24, female (%) (national estimate) | SL.EMP.1524.SP.FE.NE.ZS | .. | .. | 49.2099990844727 | .. | .. | .. | .. | .. | 67.6699981689453 | .. | .. | .. | .. | .. | .. | .. | 67.6699981689453 | .. | .. | .. | .. | .. | .. | .. | .. |
497 | Ethiopia | ETH | Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate) | SL.EMP.1524.SP.MA.ZS | 76.870002746582 | 77.0599975585938 | 77.2809982299805 | 77.5250015258789 | 77.7379989624023 | 77.927001953125 | 78.1179962158203 | 78.3399963378906 | 78.5319976806641 | 78.3779983520508 | 78.2259979248047 | 78.0749969482422 | 77.9300003051758 | 77.8050003051758 | 77.6829986572266 | 77.5619964599609 | 77.4440002441406 | 76.6849975585938 | 75.9000015258789 | 75.2379989624023 | 74.5279998779297 | 73.7590026855469 | 73.0189971923828 | 67.8889999389648 | 69.3479995727539 |
498 | Ethiopia | ETH | Employment to population ratio, ages 15-24, male (%) (national estimate) | SL.EMP.1524.SP.MA.NE.ZS | .. | .. | 70.6100006103516 | .. | .. | .. | .. | .. | 78.6399993896484 | .. | .. | .. | .. | .. | .. | .. | 77 | .. | .. | .. | .. | .. | .. | .. | .. |
499 | Ethiopia | ETH | Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) | SL.EMP.1524.SP.ZS | 69.9059982299805 | 70.0299987792969 | 70.197998046875 | 70.6699981689453 | 71.1220016479492 | 71.5510025024414 | 71.9869995117188 | 72.4660034179688 | 72.9079971313477 | 72.8560028076172 | 72.8079986572266 | 72.7600021362305 | 72.7170028686523 | 72.6940002441406 | 72.6689987182617 | 72.6439971923828 | 72.625 | 72.0070037841797 | 71.3730010986328 | 70.8399963378906 | 70.2720031738281 | 69.6510009765625 | 69.0619964599609 | 63.4529991149902 | 65.125 |
500 | Ethiopia | ETH | Employment to population ratio, ages 15-24, total (%) (national estimate) | SL.EMP.1524.SP.NE.ZS | .. | .. | 59.5099983215332 | .. | .. | .. | .. | .. | 72.8000030517578 | .. | .. | .. | .. | .. | .. | .. | 72.25 | .. | .. | .. | .. | .. | .. | .. | .. |
501 | Ethiopia | ETH | Exports of goods and services (annual % growth) | NE.EXP.GNFS.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -10.361418652440065 | 0.27516483261472047 | 2.821865660394508 | -11.218729844422157 | -8.141084753749894 | 7.665659055844415 | 11.777931056956831 | 17.70412757350148 | -0.5170462730204548 | 35.42544725871113 |
502 | Ethiopia | ETH | Exports of goods and services (constant 2015 US$) | NE.EXP.GNFS.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7370470108.591239 | 6606784843.987146 | 6624964392.444318 | 6811911987.648067 | 6047701984.514023 | 5555353440.300522 | 5981207894.3810835 | 6685670436.554547 | 7869310059.786037 | 7828622085.409491 | 10601946473.36004 |
503 | Ethiopia | ETH | External health expenditure (% of current health expenditure) | SH.XPD.EHEX.CH.ZS | .. | .. | .. | 16.25700188 | 17.07106018 | 12.69980526 | 14.19543171 | 29.64548492 | 22.23941803 | 32.35616684 | 33.34823608 | 46.76120758 | 33.59081268 | 34.442379 | 37.52742004 | 27.94426155 | 23.27150917 | 23.43493462 | 18.26107597 | 20.23424911 | 35.35738754 | 36.09846115 | 34.10496902 | .. | .. |
504 | Ethiopia | ETH | External health expenditure per capita (current US$) | SH.XPD.EHEX.PC.CD | .. | .. | .. | 0.87535746 | 0.95886863 | 0.66791894 | 0.8292032 | 1.74334739 | 1.47972266 | 2.80262417 | 3.99589039 | 6.29022492 | 5.25294417 | 5.75389268 | 5.67083296 | 5.77462377 | 4.62722579 | 5.21941179 | 4.36736272 | 5.07385817 | 8.812762 | 8.76979162 | 9.12042166 | .. | .. |
505 | Ethiopia | ETH | External health expenditure per capita, PPP (current international $) | SH.XPD.EHEX.PP.CD | .. | .. | .. | 3.42504775 | 4.18717523 | 3.11419832 | 3.50513429 | 7.31326453 | 5.84625177 | 10.264561 | 13.21428837 | 17.42379747 | 14.48907822 | 19.36409151 | 19.03140264 | 15.39514009 | 12.17247227 | 14.30894537 | 11.57077479 | 13.68717366 | 24.68370801 | 25.73220077 | 25.61763869 | .. | .. |
506 | Ethiopia | ETH | Female share of employment in senior and middle management (%) | SL.EMP.SMGT.FE.ZS | .. | .. | 14.1000003814697 | .. | .. | .. | .. | .. | 15.1000003814697 | .. | .. | .. | .. | .. | .. | .. | 21.1000003814697 | .. | .. | .. | .. | .. | .. | .. | .. |
507 | Ethiopia | ETH | Final consumption expenditure (annual % growth) | NE.CON.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.958720543392303 | 10.140196267903761 | 7.942598156200418 | 9.109543414335562 | 5.066781515818434 | 8.600135578010367 | 9.62511438732507 | 28.455502201423712 | 21.528145633472008 | 27.52430546957909 |
508 | Ethiopia | ETH | Final consumption expenditure (constant 2015 US$) | NE.CON.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 38813764753.4861 | 39962155584.91145 | 44014396594.106544 | 47510283246.45279 | 51838253125.0622 | 54464784152.526024 | 59148829431.91396 | 64841971923.49948 | 83293080671.63742 | 101224536381.23285 | 129085886984.9686 |
509 | Ethiopia | ETH | GDP (constant 2015 US$) | NY.GDP.MKTP.KD | 16113248919.186678 | 15556030352.598984 | 16359055323.367773 | 17352576330.760635 | 18793066846.479694 | 19077730261.007534 | 18665391883.263252 | 21198771447.52002 | 23704204628.467556 | 26272490503.098995 | 29282310890.19936 | 32441439350.566715 | 35297114307.540695 | 39727092173.71561 | 44167904219.33208 | 47987461378.62903 | 53065624131.02348 | 58508826790.97666 | 64589334978.80132 | 70682358692.84334 | 77442553522.34132 | 82721152428.05324 | 89640020508.40129 | 95071785237.71336 | 100431269846.86105 |
510 | Ethiopia | ETH | GDP growth (annual %) | NY.GDP.MKTP.KD.ZG | 3.133906850875931 | -3.458139133717424 | 5.162145821055347 | 6.073217479579569 | 8.301306320523281 | 1.5147257063110118 | -2.1613597220579805 | 13.572603136869475 | 11.818765946649407 | 10.834727065876976 | 11.456167000023612 | 10.788521685372515 | 8.80255319782566 | 12.550538345930761 | 11.178296227164125 | 8.647811633374161 | 10.582270048267219 | 10.257492961005127 | 10.392463020233407 | 9.433482657844024 | 9.564189642956066 | 6.8161477968170345 | 8.364085699078899 | 6.059530886433691 | 5.637303008192248 |
511 | Ethiopia | ETH | GDP per capita (constant 2015 US$) | NY.GDP.PCAP.KD | 265.4683314944038 | 248.86572981922976 | 254.2475994185378 | 262.02531336497526 | 275.7222155798166 | 271.98690915836033 | 258.6288155732493 | 285.5456887930887 | 310.48264976352567 | 334.7274380355744 | 362.9693134309053 | 391.25557207597694 | 414.120494108205 | 453.29882929108993 | 489.992672496167 | 517.5134609538896 | 556.3262878259395 | 596.4551280080624 | 640.5419230754219 | 682.2393577454264 | 727.8440543496367 | 757.3504167067896 | 799.7951342577373 | 826.9730531773124 | 852.0061530207207 |
512 | Ethiopia | ETH | GDP per capita growth (annual %) | NY.GDP.PCAP.KD.ZG | 0.05180286103099263 | -6.254079943062436 | 2.1625595469562313 | 3.059110081756941 | 5.227320230607987 | -1.3547353859757862 | -4.911300189574007 | 10.407530638138013 | 8.7330896417444 | 7.808741741451385 | 8.437275283160204 | 7.793016543933362 | 5.84398630054217 | 9.460612488462857 | 8.094846232553095 | 5.6165714310631785 | 7.499868080824285 | 7.21318425180695 | 7.391468862811706 | 6.50971203723924 | 6.684559617744483 | 4.053940151165804 | 5.6043697362063085 | 3.3981100603716357 | 3.0270756401588557 |
513 | Ethiopia | ETH | GDP per capita, PPP (constant 2017 international $) | NY.GDP.PCAP.PP.KD | 737.3295542912306 | 691.2163745220311 | 706.1643402193819 | 727.7666847448054 | 765.8093798880956 | 755.4346892296297 | 718.3330239053872 | 793.0937534522038 | 862.3553418842599 | 929.6944434256121 | 1008.1353229096749 | 1086.6994754092616 | 1150.2060438802425 | 1259.0225805106315 | 1360.9385224360892 | 1437.376606681568 | 1545.1779560073142 | 1656.6344889924262 | 1779.084111416901 | 1894.897363970418 | 2021.5629079600892 | 2103.515858366958 | 2221.4046645295766 | 2296.8904399165212 | 2366.4190509043715 |
514 | Ethiopia | ETH | GDP per capita, PPP (current international $) | NY.GDP.PCAP.PP.CD | 465.9628041280369 | 441.737684140394 | 457.65025850085846 | 482.33574571297413 | 518.9838164388344 | 519.931906593849 | 504.1538956265763 | 571.5659226180595 | 640.9698467699249 | 712.3435690279232 | 793.3215141242481 | 871.5463025924995 | 928.3920241649951 | 1028.436486016332 | 1134.7845092344671 | 1213.5959716993423 | 1283.5704492513291 | 1513.7032362895404 | 1657.3447042636453 | 1878.8126819381412 | 2021.5629079600892 | 2153.769081359742 | 2315.158137813175 | 2422.6810259853423 | 2599.7361652958834 |
515 | Ethiopia | ETH | GDP per person employed (constant 2017 PPP $) | SL.GDP.PCAP.EM.KD | 1810.1894766048204 | 1690.4787189663832 | 1718.2875487647468 | 1755.764632016997 | 1838.2233717744277 | 1802.9537894287444 | 1703.4476118055518 | 1866.9925399800911 | 2015.2550912078354 | 2167.036053431312 | 2341.252453490209 | 2511.484667102353 | 2642.098639646874 | 2871.223121759647 | 3077.124257797665 | 3221.4249808287805 | 3431.742101738809 | 3648.231057832087 | 3885.3735425919936 | 4110.9755925857835 | 4356.033071824462 | 4502.630368501983 | 4724.7766013331775 | 5096.388408991933 | 5181.5880127921355 |
516 | Ethiopia | ETH | GDP, PPP (constant 2017 international $) | NY.GDP.MKTP.PP.KD | 44754018593.80737 | 43206362362.90375 | 45436737792.05041 | 48196209693.78795 | 52197124695.35102 | 52987767961.06672 | 51842511686.738686 | 58878890054.16492 | 65837648261.651695 | 72970977757.39377 | 81330654830.83087 | 90105030164.11053 | 98036573378.22322 | 110340691113.09369 | 122674900424.81546 | 133283594734.98283 | 147388024659.87677 | 162506340914.72815 | 179394752299.82568 | 196317925147.112 | 215094143811.2983 | 229755278555.77457 | 248972206952.337 | 264058754731.24948 | 278944546855.1092 |
517 | Ethiopia | ETH | GDP, PPP (current international $) | NY.GDP.MKTP.PP.CD | 28282750743.681686 | 27612017240.646923 | 29446594243.922802 | 31942592633.71428 | 35373636955.82505 | 36469110586.17735 | 36385079560.78337 | 42432772884.73081 | 48935682622.149185 | 55911280419.86431 | 64000691939.73894 | 72265338910.6871 | 79130494301.49333 | 90132134553.88487 | 102289393957.9102 | 112533091823.03741 | 122434385173.20428 | 148485604878.24057 | 167119104031.5757 | 194651496419.4836 | 215094143811.2983 | 235244157187.7598 | 259479976889.7912 | 278520091213.39105 | 306447087760.7909 |
518 | Ethiopia | ETH | General government final consumption expenditure (annual % growth) | NE.CON.GOVT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -0.2586522629505481 | 12.334416318155732 | 18.024390222822447 | 3.7927639331875014 | 13.63914472273862 | 8.300018671355502 | 3.643085351648523 | 12.094415473186743 | 18.726666130631386 | 20.54150632450309 |
519 | Ethiopia | ETH | General government final consumption expenditure (constant 2015 US$) | NE.CON.GOVT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4241712924.442808 | 4230741637.9758706 | 4752578924.949375 | 5609202296.029871 | 5821946097.653217 | 6616009751.591973 | 7165139796.272808 | 7426171954.615962 | 8324324044.56049 | 9883192416.017204 | 11913349011.216188 |
520 | Ethiopia | ETH | Gini index | SI.POV.GINI | .. | .. | 30 | .. | .. | .. | .. | 29.8 | .. | .. | .. | .. | .. | 33.2 | .. | .. | .. | .. | 35 | .. | .. | .. | .. | .. | .. |
521 | Ethiopia | ETH | GNI (constant 2015 US$) | NY.GNP.MKTP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 44071270994.77506 | 47880378096.944244 | 52945509653.8313 | 58346495201.18545 | 64326834729.99064 | 70444016858.4429 | 76978559878.31055 | 82323694783.36113 | 88965458391.91797 | 94318656049.51868 | 99611184176.28569 |
522 | Ethiopia | ETH | GNI growth (annual %) | NY.GNP.MKTP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.64306160496433 | 10.578720883597853 | 10.20102664544531 | 10.249697960750325 | 9.509533858037457 | 9.276221475272763 | 6.943667059373794 | 8.067863846532816 | 6.0171641380392344 | 5.611326908632336 |
523 | Ethiopia | ETH | GNI per capita (constant 2015 US$) | NY.GNP.PCAP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 488.920636754614 | 516.3586376287351 | 555.067038692348 | 594.8002749802521 | 637.9386695470157 | 679.9388377425239 | 723.4832087976315 | 753.7115081085 | 793.7764888417939 | 820.4220292048368 | 845.0489768503929 |
524 | Ethiopia | ETH | GNI per capita growth (annual %) | NY.GNP.PCAP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.611953926970784 | 7.496417846590674 | 7.158277022088981 | 7.252584839204374 | 6.583731352314999 | 6.404159997637436 | 4.178161834758427 | 5.315691786880123 | 3.356806448364509 | 3.0017413927104144 |
525 | Ethiopia | ETH | GNI per capita, Atlas method (current US$) | NY.GNP.PCAP.CD | 140 | 130 | 120 | 130 | 130 | 120 | 110 | 140 | 160 | 180 | 220 | 280 | 340 | 380 | 390 | 410 | 470 | 550 | 600 | 670 | 740 | 800 | 850 | 890 | 960 |
526 | Ethiopia | ETH | GNI per capita, PPP (constant 2017 international $) | NY.GNP.PCAP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1358.033249149547 | 1434.2454494047636 | 1541.7624812378572 | 1652.1261106674956 | 1771.947958494303 | 1888.6082517843981 | 2009.5577459572542 | 2093.5203207462723 | 2204.805408492848 | 2278.8164586190255 | 2347.22063552129 |
527 | Ethiopia | ETH | GNI per capita, PPP (current international $) | NY.GNP.PCAP.PP.CD | 460 | 440 | 450 | 480 | 520 | 520 | 500 | 570 | 640 | 710 | 790 | 870 | 930 | 1020 | 1130 | 1210 | 1280 | 1510 | 1650 | 1870 | 2010 | 2140 | 2300 | 2410 | 2590 |
528 | Ethiopia | ETH | GNI, Atlas method (current US$) | NY.GNP.ATLS.CD | 8749819777.234625 | 7969964500.661967 | 8003894080.081504 | 8282808160.47557 | 8565169694.416424 | 8244554537.351186 | 8231634992.17292 | 10032643822.789886 | 12291510934.123798 | 14407106797.331577 | 17783871681.349792 | 23011340074.88801 | 28930389370.878624 | 33247716569.741077 | 35237153539.82399 | 38143234738.89083 | 44574863493.55522 | 53613560417.01184 | 60070079523.16255 | 68942747989.16751 | 78378593589.74936 | 86862198769.10829 | 94972317026.58804 | 102643542580.06453 | 113593421405.22774 |
529 | Ethiopia | ETH | GNI, PPP (constant 2017 international $) | NY.GNP.MKTP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 122413019299.94621 | 132993251970.53743 | 147062236890.52063 | 162064094861.11053 | 178675175087.19824 | 195666351358.02307 | 213816795462.57864 | 228663521856.52237 | 247111783466.59338 | 261980905082.21442 | 276681510104.5712 |
530 | Ethiopia | ETH | GNI, PPP (current international $) | NY.GNP.MKTP.PP.CD | 27971297397.39186 | 27383170537.881577 | 29250766632.065807 | 31709569421.4444 | 35153364909.15778 | 36220115501.784386 | 36106147528.83725 | 42166685855.70563 | 48794472563.37203 | 55770778598.665764 | 64046772909.526955 | 72318569548.45204 | 79028887577.01329 | 89806292572.82532 | 102066933556.26118 | 112283157655.96619 | 122160005499.9225 | 148077638928.90082 | 166439908210.72223 | 194015690748.87738 | 213816795462.57864 | 234190855940.93903 | 257884909729.08194 | 276935254983.7209 | 304912793676.70026 |
531 | Ethiopia | ETH | Gross capital formation (annual % growth) | NE.GDI.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 46.51122796154269 | 9.440736524937734 | 24.390427144205873 | 26.26626586045866 | 10.578568788663574 | 11.885511341808012 | 4.15125830972643 | 25.25476693107902 | 7.424957139134676 | 11.987766142391493 |
532 | Ethiopia | ETH | Gross capital formation (constant 2015 US$) | NE.GDI.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10430962091.9206 | 15282530649.075895 | 16725314101.998007 | 20804689652.68542 | 26269304748.30311 | 29048221221.406017 | 32500750849.269714 | 33849940969.623505 | 42398664667.80975 | 45546747346.96006 | 51006784904.37954 |
533 | Ethiopia | ETH | Gross fixed capital formation (annual % growth) | NE.GDI.FTOT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 46.51122796154269 | 9.440736524937734 | 24.390427144205873 | 26.26626586045866 | 10.578568788663574 | 11.885511341808012 | 4.15125830972643 | 25.25476693107902 | 7.424957139134676 | 11.987766142391493 |
534 | Ethiopia | ETH | Gross fixed capital formation (constant 2015 US$) | NE.GDI.FTOT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10430962091.9206 | 15282530649.075895 | 16725314101.998007 | 20804689652.68542 | 26269304748.30311 | 29048221221.406017 | 32500750849.269714 | 33849940969.623505 | 42398664667.80975 | 45546747346.96006 | 51006784904.37954 |
535 | Ethiopia | ETH | Gross national expenditure (constant 2015 US$) | NE.DAB.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 49244726845.4067 | 55244686233.98735 | 60739710696.10455 | 68314972899.138214 | 78107557873.36531 | 83513005373.93204 | 91649580281.18369 | 98691912893.12299 | 125691745339.44717 | 146771283728.1929 | 180092671889.34814 |
536 | Ethiopia | ETH | Gross value added at basic prices (GVA) (constant 2015 US$) | NY.GDP.FCST.KD | 15039369702.32658 | 14497322963.93343 | 15240370144.530312 | 16136908711.95118 | 17333921479.71359 | 17617145784.1995 | 17247394124.393425 | 19270444837.415142 | 21707024840.111385 | 24211903344.183277 | 27067712122.466408 | 30095811028.847534 | 33117847987.02869 | 36617446378.646935 | 40786701986.33624 | 44334944140.38611 | 48742983336.43799 | 53759903783.358246 | 59357907701.18832 | 65288682891.181496 | 71954455622.3867 | 77496893912.96567 | 84500328332.87042 | 89621769059.28654 | 95233320681.92331 |
537 | Ethiopia | ETH | Hospital beds (per 1,000 people) | SH.MED.BEDS.ZS | .. | .. | .. | .. | .. | .. | .. | 0.2 | .. | 0.2 | .. | 0.2 | .. | .. | 6.3 | .. | .. | .. | 0.3 | 0.33 | .. | .. | .. | .. | .. |
538 | Ethiopia | ETH | Households and NPISHs Final consumption expenditure (annual % growth) | NE.CON.PRVT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.4170406634927275 | 9.838735471281893 | 6.526003156247114 | 9.937243023576968 | 3.8167125026402857 | 8.65041080723232 | 10.623985085619125 | 31.015054083844632 | 21.903120370125293 | 28.434590854801456 |
539 | Ethiopia | ETH | Households and NPISHs Final consumption expenditure (constant 2015 US$) | NE.CON.PRVT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34591043010.11912 | 35773033015.70115 | 39292647104.17032 | 41856886494.36151 | 46016307027.40898 | 47772617170.97744 | 51905144809.6334 | 57419539652.87786 | 75228240930.91254 | 91705573094.33818 | 117781677594.76414 |
540 | Ethiopia | ETH | Households and NPISHs Final consumption expenditure per capita (constant 2015 US$) | NE.CON.PRVT.PC.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 383.74828755264946 | 385.78882051505946 | 411.9339564978017 | 426.7006528981298 | 456.35047652742713 | 461.1102439036997 | 487.8306476419298 | 525.7024474005203 | 671.2089166654483 | 797.69237094752 | .. |
541 | Ethiopia | ETH | Households and NPISHs Final consumption expenditure per capita growth (annual %) | NE.CON.PRVT.PC.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.5317373467445208 | 6.777059000267656 | 3.5847242421751986 | 6.9486239188801875 | 1.0430069915762488 | 5.794797251090884 | 7.76330883302532 | 27.678484280304303 | 18.844126045052974 | .. |
542 | Ethiopia | ETH | Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $) | NE.CON.PRVT.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 95642630023.21858 | 98910777582.74586 | 108642347341.70023 | 115732350358.24054 | 127232955270.23647 | 132089071381.51431 | 143515318687.47363 | 158762364740.40958 | 208002598029.4383 | 253561657448.81403 | 325660877309.03754 |
543 | Ethiopia | ETH | Households and NPISHs Final consumption expenditure, PPP (current international $) | NE.CON.PRVT.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 66924740420.57277 | 80456964728.29709 | 87876241927.5143 | 101078238465.4786 | 117359837283.1232 | 129912649897.23662 | 143515318687.47363 | 153021216512.17493 | 172087760248.90735 | 185137674982.7548 | 202678215256.56982 |
544 | Ethiopia | ETH | Imports of goods and services (annual % growth) | NE.IMP.GNFS.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 22.206410696193927 | 4.213199996281077 | 20.184962077646063 | 21.851529746905513 | 0.04797860583730085 | -7.468505497351387 | 2.2040382912837515 | 18.46389681097365 | 15.603050339339617 | 24.52685930151837 |
545 | Ethiopia | ETH | Imports of goods and services (constant 2015 US$) | NE.IMP.GNFS.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10490653550.85967 | 12820251163.07842 | 13360393984.604464 | 16057184443.82098 | 19565924879.078007 | 19575312337.05416 | 18113329059.037567 | 18512553767.32498 | 21930692591.99988 | 25352549596.895447 | 31570733765.873653 |
546 | Ethiopia | ETH | Income share held by fourth 20% | SI.DST.04TH.20 | .. | .. | 21.5 | .. | .. | .. | .. | 21.4 | .. | .. | .. | .. | .. | 21.3 | .. | .. | .. | .. | 21.2 | .. | .. | .. | .. | .. | .. |
547 | Ethiopia | ETH | Income share held by highest 10% | SI.DST.10TH.10 | .. | .. | 25.5 | .. | .. | .. | .. | 25.6 | .. | .. | .. | .. | .. | 27.4 | .. | .. | .. | .. | 28.5 | .. | .. | .. | .. | .. | .. |
548 | Ethiopia | ETH | Income share held by highest 20% | SI.DST.05TH.20 | .. | .. | 39.4 | .. | .. | .. | .. | 39.3 | .. | .. | .. | .. | .. | 41.7 | .. | .. | .. | .. | 43 | .. | .. | .. | .. | .. | .. |
549 | Ethiopia | ETH | Income share held by lowest 10% | SI.DST.FRST.10 | .. | .. | 3.9 | .. | .. | .. | .. | 4.1 | .. | .. | .. | .. | .. | 3.2 | .. | .. | .. | .. | 2.9 | .. | .. | .. | .. | .. | .. |
550 | Ethiopia | ETH | Income share held by lowest 20% | SI.DST.FRST.20 | .. | .. | 9.1 | .. | .. | .. | .. | 9.4 | .. | .. | .. | .. | .. | 8 | .. | .. | .. | .. | 7.3 | .. | .. | .. | .. | .. | .. |
551 | Ethiopia | ETH | Income share held by second 20% | SI.DST.02ND.20 | .. | .. | 13.2 | .. | .. | .. | .. | 13 | .. | .. | .. | .. | .. | 12.6 | .. | .. | .. | .. | 12.1 | .. | .. | .. | .. | .. | .. |
552 | Ethiopia | ETH | Income share held by third 20% | SI.DST.03RD.20 | .. | .. | 16.8 | .. | .. | .. | .. | 16.9 | .. | .. | .. | .. | .. | 16.3 | .. | .. | .. | .. | 16.3 | .. | .. | .. | .. | .. | .. |
553 | Ethiopia | ETH | Industry (including construction), value added (annual % growth) | NV.IND.TOTL.KD.ZG | 3.6781129622211637 | 5.206390559210732 | 5.483743629980054 | 5.348708188287816 | 5.114180726890382 | 8.32587444991151 | 6.4755841490384825 | 11.645205480026007 | 9.431168853401985 | 10.164074420576611 | 9.523255063755613 | 10.130327712034727 | 9.673308143290882 | 10.817155819968875 | 15.010864337632185 | 19.637824870436177 | 24.10271588845947 | 17.0423338419605 | 19.846193061335484 | 23.944050299332375 | 20.572140798664492 | 12.739949536851228 | 12.555716874447882 | 9.635114898844833 | 7.25807062492045 |
554 | Ethiopia | ETH | Industry (including construction), value added (constant 2015 US$) | NV.IND.TOTL.KD | 1571415426.3710523 | 1653229450.7756157 | 1743888315.4714777 | 1837163812.595695 | 1931119690.2208686 | 2091902291.106178 | 2227365184.2824225 | 2486746436.7826705 | 2721275692.1916013 | 2997868178.735017 | 3283362811.8711176 | 3615978224.6887403 | 3965762940.757181 | 4394745697.509465 | 5054435012.146539 | 6047016108.021885 | 7504511220.267779 | 8783455075.633198 | 10526636527.399033 | 13047139672.347351 | 15731215615.941061 | 17735364546.94521 | 19962166706.110855 | 21885544404.543583 | 23474012674.073685 |
555 | Ethiopia | ETH | Industry (including construction), value added per worker (constant 2015 US$) | NV.IND.EMPL.KD | 970.2498399489167 | 991.8193030376672 | 1012.0393288354825 | 1012.9070725323813 | 1010.6385237130495 | 1039.074980774429 | 1045.1710720161489 | 1095.0958808009073 | 1130.054106826357 | 1198.0441936139416 | 1255.3895969182531 | 1320.5085317021335 | 1380.4097355238523 | 1447.505281487546 | 1574.582402893503 | 1781.4102467404475 | 2091.1636210031156 | 2315.0382762278873 | 2627.0420166765516 | 3085.960371577369 | 3539.1308471244993 | 3821.6571156676796 | 4123.8810648046165 | .. | .. |
556 | Ethiopia | ETH | International migrant stock (% of population) | SM.POP.TOTL.ZS | .. | .. | .. | 0.920154796542265 | .. | .. | .. | .. | 0.671260321204072 | .. | .. | .. | .. | 0.648364822592643 | .. | .. | .. | .. | 1.07952601222951 | .. | .. | .. | .. | .. | .. |
557 | Ethiopia | ETH | International migrant stock, total | SM.POP.TOTL | .. | .. | .. | 611384 | .. | .. | .. | .. | 514242 | .. | .. | .. | .. | 567720 | .. | .. | .. | .. | 1072949 | .. | .. | .. | .. | .. | .. |
558 | Ethiopia | ETH | Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.FE.ZS | 67.1920013427734 | 67.6350021362305 | 68.0759963989258 | 68.5120010375977 | 68.9400024414063 | 69.359001159668 | 69.7710037231445 | 70.1780014038086 | 70.5830001831055 | 70.6100006103516 | 70.6350021362305 | 70.6589965820313 | 70.6849975585938 | 70.713996887207 | 70.7519989013672 | 70.7939987182617 | 70.8359985351563 | 70.3649978637695 | 69.8919982910156 | 69.5080032348633 | 69.1009979248047 | 68.6600036621094 | 68.2409973144531 | 62.7529983520508 | 65.5179977416992 |
559 | Ethiopia | ETH | Labor force participation rate for ages 15-24, female (%) (national estimate) | SL.TLF.ACTI.1524.FE.NE.ZS | .. | .. | 53.1699981689453 | .. | .. | .. | .. | .. | 70.9300003051758 | .. | .. | .. | .. | .. | .. | .. | 70.8499984741211 | .. | .. | .. | .. | .. | .. | .. | .. |
560 | Ethiopia | ETH | Labor force participation rate for ages 15-24, male (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.MA.ZS | 80.0989990234375 | 80.2009963989258 | 80.2990036010742 | 80.3899993896484 | 80.4509963989258 | 80.5070037841797 | 80.556999206543 | 80.6060028076172 | 80.6559982299805 | 80.4929962158203 | 80.3320007324219 | 80.1729965209961 | 80.0220031738281 | 79.879997253418 | 79.7490005493164 | 79.620002746582 | 79.4869995117188 | 78.7399978637695 | 77.9680023193359 | 77.3239974975586 | 76.6309967041016 | 75.8820037841797 | 75.1579971313477 | 70.6679992675781 | 72.572998046875 |
561 | Ethiopia | ETH | Labor force participation rate for ages 15-24, male (%) (national estimate) | SL.TLF.ACTI.1524.MA.NE.ZS | .. | .. | 73.4199981689453 | .. | .. | .. | .. | .. | 80.7600021362305 | .. | .. | .. | .. | .. | .. | .. | 79.0999984741211 | .. | .. | .. | .. | .. | .. | .. | .. |
562 | Ethiopia | ETH | Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.ZS | 73.677001953125 | 73.9369964599609 | 74.1969985961914 | 74.4550018310547 | 74.693000793457 | 74.9280014038086 | 75.161003112793 | 75.390998840332 | 75.6210021972656 | 75.5559997558594 | 75.4919967651367 | 75.4309997558594 | 75.3759994506836 | 75.3290023803711 | 75.2880020141602 | 75.2490005493164 | 75.2070007324219 | 74.5989990234375 | 73.9749984741211 | 73.4589996337891 | 72.9059982299805 | 72.306999206543 | 71.7320022583008 | 66.7470016479492 | 69.0749969482422 |
563 | Ethiopia | ETH | Labor force participation rate for ages 15-24, total (%) (national estimate) | SL.TLF.ACTI.1524.NE.ZS | .. | .. | 62.9199981689453 | .. | .. | .. | .. | .. | 75.5299987792969 | .. | .. | .. | .. | .. | .. | .. | 74.9000015258789 | .. | .. | .. | .. | .. | .. | .. | .. |
564 | Ethiopia | ETH | Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.FE.ZS | 68.8860015869141 | 69.6370010375977 | 70.3769989013672 | 71.1050033569336 | 71.8259963989258 | 72.5339965820313 | 73.2300033569336 | 73.9140014648438 | 74.5879974365234 | 74.5490036010742 | 74.5110015869141 | 74.4720001220703 | 74.4329986572266 | 74.3929977416992 | 74.3529968261719 | 74.3119964599609 | 74.2730026245117 | 74.3690032958984 | 74.4680023193359 | 74.5510025024414 | 74.6389999389648 | 74.7289962768555 | 74.8170013427734 | 71.0289993286133 | 72.3349990844727 |
565 | Ethiopia | ETH | Labor force participation rate, female (% of female population ages 15+) (national estimate) | SL.TLF.CACT.FE.NE.ZS | .. | .. | 54.4799995422363 | .. | .. | .. | .. | .. | 74.7900009155273 | .. | .. | .. | .. | .. | .. | .. | 74.3000030517578 | .. | .. | .. | .. | .. | .. | .. | .. |
566 | Ethiopia | ETH | Labor force participation rate, female (% of female population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.FE.ZS | 70.47 | 71.31 | 72.13 | 72.92 | 73.72 | 74.49 | 75.25 | 75.98 | 76.68 | 76.62 | 76.55 | 76.46 | 76.37 | 76.28 | 76.21 | 76.15 | 76.1 | 76.05 | 76.01 | 75.99 | 75.98 | 76 | 76.02 | .. | .. |
567 | Ethiopia | ETH | Labor force participation rate, male (% of male population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.MA.ZS | 89.6159973144531 | 89.6179962158203 | 89.620002746582 | 89.6240005493164 | 89.6320037841797 | 89.6389999389648 | 89.6470031738281 | 89.6559982299805 | 89.6669998168945 | 89.5139999389648 | 89.359001159668 | 89.2009963989258 | 89.0390014648438 | 88.8730010986328 | 88.7040023803711 | 88.5319976806641 | 88.3580017089844 | 88.0329971313477 | 87.7089996337891 | 87.4449996948242 | 87.1709976196289 | 86.8960037231445 | 86.6320037841797 | 84.1119995117188 | 84.6829986572266 |
568 | Ethiopia | ETH | Labor force participation rate, male (% of male population ages 15+) (national estimate) | SL.TLF.CACT.MA.NE.ZS | .. | .. | 79.7300033569336 | .. | .. | .. | .. | .. | 89.9100036621094 | .. | .. | .. | .. | .. | .. | .. | 88.3899993896484 | .. | .. | .. | .. | .. | .. | .. | .. |
569 | Ethiopia | ETH | Labor force participation rate, male (% of male population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.MA.ZS | 90.56 | 90.54 | 90.54 | 90.55 | 90.62 | 90.7 | 90.79 | 90.86 | 90.92 | 90.77 | 90.6 | 90.41 | 90.2 | 89.98 | 89.78 | 89.59 | 89.4 | 88.84 | 88.3 | 87.87 | 87.45 | 87.06 | 86.69 | .. | .. |
570 | Ethiopia | ETH | Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.ZS | 79.1080017089844 | 79.4899978637695 | 79.8669967651367 | 80.2389984130859 | 80.6050033569336 | 80.9670028686523 | 81.322998046875 | 81.6740036010742 | 82.0199966430664 | 81.9240036010742 | 81.8270034790039 | 81.7310028076172 | 81.6330032348633 | 81.536003112793 | 81.4369964599609 | 81.338996887207 | 81.2399978637695 | 81.1340026855469 | 81.0279998779297 | 80.9420013427734 | 80.8529968261719 | 80.7639999389648 | 80.6790008544922 | 77.5220031738281 | 78.463996887207 |
571 | Ethiopia | ETH | Labor force participation rate, total (% of total population ages 15+) (national estimate) | SL.TLF.CACT.NE.ZS | .. | .. | 66.629997253418 | .. | .. | .. | .. | .. | 82.0199966430664 | .. | .. | .. | .. | .. | .. | .. | 81.2399978637695 | .. | .. | .. | .. | .. | .. | .. | .. |
572 | Ethiopia | ETH | Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.ZS | 80.37 | 80.79 | 81.21 | 81.62 | 82.06 | 82.49 | 82.92 | 83.33 | 83.71 | 83.6 | 83.48 | 83.35 | 83.2 | 83.06 | 82.93 | 82.81 | 82.7 | 82.41 | 82.12 | 81.91 | 81.69 | 81.51 | 81.34 | .. | .. |
573 | Ethiopia | ETH | Labor force with advanced education (% of total working-age population with advanced education) | SL.TLF.ADVN.ZS | .. | .. | 90.2600021362305 | .. | .. | .. | .. | .. | 94.2300033569336 | .. | .. | .. | .. | .. | .. | .. | 93.5899963378906 | .. | .. | .. | .. | .. | .. | .. | .. |
574 | Ethiopia | ETH | Labor force with advanced education, female (% of female working-age population with advanced education) | SL.TLF.ADVN.FE.ZS | .. | .. | 88.0800018310547 | .. | .. | .. | .. | .. | 92.4400024414063 | .. | .. | .. | .. | .. | .. | .. | 87.8300018310547 | .. | .. | .. | .. | .. | .. | .. | .. |
575 | Ethiopia | ETH | Labor force with advanced education, male (% of male working-age population with advanced education) | SL.TLF.ADVN.MA.ZS | .. | .. | 91.0400009155273 | .. | .. | .. | .. | .. | 94.9800033569336 | .. | .. | .. | .. | .. | .. | .. | 95.8300018310547 | .. | .. | .. | .. | .. | .. | .. | .. |
576 | Ethiopia | ETH | Labor force with basic education (% of total working-age population with basic education) | SL.TLF.BASC.ZS | .. | .. | 65.6500015258789 | .. | .. | .. | .. | .. | 78.3600006103516 | .. | .. | .. | .. | .. | .. | .. | 79.1399993896484 | .. | .. | .. | .. | .. | .. | .. | .. |
577 | Ethiopia | ETH | Labor force with basic education, female (% of female working-age population with basic education) | SL.TLF.BASC.FE.ZS | .. | .. | 48.2299995422363 | .. | .. | .. | .. | .. | 64.6500015258789 | .. | .. | .. | .. | .. | .. | .. | 69.4700012207031 | .. | .. | .. | .. | .. | .. | .. | .. |
578 | Ethiopia | ETH | Labor force with basic education, male (% of male working-age population with basic education) | SL.TLF.BASC.MA.ZS | .. | .. | 74.1399993896484 | .. | .. | .. | .. | .. | 85.5999984741211 | .. | .. | .. | .. | .. | .. | .. | 85.7600021362305 | .. | .. | .. | .. | .. | .. | .. | .. |
579 | Ethiopia | ETH | Labor force with intermediate education (% of total working-age population with intermediate education) | SL.TLF.INTM.ZS | .. | .. | 76.9100036621094 | .. | .. | .. | .. | .. | 70.9199981689453 | .. | .. | .. | .. | .. | .. | .. | 81.2099990844727 | .. | .. | .. | .. | .. | .. | .. | .. |
580 | Ethiopia | ETH | Labor force with intermediate education, female (% of female working-age population with intermediate education) | SL.TLF.INTM.FE.ZS | .. | .. | 70.6100006103516 | .. | .. | .. | .. | .. | 65.8899993896484 | .. | .. | .. | .. | .. | .. | .. | 74.4300003051758 | .. | .. | .. | .. | .. | .. | .. | .. |
581 | Ethiopia | ETH | Labor force with intermediate education, male (% of male working-age population with intermediate education) | SL.TLF.INTM.MA.ZS | .. | .. | 80.9700012207031 | .. | .. | .. | .. | .. | 74.379997253418 | .. | .. | .. | .. | .. | .. | .. | 86.129997253418 | .. | .. | .. | .. | .. | .. | .. | .. |
582 | Ethiopia | ETH | Labor force, female (% of total labor force) | SL.TLF.TOTL.FE.ZS | 44.14086458693474 | 44.403954494302134 | 44.66096707409983 | 44.91153350213555 | 45.17213121620704 | 45.419167867186886 | 45.65701833185315 | 45.889247559994274 | 46.11826380594422 | 46.15279655982694 | 46.18761509136462 | 46.21448558521355 | 46.2313100217607 | 46.236343188068965 | 46.22906065926004 | 46.215507801701676 | 46.20269816673348 | 46.28168572962551 | 46.369050557073244 | 46.44887701192592 | 46.538428617405856 | 46.6329319004117 | 46.725855847548225 | 46.15633643398183 | 46.435707502061575 |
583 | Ethiopia | ETH | Labor force, total | SL.TLF.TOTL.IN | 25612115 | 26518789 | 27461846 | 28448679 | 29365214 | 30338931 | 31356568 | 32409760 | 33507107 | 34526170 | 35604865 | 36761939 | 38010277 | 39350692 | 40809845 | 42342365 | 43937092 | 45575209 | 47245852 | 48872202 | 50540486 | 52237702 | 53950175 | 53546648 | 55899088 |
584 | Ethiopia | ETH | Manufacturing, value added (annual % growth) | NV.IND.MANF.KD.ZG | 2.965248808276357 | 0.38386584890086795 | 8.705863900975402 | 6.657001608683373 | 3.8075787313469647 | 1.8092352199227832 | 1.2060749139205456 | 7.265356671999257 | 13.03492427364128 | 10.300529875204319 | 9.930254524223955 | 9.261843273961404 | 8.624984431956932 | 9.207691208346787 | 9.238393083554698 | 11.804471823223068 | 16.933577047063153 | 16.637034301260172 | 18.222644064024422 | 22.900629309103238 | 24.655226850297367 | 6.82134092215702 | 7.697168421487262 | 7.5123822267993745 | 5.099748898122641 |
585 | Ethiopia | ETH | Manufacturing, value added (constant 2015 US$) | NV.IND.MANF.KD | 608990911.5823466 | 611328619.7148212 | 664550057.3349049 | 708789165.3421957 | 735776870.8518568 | 749088805.1393543 | 758123377.3011273 | 813203744.6758609 | 919204236.9847746 | 1013887144.0295352 | 1114568718.0200531 | 1217798325.8636713 | 1322833241.8820453 | 1444635641.9959073 | 1578096761.2286232 | 1764382748.7510517 | 2063155860.9159017 | 2406403809.18494 | 2844914210.075837 | 3496417467.487307 | 4358467125.729725 | 4655773027.355887 | 5014135718.593646 | 5390816759.144875 | 5665734877.419176 |
586 | Ethiopia | ETH | Multidimensional poverty headcount ratio (% of total population) | SI.POV.MDIM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
587 | Ethiopia | ETH | Multidimensional poverty headcount ratio, children (% of population ages 0-17) | SI.POV.MDIM.17 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
588 | Ethiopia | ETH | Multidimensional poverty headcount ratio, female (% of female population) | SI.POV.MDIM.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
589 | Ethiopia | ETH | Multidimensional poverty headcount ratio, household (% of total households) | SI.POV.MDIM.HH | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
590 | Ethiopia | ETH | Multidimensional poverty headcount ratio, male (% of male population) | SI.POV.MDIM.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
591 | Ethiopia | ETH | Multidimensional poverty index (scale 0-1) | SI.POV.MDIM.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
592 | Ethiopia | ETH | Multidimensional poverty index, children (population ages 0-17) (scale 0-1) | SI.POV.MDIM.17.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
593 | Ethiopia | ETH | Multidimensional poverty intensity (average share of deprivations experienced by the poor) | SI.POV.MDIM.IT | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
594 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Australia (current US$) | DC.DAC.AUSL.CD | 4739999.771118159 | 3799999.95231628 | 750000 | 1919999.95708466 | 1559999.9427795399 | 1539999.96185303 | 3119999.8855590797 | 1879999.99523163 | 1870000.00476837 | 1340000.0333786 | 1850000.02384186 | 10130000.1144409 | 4159999.8474121103 | 2329999.92370605 | 18819999.6948242 | 27920000.0762939 | 13630000.1144409 | 9939999.5803833 | 3880000.1144409203 | 5250000 | 3650000.09536743 | 1600000.02384186 | 1149999.97615814 | 1879999.99523163 | .. |
595 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Austria (current US$) | DC.DAC.AUTL.CD | 2450000.04768372 | 3210000.03814697 | 4860000.1335144 | 3759999.99046326 | 6960000.03814697 | 4300000.19073486 | 7570000.17166138 | 4300000.19073486 | 7639999.8664856 | 17590000.1525879 | 7179999.82833862 | 9750000 | 12659999.8474121 | 9710000.03814697 | 11869999.8855591 | 8399999.61853027 | 10630000.1144409 | 9670000.07629395 | 8069999.694824221 | 8579999.92370605 | 11369999.8855591 | 13489999.7711182 | 11550000.1907349 | 11859999.6566772 | .. |
596 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Belgium (current US$) | DC.DAC.BELL.CD | 6650000.09536743 | 7900000.09536743 | 2859999.89509583 | 8899999.61853027 | 13359999.6566772 | 1570000.05245209 | 7980000.01907349 | 9439999.5803833 | 5340000.15258789 | 6599999.90463257 | 13130000.1144409 | 8770000.45776367 | 6300000.19073486 | 4179999.8283386203 | 8399999.61853027 | 3259999.99046326 | 2519999.98092651 | 3359999.89509583 | 1779999.97138977 | 2009999.9904632599 | 3730000.01907349 | 3849999.90463257 | 5360000.1335144 | 3720000.02861023 | .. |
597 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Canada (current US$) | DC.DAC.CANL.CD | 13380000.1144409 | 10850000.3814697 | 14810000.4196167 | 10939999.5803833 | 12380000.1144409 | 6880000.11444092 | 38020000.4577637 | 59479999.5422363 | 64930000.305175796 | 62479999.5422363 | 90519996.6430664 | 152550003.05175802 | 87180000.3051758 | 140380004.882813 | 118639999.38964799 | 123370002.746582 | 131839996.337891 | 108120002.746582 | 103239997.86377 | 90669998.1689453 | 89319999.6948242 | 90559997.55859381 | 79459999.0844727 | 72970001.2207031 | .. |
598 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Czech Republic (current US$) | DC.DAC.CZEL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 769999.980926514 | 610000.014305115 | 500000 | 1210000.03814697 | 1029999.97138977 | 1220000.02861023 | 2930000.0667572 | 3099999.90463257 | 3589999.91416931 | 3619999.8855590797 | 3230000.01907349 | 3230000.01907349 | 3799999.95231628 | 5039999.96185303 | 5309999.94277954 | 5289999.96185303 | .. |
599 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Denmark (current US$) | DC.DAC.DNKL.CD | 3519999.98092651 | 3109999.89509583 | 4090000.1525878897 | 2559999.94277954 | 2750000 | 2680000.0667572 | 2970000.02861023 | 2619999.8855590797 | 4059999.94277954 | 5739999.771118159 | 6429999.82833862 | 7519999.98092651 | 15369999.8855591 | 7760000.228881841 | 21889999.3896484 | 8300000.19073486 | 12119999.8855591 | 16639999.389648398 | 6070000.17166138 | 17379999.1607666 | 31120000.8392334 | 25389999.3896484 | 97459999.0844727 | 53930000.3051758 | .. |
600 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, European Union institutions (current US$) | DC.DAC.CECL.CD | 40700000.762939505 | 115010002.13623 | 82800003.0517578 | 68989997.8637695 | 100000000 | 116550003.05175799 | 149139999.38964802 | 112650001.52587901 | 163470001.220703 | 194369995.117188 | 364760009.765625 | 447140014.64843804 | 202470001.220703 | 237559997.55859402 | 198779998.779297 | 226360000.61035198 | 120809997.558594 | 267850006.103516 | 155309997.55859402 | 333170013.42773396 | 212869995.117188 | 271000000 | 200910003.66210902 | 206949996.94824198 | .. |
601 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Finland (current US$) | DC.DAC.FINL.CD | 6630000.11444092 | 7000000 | 5940000.05722046 | 5659999.84741211 | 5050000.19073486 | 4579999.92370605 | 9159999.84741211 | 9060000.4196167 | 11079999.923706101 | 13210000.038146999 | 9979999.54223633 | 15989999.7711182 | 23489999.7711182 | 25639999.3896484 | 23649999.6185303 | 31129999.1607666 | 20639999.3896484 | 40889999.3896484 | 24750000 | 21709999.084472697 | 21170000.0762939 | 18860000.6103516 | 22920000.0762939 | 25840000.1525879 | .. |
602 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, France (current US$) | DC.DAC.FRAL.CD | 7570000.17166138 | 10520000.4577637 | 10529999.7329712 | 9409999.84741211 | 6610000.1335144 | 10180000.3051758 | 15560000.4196167 | 26250000 | 15189999.5803833 | 17350000.3814697 | 20049999.237060502 | 18739999.7711182 | 38270000.4577637 | 13300000.1907349 | 13189999.5803833 | 20680000.3051758 | 46599998.4741211 | 52409999.8474121 | 14010000.2288818 | 19530000.6866455 | 53060001.373291 | 16909999.8474121 | 56770000.4577637 | 73639999.3896484 | .. |
603 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Germany (current US$) | DC.DAC.DEUL.CD | 58299999.237060495 | 63490001.6784668 | 37459999.0844727 | 38630001.0681152 | 25879999.1607666 | 40610000.6103516 | 47610000.6103516 | 126089996.337891 | 49849998.4741211 | 56759998.3215332 | 96480003.3569336 | 98250000 | 79819999.6948242 | 96449996.9482422 | 101209999.084473 | 116839996.337891 | 85889999.3896484 | 58340000.1525879 | 49119998.9318848 | 132330001.831055 | 137339996.33789098 | 175110000.61035198 | 141630004.882813 | 447440002.441406 | .. |
604 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Greece (current US$) | DC.DAC.GRCL.CD | 109999.999403954 | 239999.994635582 | 159999.99642372102 | 1190000.0572204601 | 550000.011920929 | 230000.004172325 | 419999.986886978 | 1590000.0333786 | 1490000.0095367401 | 1169999.95708466 | 2430000.0667572 | 3109999.89509583 | 2230000.01907349 | 1389999.98569489 | 1100000.02384186 | 850000.023841858 | 90000.0035762787 | 90000.0035762787 | 70000.0002980232 | 9999.99977648258 | 50000.0007450581 | 70000.0002980232 | 79999.9982118607 | .. | .. |
605 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Hungary (current US$) | DC.DAC.HUNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 19999.9995529652 | .. | 119999.997317791 | 129999.995231628 | 170000.00178813902 | 129999.995231628 | 129999.995231628 | 29999.999329447703 | 59999.9986588955 | 90000.0035762787 | 70000.0002980232 | 490000.009536743 | 3089999.91416931 | 860000.014305115 | .. |
606 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Iceland (current US$) | DC.DAC.ISLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 280000.001192093 | 280000.001192093 | 189999.99761581398 | 180000.00715255702 | 189999.99761581398 | 419999.986886978 | 419999.986886978 | 360000.01430511504 | 479999.989271164 | 819999.992847443 | 360000.01430511504 | 230000.004172325 | .. |
607 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Ireland (current US$) | DC.DAC.IRLL.CD | 15890000.3433228 | 16709999.0844727 | 16760000.2288818 | 21629999.1607666 | 21090000.1525879 | 25299999.237060502 | 33380001.068115197 | 42439998.626709 | 44099998.4741211 | 50630001.0681152 | 58939998.626709 | 72669998.1689453 | 52470001.220703095 | 49229999.5422363 | 49520000.4577637 | 42659999.8474121 | 45770000.4577637 | 48270000.4577637 | 38779998.779296905 | 39229999.5422363 | 40619998.9318848 | 44020000.4577637 | 44479999.5422363 | 45220001.220703095 | .. |
608 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Italy (current US$) | DC.DAC.ITAL.CD | 31670000.0762939 | 46220001.220703095 | 18700000.762939498 | 25969999.3133545 | 13560000.4196167 | 49240001.6784668 | 47569999.6948242 | 11210000.038146999 | 86930000.3051758 | 105389999.38964799 | 75470001.2207031 | 65860000.61035161 | 53970001.220703095 | 18309999.4659424 | 24760000.2288818 | -3019999.98092651 | -18170000.0762939 | 10630000.1144409 | 18659999.8474121 | 19059999.4659424 | 21000000 | 40090000.1525879 | 19530000.6866455 | 22790000.915527303 | .. |
609 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Japan (current US$) | DC.DAC.JPNL.CD | 37330001.8310547 | 26079999.9237061 | 40380001.0681152 | 34029998.779296905 | 52389999.3896484 | 50529998.779296905 | 56529998.779296905 | 33330001.831054702 | 34169998.1689453 | 57849998.4741211 | 36029998.779296905 | 47119998.9318848 | 97760002.1362305 | 93889999.3896484 | 120569999.69482401 | 108669998.168945 | 150119995.117188 | 82769996.6430664 | 54200000.762939505 | 62610000.6103516 | 38900001.5258789 | 69410003.6621094 | 64449996.9482422 | 75230003.3569336 | .. |
610 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Korea, Rep. (current US$) | DC.DAC.KORL.CD | 460000.00834465 | 540000.021457672 | 639999.985694885 | 490000.009536743 | 500000 | 839999.973773956 | 1049999.95231628 | 2069999.9332428002 | 2369999.8855590797 | 2289999.96185303 | 3299999.95231628 | 4389999.8664856 | 4159999.8474121103 | 10199999.8092651 | 11609999.6566772 | 20440000.5340576 | 27340000.1525879 | 42909999.8474121 | 46020000.4577637 | 61590000.1525879 | 46950000.762939505 | 84540000.9155273 | 74470001.2207031 | 108620002.746582 | .. |
611 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Luxembourg (current US$) | DC.DAC.LUXL.CD | 560000.002384186 | 250000 | 460000.00834465 | 200000.00298023198 | 529999.971389771 | 670000.016689301 | 479999.989271164 | 439999.997615814 | 150000.005960464 | 1730000.01907349 | 980000.019073486 | 1429999.94754791 | 1629999.99523163 | 740000.009536743 | 1399999.97615814 | 769999.980926514 | 779999.971389771 | 879999.995231628 | 589999.973773956 | 1320000.05245209 | 720000.028610229 | 1070000.05245209 | 1639999.98569489 | 2049999.9523162802 | .. |
612 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Netherlands (current US$) | DC.DAC.NLDL.CD | 35439998.626709 | 36840000.1525879 | 31219999.3133545 | 25719999.3133545 | 44180000.3051758 | 34790000.9155273 | 57229999.5422363 | 57520000.4577637 | 58659999.8474121 | 49759998.3215332 | 50759998.3215332 | 113629997.253418 | 85900001.5258789 | 54250000 | 67900001.5258789 | 79339996.3378906 | 76650001.5258789 | 89949996.9482422 | 80480003.3569336 | 73849998.4741211 | 82370002.746582 | 78800003.0517578 | 97559997.55859381 | 108550003.05175799 | .. |
613 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, New Zealand (current US$) | DC.DAC.NZLL.CD | 180000.00715255702 | 59999.9986588955 | 209999.993443489 | 270000.010728836 | 180000.00715255702 | 790000.021457672 | 1279999.97138977 | 800000.011920929 | 1210000.03814697 | 159999.99642372102 | 59999.9986588955 | 340000.00357627904 | 400000.00596046395 | .. | 189999.99761581398 | 19999.9995529652 | 39999.9991059303 | 209999.993443489 | 239999.994635582 | 479999.989271164 | 740000.009536743 | 1429999.94754791 | 4449999.80926514 | 2740000.00953674 | .. |
614 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Norway (current US$) | DC.DAC.NORL.CD | 28420000.0762939 | 26719999.3133545 | 23930000.3051758 | 23569999.6948242 | 16250000 | 28479999.5422363 | 37180000.3051758 | 34040000.9155273 | 38069999.6948242 | 41799999.237060495 | 34139999.3896484 | 37279998.779296905 | 37810001.373291 | 32560001.373291 | 29090000.1525879 | 39150001.5258789 | 61069999.6948242 | 59470001.220703095 | 48340000.1525879 | 52590000.1525879 | 60049999.237060495 | 63970001.220703095 | 79330001.8310547 | 78169998.1689453 | .. |
615 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Poland (current US$) | DC.DAC.POLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 50000.0007450581 | 159999.99642372102 | 449999.988079071 | 270000.010728836 | 100000.00149011599 | 159999.99642372102 | 389999.98569488496 | 270000.010728836 | 23479999.5422363 | 27290000.915527303 | 42290000.9155273 | 8619999.88555908 | 219999.998807907 | 400000.00596046395 | 810000.002384186 | .. |
616 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Portugal (current US$) | DC.DAC.PRTL.CD | .. | .. | .. | .. | .. | 2150000.09536743 | 819999.992847443 | 9999.99977648258 | 79999.9982118607 | 129999.995231628 | 129999.995231628 | 209999.993443489 | 19999.9995529652 | .. | 19999.9995529652 | 39999.9991059303 | 39999.9991059303 | 50000.0007450581 | 39999.9991059303 | 39999.9991059303 | 39999.9991059303 | 39999.9991059303 | 50000.0007450581 | 39999.9991059303 | .. |
617 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Slovak Republic (current US$) | DC.DAC.SVKL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 59999.9986588955 | 29999.999329447703 | 19999.9995529652 | 19999.9995529652 | 19999.9995529652 | 9999.99977648258 | .. | 209999.993443489 | 9999.99977648258 | 189999.99761581398 | 270000.010728836 | .. |
618 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Slovenia (current US$) | DC.DAC.SVNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29999.999329447703 | 59999.9986588955 | 9999.99977648258 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
619 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Spain (current US$) | DC.DAC.ESPL.CD | 970000.028610229 | 330000.013113022 | 689999.997615814 | -349999.99403953605 | -1110000.01430511 | 1179999.94754791 | 1799999.95231628 | 810000.002384186 | 4480000.01907349 | 9720000.26702881 | 27079999.9237061 | 60540000.9155273 | 94000000 | 39459999.0844727 | 38819999.6948242 | 14739999.7711182 | 8220000.26702881 | 7960000.03814697 | 6840000.15258789 | 7630000.11444092 | 8250000 | 8069999.694824221 | 7260000.228881841 | 7780000.20980835 | .. |
620 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Sweden (current US$) | DC.DAC.SWEL.CD | 35950000.762939505 | 30940000.5340576 | 18879999.1607666 | 20719999.3133545 | 20620000.8392334 | 21309999.4659424 | 28629999.1607666 | 50759998.3215332 | 68370002.746582 | 41529998.779296905 | 44720001.220703095 | 46939998.626709 | 44599998.4741211 | 39419998.1689453 | 40669998.1689453 | 27229999.5422363 | 29790000.915527303 | 35209999.0844727 | 34340000.1525879 | 47130001.0681152 | 79529998.7792969 | 78720001.2207031 | 76930000.3051758 | 57919998.1689453 | .. |
621 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Switzerland (current US$) | DC.DAC.CHEL.CD | 2390000.10490417 | 4550000.19073486 | 2960000.03814697 | 3589999.91416931 | 2259999.99046326 | 2119999.8855590797 | 5300000.19073486 | 3240000.00953674 | 2650000.09536743 | 2759999.99046326 | 2430000.0667572 | 3150000.09536743 | 5400000.09536743 | 6230000.01907349 | 11340000.1525879 | 9539999.96185303 | 9949999.80926514 | 14210000.038146999 | 19780000.6866455 | 14149999.6185303 | 16799999.237060502 | 15739999.7711182 | 15640000.3433228 | 19219999.3133545 | .. |
622 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, Total (current US$) | DC.DAC.TOTL.CD | 414870001.62899494 | 480630004.3575461 | 408480001.822114 | 448970000.9971858 | 467579999.08924097 | 606609996.3635206 | 1183519985.3777883 | 1139459990.3319042 | 1351029987.4488268 | 1221409988.1239243 | 1610330024.2275 | 2292219998.702408 | 2020739998.5697117 | 2094390012.9515684 | 2128510024.1284814 | 2024970006.8477552 | 2034410015.854986 | 2181890052.2496567 | 2009669987.5649073 | 2382350040.541962 | 2419460060.4362817 | 2332720001.7217555 | 2360659986.3506856 | 2553819995.0382113 | .. |
623 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, United Kingdom (current US$) | DC.DAC.GBRL.CD | 21559999.4659424 | 13029999.7329712 | 12039999.961853001 | 11350000.3814697 | 27610000.6103516 | 43659999.8474121 | 62919998.1689453 | 147130004.882813 | 75480003.3569336 | 164610000.61035198 | 291070007.324219 | 253679992.67578098 | 342920013.42773396 | 406950012.207031 | 552250000 | 421049987.792969 | 515059997.558594 | 529650024.414063 | 517619995.117188 | 451170013.42773396 | 419950012.207031 | 402079986.57226604 | 382250000 | 325619995.11718804 | .. |
624 | Ethiopia | ETH | Net bilateral aid flows from DAC donors, United States (current US$) | DC.DAC.USAL.CD | 60000000 | 53229999.5422363 | 77349998.4741211 | 129820007.324219 | 94419998.1689453 | 156429992.67578098 | 567799987.792969 | 402299987.792969 | 608609985.351563 | 315779998.779297 | 371730010.986328 | 811369995.117188 | 726039978.027344 | 802630004.882813 | 659280029.296875 | 693400024.414063 | 678780029.296875 | 664840026.855469 | 746429992.675781 | 874890014.648438 | 1026680053.71094 | 821320007.324219 | 865979980.46875 | 794179992.675781 | .. |
625 | Ethiopia | ETH | Net migration | SM.POP.NETM | -155577 | .. | .. | .. | .. | -150001 | .. | .. | .. | .. | -50132 | .. | .. | .. | .. | 399997 | .. | .. | .. | .. | 150002 | .. | .. | .. | .. |
626 | Ethiopia | ETH | Net ODA provided to the least developed countries (% of GNI) | DC.ODA.TLDC.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
627 | Ethiopia | ETH | Net ODA provided, to the least developed countries (current US$) | DC.ODA.TLDC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
628 | Ethiopia | ETH | Net ODA provided, total (% of GNI) | DC.ODA.TOTL.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
629 | Ethiopia | ETH | Net ODA provided, total (constant 2020 US$) | DC.ODA.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
630 | Ethiopia | ETH | Net ODA provided, total (current US$) | DC.ODA.TOTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
631 | Ethiopia | ETH | Net ODA received (% of central government expense) | DT.ODA.ODAT.XP.ZS | 54.374211477335635 | 52.767673678627894 | 46.00160612346195 | .. | 92.38322001431992 | 97.84504988349778 | 119.25690294472686 | 111.7457945238282 | 104.74243957849345 | 139.91812910561055 | 171.91956433891428 | 95.13888910440929 | 96.99672425090776 | 92.31777881480886 | 103.31271677569968 | 88.44729983165924 | 79.79252273296632 | 67.46504614127798 | 48.31827550157612 | 54.467272713047755 | 44.907911917109274 | 54.198218268596854 | 50.242818306730065 | 58.54010304852266 | .. |
632 | Ethiopia | ETH | Net ODA received (% of GNI) | DT.ODA.ODAT.GN.ZS | 6.8169082217874895 | 8.517235155694202 | 8.410840979053026 | 8.405986943046077 | 13.491327693194952 | 16.98992838846462 | 18.944138644348715 | 18.180000588021255 | 15.601008522663431 | 13.347909679925534 | 13.216588763144916 | 12.243025621034844 | 11.803280990517681 | 11.584554263989657 | 10.958379420163833 | 7.50495274404601 | 8.166645494695146 | 6.462309057798212 | 5.034757212547758 | 5.513373432482775 | 5.074417512545543 | 5.8892479206910355 | 4.9064338852955975 | 4.952733175841793 | .. |
633 | Ethiopia | ETH | Net ODA received (% of gross capital formation) | DT.ODA.ODAT.GI.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34.05587570201147 | 20.18516373656035 | 23.908674842958533 | 16.9621529238885 | 12.328837714599535 | 14.713641485550214 | 13.121123179098376 | 16.88188484293703 | 13.82791354481379 | 16.10437323108631 | .. |
634 | Ethiopia | ETH | Net ODA received (% of imports of goods, services and primary income) | DT.ODA.ODAT.MP.ZS | 39.61351799302582 | 35.12685217581307 | 33.78782940420277 | 41.111650916065926 | 50.2635338664941 | 63.97851430402316 | 61.250557465030695 | 48.32968928339713 | 39.02949649031742 | 38.28694519765597 | 37.55046926654895 | 34.42308523729135 | 42.08342985631411 | 34.60095854598852 | 29.46600583512751 | 22.78283597563909 | 26.98091191724489 | 19.488397925474203 | 16.055257617140473 | 19.992765253087903 | 20.821307805384485 | 24.3030352541771 | 23.510553108604384 | 29.712360471614918 | .. |
635 | Ethiopia | ETH | Net ODA received per capita (current US$) | DT.ODA.ODAT.PC.ZS | 9.537633622301536 | 10.562534483488392 | 9.997822576578079 | 10.385835734052007 | 16.19145150007199 | 18.886520065689233 | 22.46289293666196 | 24.65398947455484 | 25.26801878332024 | 25.921399622128035 | 32.30952929890151 | 39.99518260814444 | 44.86195020925682 | 39.42447980647663 | 38.76073533781977 | 34.976119253711396 | 40.703546271953726 | 36.53587696970233 | 32.118663176649584 | 39.408626678866455 | 38.766474330066735 | 45.23356878999163 | 41.729238778180445 | 46.115996195508274 | .. |
636 | Ethiopia | ETH | Net official aid received (constant 2020 US$) | DT.ODA.OATL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
637 | Ethiopia | ETH | Net official aid received (current US$) | DT.ODA.OATL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
638 | Ethiopia | ETH | Net official development assistance and official aid received (constant 2020 US$) | DT.ODA.ALLD.KD | 807619995.117188 | 944070007.324219 | 910330017.089844 | 1027739990.23438 | 1659439941.40625 | 1914439941.40625 | 2096000000 | 2158750000 | 2250750000 | 2240330078.125 | 2628270019.53125 | 3288560058.59375 | 3889870117.1875 | 3519469970.70313 | 3347219970.70313 | 3165139892.57813 | 3737270019.53125 | 3407840087.89063 | 3364750000 | 4323910156.25 | 4291939941.40625 | 4941029785.15625 | 4893290039.0625 | .. | .. |
639 | Ethiopia | ETH | Net official development assistance and official aid received (current US$) | DT.ODA.ALLD.CD | 578909973.144531 | 660239990.234375 | 643289978.027344 | 687799987.792969 | 1103599975.58594 | 1324739990.23438 | 1621160034.17969 | 1830300048.82813 | 1929119995.11719 | 2034550048.82813 | 2606550048.82813 | 3316250000 | 3823760009.76563 | 3455159912.10938 | 3493889892.57813 | 3243229980.46875 | 3882540039.0625 | 3583959960.9375 | 3238699951.17188 | 4082870117.1875 | 4124750000 | 4940609863.28125 | 4676959960.9375 | 5301660156.25 | .. |
640 | Ethiopia | ETH | Net official development assistance received (constant 2020 US$) | DT.ODA.ODAT.KD | 808179992.675781 | 943890014.648438 | 913500000 | 1033489990.23438 | 1675380004.88281 | 1930729980.46875 | 2122540039.0625 | 2185879882.8125 | 2277469970.70313 | 2263550048.82813 | 2655169921.875 | 3329120117.1875 | 3939850097.65625 | 3572209960.9375 | 3398080078.125 | 3212050048.82813 | 3789570068.35938 | 3453010009.76563 | 3410110107.42188 | 4374729980.46875 | 4346399902.34375 | 4987029785.15625 | 4798839843.75 | 5301660156.25 | .. |
641 | Ethiopia | ETH | Net official development assistance received (current US$) | DT.ODA.ODAT.CD | 578909973.144531 | 660239990.234375 | 643289978.027344 | 687799987.792969 | 1103599975.58594 | 1324739990.23438 | 1621160034.17969 | 1830300048.82813 | 1929119995.11719 | 2034550048.82813 | 2606550048.82813 | 3316250000 | 3823760009.76563 | 3455159912.10938 | 3493889892.57813 | 3243229980.46875 | 3882540039.0625 | 3583959960.9375 | 3238699951.17188 | 4082870117.1875 | 4124750000 | 4940609863.28125 | 4676959960.9375 | 5301660156.25 | .. |
642 | Ethiopia | ETH | Net official flows from UN agencies, FAO (current US$) | DT.NFL.FAOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 370575.815439224 | .. | .. | .. | .. | 620500.028133392 | 854004.02545929 | .. | .. |
643 | Ethiopia | ETH | Net official flows from UN agencies, IAEA (current US$) | DT.NFL.IAEA.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1159999.9666214 | 910000.026226044 | 680000.007152557 | 920000.016689301 | 720000.028610229 | 370000.00476837205 | 759999.990463257 | 1210000.03814697 | 860000.014305115 | 667698.264122009 | 773694.87285614 | 670375.406742096 | 327601.999044418 | 417469.084262848 | 459020.584821701 | .. |
644 | Ethiopia | ETH | Net official flows from UN agencies, IFAD (current US$) | DT.NFL.IFAD.CD | -400000.00596046395 | -620000.004768372 | 899999.976158142 | 3140000.10490417 | 3930000.0667572 | 5050000.19073486 | 8680000.30517578 | 8000000 | 12710000.038146999 | 16299999.2370605 | 29579999.9237061 | 3809999.94277954 | -1090000.0333786 | 13369999.8855591 | 8210000.038146971 | 62200000.762939505 | 55159999.8474121 | 31530000.6866455 | 22876054.7637939 | 33966331.4819336 | 53801502.2277832 | 41780162.8112793 | 34574302.6733398 | 15740157.127380399 | .. |
645 | Ethiopia | ETH | Net official flows from UN agencies, ILO (current US$) | DT.NFL.ILOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 579415.798187256 | 477077.394723892 | 328249.990940094 | 440910.01152992196 | 470120.012760162 | 370110.00514030503 | 1615723.3715057399 | 4330810.07003784 | 2044433.83216858 | .. |
646 | Ethiopia | ETH | Net official flows from UN agencies, UNAIDS (current US$) | DT.NFL.UNAI.CD | .. | .. | .. | .. | .. | .. | .. | .. | 750000 | 769999.980926514 | 2329999.92370605 | 1590000.0333786 | 1990000.0095367401 | 1600000.02384186 | 1750000 | 1770872.47371674 | 1751628.39889526 | 1261555.07564545 | 882627.010345459 | 820571.8994140631 | 774900.019168854 | 409196.70462608297 | 1131139.9936676002 | .. | .. |
647 | Ethiopia | ETH | Net official flows from UN agencies, UNDP (current US$) | DT.NFL.UNDP.CD | 24579999.9237061 | 15909999.8474121 | 7670000.07629395 | 18840000.1525879 | 17000000 | 13329999.923706101 | 10649999.6185303 | 10970000.2670288 | 12060000.4196167 | 17170000.0762939 | 9460000.03814697 | 21940000.5340576 | 17350000.3814697 | 17110000.6103516 | 15619999.8855591 | 15512259.4833374 | 13857172.9660034 | 15166576.385498 | 11319893.8369751 | 10847601.890564 | 10108265.87677 | 9257479.66766357 | 10823478.6987305 | 11373818.397521999 | .. |
648 | Ethiopia | ETH | Net official flows from UN agencies, UNECE (current US$) | DT.NFL.UNEC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
649 | Ethiopia | ETH | Net official flows from UN agencies, UNEP (current US$) | DT.NFL.UNEP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
650 | Ethiopia | ETH | Net official flows from UN agencies, UNFPA (current US$) | DT.NFL.UNFP.CD | 5789999.96185303 | 1820000.05245209 | 870000.004768372 | 2960000.03814697 | 3329999.92370605 | 3799999.95231628 | 4539999.96185303 | 4599999.90463257 | 3730000.01907349 | 4269999.98092651 | 3440000.05722046 | 5429999.82833862 | 6099999.90463257 | 5039999.96185303 | 6059999.94277954 | 5661562.9196167 | 5716928.0052185105 | 6527814.8651123 | 7131953.23944092 | 6444245.33843994 | 4796517.37213135 | 4402910.23254395 | 5043574.81002808 | 5166850.09002686 | .. |
651 | Ethiopia | ETH | Net official flows from UN agencies, UNHCR (current US$) | DT.NFL.UNCR.CD | 17690000.5340576 | 17579999.9237061 | 16959999.084472697 | 16299999.2370605 | 18379999.1607666 | 19149999.6185303 | 14390000.3433228 | 8840000.15258789 | 2670000.07629395 | 1549999.95231628 | 2839999.91416931 | 4869999.88555908 | 6159999.84741211 | 4440000.05722046 | .. | .. | .. | .. | .. | .. | .. | 1259900.09307861 | 3855360.26954651 | .. | .. |
652 | Ethiopia | ETH | Net official flows from UN agencies, UNICEF (current US$) | DT.NFL.UNCF.CD | 12210000.038146999 | 12779999.7329712 | 14359999.6566772 | 13449999.8092651 | 19379999.1607666 | 14010000.2288818 | 14560000.4196167 | 18620000.8392334 | 24090000.1525879 | 25829999.9237061 | 51409999.8474121 | 45849998.4741211 | 35930000.3051758 | 42740001.6784668 | 40020000.4577637 | 29852664.947509803 | 43873279.5715332 | 40216514.5874023 | 41178203.5827637 | 38996749.8779297 | 43286861.4196777 | 38733085.6323242 | 40898998.260497995 | 35014999.3896484 | .. |
653 | Ethiopia | ETH | Net official flows from UN agencies, UNIDIR (current US$) | DT.NFL.UNID.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
654 | Ethiopia | ETH | Net official flows from UN agencies, UNPBF (current US$) | DT.NFL.UNPB.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 24492.2991842031 | .. | 1136139.98889923 | .. |
655 | Ethiopia | ETH | Net official flows from UN agencies, UNRWA (current US$) | DT.NFL.UNRW.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
656 | Ethiopia | ETH | Net official flows from UN agencies, UNTA (current US$) | DT.NFL.UNTA.CD | 2400000.09536743 | 1779999.97138977 | 2720000.02861023 | 4440000.05722046 | 2269999.98092651 | 3799999.95231628 | 4300000.19073486 | 4500000 | 4840000.15258789 | 3150000.09536743 | 3769999.98092651 | 1139999.98569489 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
657 | Ethiopia | ETH | Net official flows from UN agencies, UNWTO (current US$) | DT.NFL.UNWT.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
658 | Ethiopia | ETH | Net official flows from UN agencies, WFP (current US$) | DT.NFL.WFPG.CD | 22309999.4659424 | 16129999.160766602 | 19860000.6103516 | 36020000.4577637 | 27309999.4659424 | 23530000.6866455 | 15229999.5422363 | 9829999.92370605 | 14079999.923706101 | 15970000.2670288 | 12270000.4577637 | 15930000.3051758 | 16569999.6948242 | 3720000.02861023 | 28059999.4659424 | 23435207.366943397 | 18907915.1153564 | 26490539.5507813 | 23967273.7121582 | 16280845.6420898 | 12729060.1730347 | .. | 7503250.12207031 | 14844142.9138184 | .. |
659 | Ethiopia | ETH | Net official flows from UN agencies, WHO (current US$) | DT.NFL.WHOL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2880000.1144409203 | 1911525.84552765 | 3375506.16264343 | 2368910.07423401 | 3702135.56289673 | 2965979.33769226 | 3568063.25912476 | 4047751.90353394 | 4542177.20031738 | 2719916.82052612 | .. |
660 | Ethiopia | ETH | Number of surgical procedures (per 100,000 population) | SH.SGR.PROC.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 43 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
661 | Ethiopia | ETH | Nurses and midwives (per 1,000 people) | SH.MED.NUMW.P3 | .. | .. | .. | .. | .. | .. | 0.2154 | 0.2094 | 0.2464 | 0.2274 | 0.2249 | 0.2022 | 0.2521 | .. | .. | .. | .. | .. | .. | .. | 0.8286 | 0.7135 | .. | .. | .. |
662 | Ethiopia | ETH | Out-of-pocket expenditure (% of current health expenditure) | SH.XPD.OOPC.CH.ZS | .. | .. | .. | 35.95730209 | 34.5539856 | 37.46262741 | 34.4589386 | 34.86631393 | 31.3402977 | 38.77532959 | 36.99623489 | 38.47733307 | 41.53925705 | 42.29020691 | 46.53787994 | 42.16745377 | 42.40406799 | 38.47408676 | 36.74348068 | 35.43159103 | 34.40161514 | 35.44364929 | 37.87532043 | .. | .. |
663 | Ethiopia | ETH | Out-of-pocket expenditure per capita (current US$) | SH.XPD.OOPC.PC.CD | .. | .. | .. | 1.93611907 | 1.94087127 | 1.9702664 | 2.01286322 | 2.05036624 | 2.08525903 | 3.35863905 | 4.43300548 | 5.17589472 | 6.49592499 | 7.06493892 | 7.03241875 | 8.71381735 | 8.43147671 | 8.56892023 | 8.78765915 | 8.88468168 | 8.57453864 | 8.61071131 | 10.12869588 | .. | .. |
664 | Ethiopia | ETH | Out-of-pocket expenditure per capita, PPP (current international $) | SH.XPD.OOPC.PP.CD | .. | .. | .. | 7.57553407 | 8.47537171 | 9.18644463 | 8.50859709 | 8.60119489 | 8.23867175 | 12.30095559 | 14.65981471 | 14.33712508 | 17.91756439 | 23.77627309 | 23.6009055 | 23.23102668 | 22.18001045 | 23.49157652 | 23.28179075 | 23.96720148 | 24.01646704 | 25.26542953 | 28.44970125 | .. | .. |
665 | Ethiopia | ETH | Part time employment, female (% of total female employment) | SL.TLF.PART.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 78.7099990844727 | .. | .. | .. | .. | .. | .. | .. | 66.4700012207031 | .. | .. | .. | .. | .. | .. | .. | .. |
666 | Ethiopia | ETH | Part time employment, male (% of total male employment) | SL.TLF.PART.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 51.4599990844727 | .. | .. | .. | .. | .. | .. | .. | 42.9099998474121 | .. | .. | .. | .. | .. | .. | .. | .. |
667 | Ethiopia | ETH | Part time employment, total (% of total employment) | SL.TLF.PART.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 64.3300018310547 | .. | .. | .. | .. | .. | .. | .. | 53.7700004577637 | .. | .. | .. | .. | .. | .. | .. | .. |
668 | Ethiopia | ETH | Physicians (per 1,000 people) | SH.MED.PHYS.ZS | 0.023 | 0.021 | 0.02 | 0.021 | 0.028 | 0.029 | 0.0268 | 0.0269 | 0.0321 | 0.0269 | 0.0224 | 0.0251 | 0.0252 | .. | .. | .. | .. | .. | .. | .. | .. | 0.0769 | .. | .. | .. |
669 | Ethiopia | ETH | Poverty gap at $1.90 a day (2011 PPP) (%) | SI.POV.GAPS | .. | .. | 17.4 | .. | .. | .. | .. | 9.2 | .. | .. | .. | .. | .. | 9.8 | .. | .. | .. | .. | 8.9 | .. | .. | .. | .. | .. | .. |
670 | Ethiopia | ETH | Poverty gap at $3.20 a day (2011 PPP) (%) | SI.POV.LMIC.GP | .. | .. | 41.7 | .. | .. | .. | .. | 30.5 | .. | .. | .. | .. | .. | 29.3 | .. | .. | .. | .. | 25.7 | .. | .. | .. | .. | .. | .. |
671 | Ethiopia | ETH | Poverty gap at $5.50 a day (2011 PPP) (%) | SI.POV.UMIC.GP | .. | .. | 63.9 | .. | .. | .. | .. | 55.6 | .. | .. | .. | .. | .. | 53.4 | .. | .. | .. | .. | 49.6 | .. | .. | .. | .. | .. | .. |
672 | Ethiopia | ETH | Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) | SI.POV.DDAY | .. | .. | 57.8 | .. | .. | .. | .. | 38.5 | .. | .. | .. | .. | .. | 35.6 | .. | .. | .. | .. | 30.8 | .. | .. | .. | .. | .. | .. |
673 | Ethiopia | ETH | Poverty headcount ratio at $3.20 a day (2011 PPP) (% of population) | SI.POV.LMIC | .. | .. | 89.2 | .. | .. | .. | .. | 79.8 | .. | .. | .. | .. | .. | 74.6 | .. | .. | .. | .. | 68.9 | .. | .. | .. | .. | .. | .. |
674 | Ethiopia | ETH | Poverty headcount ratio at $5.50 a day (2011 PPP) (% of population) | SI.POV.UMIC | .. | .. | 97.5 | .. | .. | .. | .. | 95.8 | .. | .. | .. | .. | .. | 93.6 | .. | .. | .. | .. | 90.2 | .. | .. | .. | .. | .. | .. |
675 | Ethiopia | ETH | Poverty headcount ratio at national poverty lines (% of population) | SI.POV.NAHC | .. | .. | 44.2 | .. | .. | .. | .. | 38.7 | .. | .. | .. | .. | .. | 29.6 | .. | .. | .. | .. | 23.5 | .. | .. | .. | .. | .. | .. |
676 | Ethiopia | ETH | PPP conversion factor, GDP (LCU per international $) | PA.NUS.PPP | 2.0227443612494 | 1.99722781441452 | 2.01324928727572 | 2.10251672023376 | 1.93785097318674 | 1.83901140504973 | 2.03367930187939 | 2.05797930852225 | 2.19246350211203 | 2.37253792980336 | 2.70792044034746 | 3.46233123889768 | 4.27098503785818 | 4.28123102942055 | 5.03550291061401 | 6.64094877243042 | 7.08069944381714 | 7.14422369003296 | 7.76668500900269 | 8.05592060089111 | 8.52085494995117 | 9.35250008459928 | 10.3697827950048 | 12.116709373811 | 14.1668407806467 |
677 | Ethiopia | ETH | PPP conversion factor, private consumption (LCU per international $) | PA.NUS.PRVT.PP | 2.00984346786234 | 1.99683118808889 | 2.1092573860842 | 2.05387394115432 | 1.83287871020799 | 1.81644291551905 | 2.01899112483323 | 2.03177501331596 | 2.16102431348011 | 2.35097775868675 | 2.67984844856645 | 3.72551418089792 | 4.05599447979683 | 4.31574803632374 | 5.57474660873413 | 6.73075819015503 | 7.24770784378052 | 7.36900234222412 | 7.87940168380737 | 8.02281379699707 | 8.49641704559326 | 9.44112217200322 | 10.7391135623298 | 12.7677043595809 | 15.4678380013926 |
678 | Ethiopia | ETH | Price level ratio of PPP conversion factor (GDP) to market exchange rate | PA.NUS.PPPC.RF | 0.3112680600223747 | 0.2902103769855449 | 0.2680436814863359 | 0.2580376677058161 | 0.23269662734296453 | 0.21527285343623562 | 0.23701174778618844 | 0.2387585484682696 | 0.253417113841605 | 0.273305524750125 | 0.3079281828914555 | 0.37454903060338385 | 0.40992274094041464 | 0.33211007908002094 | 0.3123761110802736 | 0.3848709807261907 | 0.3891734422957393 | 0.3745294251191579 | 0.3864868433389742 | 0.3816904562653623 | 0.38016279998175984 | 0.3582207921112631 | 0.3696338799539748 | 0.38653489564586724 | 0.36310057029105014 |
679 | Ethiopia | ETH | Proportion of people living below 50 percent of median income (%) | SI.DST.50MD | .. | .. | 6.1 | .. | .. | .. | .. | 5.2 | .. | .. | .. | .. | .. | 9.4 | .. | .. | .. | .. | 12.4 | .. | .. | .. | .. | .. | .. |
680 | Ethiopia | ETH | Proportion of seats held by women in national parliaments (%) | SG.GEN.PARL.ZS | 2.04841713221601 | 2.04841713221601 | 2.02578268876611 | 7.69230769230769 | 7.6782449725777004 | 7.6782449725777004 | 7.6782449725777004 | 7.6782449725777004 | 21.4285714285714 | 21.9281663516068 | 21.9281663516068 | 21.9281663516068 | 21.9281663516068 | 27.7879341864717 | 27.7879341864717 | 27.7879341864717 | 27.7879341864717 | 27.7879341864717 | 38.7568555758684 | 38.7568555758684 | 38.7568555758684 | 38.7568555758684 | 38.7568555758684 | 38.7568555758684 | 42.5882352941177 |
681 | Ethiopia | ETH | Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day) | SG.TIM.UWRK.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 19.30556 | .. | .. | .. | .. | .. | .. | .. | .. |
682 | Ethiopia | ETH | Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day) | SG.TIM.UWRK.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.59722 | .. | .. | .. | .. | .. | .. | .. | .. |
683 | Ethiopia | ETH | Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of ever-partnered women ages 15-49) | SG.VAW.1549.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 19.8 | .. | .. | .. | .. | .. |
684 | Ethiopia | ETH | Ratio of female to male labor force participation rate (%) (modeled ILO estimate) | SL.TLF.CACT.FM.ZS | 76.86797407967283 | 77.70426028037508 | 78.52822667320359 | 79.33701120360882 | 80.13431962524449 | 80.91790027936469 | 81.6870623270457 | 82.44178072195882 | 83.1833312019323 | 83.28194880343355 | 83.38387920627798 | 83.48785678246877 | 83.5959494521238 | 83.70708406610076 | 83.82146783787644 | 83.9380093150107 | 84.05916972764618 | 84.47855431405766 | 84.90349066830282 | 85.2547347048067 | 85.62366151257378 | 85.99819678123085 | 86.36185021087564 | 84.44573870666011 | 85.41856125958034 |
685 | Ethiopia | ETH | Ratio of female to male labor force participation rate (%) (national estimate) | SL.TLF.CACT.FM.NE.ZS | .. | .. | 68.33061237730217 | .. | .. | .. | .. | .. | 83.18318081333356 | .. | .. | .. | .. | .. | .. | .. | 84.05928675734246 | .. | .. | .. | .. | .. | .. | .. | .. |
686 | Ethiopia | ETH | Refugee population by country or territory of asylum | SM.POP.REFG | 323064 | 262158 | 257683 | 197960 | 152554 | 132939 | 130274 | 115979 | 100813 | 96975 | 85179 | 83573 | 121880 | 154288 | 288839 | 376388 | 433933 | 659520 | 736081 | 791631 | 889412 | 903226 | 733123 | 800454 | 821283 |
687 | Ethiopia | ETH | Refugee population by country or territory of origin | SM.POP.REFG.OR | 84386 | 70663 | 71040 | 66396 | 58980 | 61235 | 62674 | 63153 | 65447 | 74007 | 59845 | 63863 | 62877 | 68838 | 70601 | 74964 | 77109 | 86857 | 85839 | 83958 | 87448 | 92232 | 93467 | 151426 | 149125 |
688 | Ethiopia | ETH | Self-employed, female (% of female employment) (modeled ILO estimate) | SL.EMP.SELF.FE.ZS | 91.2099990844727 | 91.6900024414063 | 91.9400024414063 | 92.5199966430664 | 92.2600021362305 | 92.5400009155273 | 93.1399993896484 | 93.0299987792969 | 93.1999969482422 | 93.0699996948242 | 92.6900024414063 | 92.629997253418 | 92.4700012207031 | 92.0199966430664 | 91.5800018310547 | 91.2200012207031 | 90.879997253418 | 90.2699966430664 | 89.5400009155273 | 88.8300018310547 | 88.0999984741211 | 87.3000030517578 | 86.620002746582 | .. | .. |
689 | Ethiopia | ETH | Self-employed, male (% of male employment) (modeled ILO estimate) | SL.EMP.SELF.MA.ZS | 89.4899978637695 | 89.2799987792969 | 88.9100036621094 | 89 | 89.1399993896484 | 89.2200012207031 | 89.5199966430664 | 89.4499969482422 | 89.5400009155273 | 89.1699981689453 | 88.7900009155273 | 88.4400024414063 | 88.0599975585938 | 87.4700012207031 | 86.8899993896484 | 86.4599990844727 | 85.9199981689453 | 85.1900024414063 | 84.4800033569336 | 83.6100006103516 | 82.9700012207031 | 82.4599990844727 | 82.0299987792969 | .. | .. |
690 | Ethiopia | ETH | Self-employed, total (% of total employment) (modeled ILO estimate) | SL.EMP.SELF.ZS | 90.2399978637695 | 90.3399963378906 | 90.2399978637695 | 90.5599975585938 | 90.5299987792969 | 90.7099990844727 | 91.1500015258789 | 91.0699996948242 | 91.2099990844727 | 90.9499969482422 | 90.5699996948242 | 90.3499984741211 | 90.0699996948242 | 89.5500030517578 | 89.0299987792969 | 88.629997253418 | 88.1800003051758 | 87.5100021362305 | 86.8000030517578 | 86.0100021362305 | 85.3399963378906 | 84.6900024414063 | 84.1500015258789 | .. | .. |
691 | Ethiopia | ETH | Services, value added (annual % growth) | NV.SRV.TOTL.KD.ZG | 4.396839696733721 | 6.483649734630646 | 8.113166809219962 | 10.884424742147928 | 4.540421243458212 | 5.63736351870925 | 8.467541947973075 | 5.079107217654325 | 12.316710813960924 | 12.84491057397905 | 15.756621458216785 | 16.400398521781185 | 14.682129516412147 | 16.73739950868662 | 13.002182953231852 | 9.908847914735901 | 9.05024917178406 | 12.865554089525034 | 11.105243189877442 | 11.214100077226519 | 7.533163585452158 | 8.484738704565615 | 11.245579756241938 | 5.287522802301851 | 6.271380022048007 |
692 | Ethiopia | ETH | Services, value added (constant 2015 US$) | NV.SRV.TOTL.KD | 4093884580.7547746 | 4359317717.510966 | 4712996435.676512 | 5225978985.817836 | 5463260445.868571 | 5771244297.176039 | 6259926828.959424 | 6577875224.348982 | 7388053093.435229 | 8337041906.445077 | 9650678040.456528 | 11233427699.145422 | 12882734103.06647 | 15038968777.53852 | 16994363012.273495 | 18678308597.237804 | 20368742066.362587 | 22989293594.266304 | 25542310555.544495 | 28406650823.279247 | 30546570298.945065 | 33138366972.017 | 36864968459.77131 | 38814212073.143105 | 41248398814.813545 |
693 | Ethiopia | ETH | Services, value added per worker (constant 2015 US$) | NV.SRV.EMPL.KD | 960.0034149352023 | 999.1468782835229 | 1039.4401679346 | 1138.7196593221488 | 1173.7054448735857 | 1244.9459708017087 | 1368.8350380032023 | 1398.7511552180736 | 1555.1342831013205 | 1631.7874126349661 | 1751.7823074190965 | 1893.5613141410201 | 2023.1243374598312 | 2177.414384958036 | 2269.7304174976252 | 2310.211648210676 | 2321.6818237722437 | 2453.9795540753234 | 2560.845951882007 | 2687.5408034991397 | 2726.1682620701536 | 2803.984132940252 | 2951.2985961502536 | .. | .. |
694 | Ethiopia | ETH | Share of youth not in education, employment or training, female (% of female youth population) | SL.UEM.NEET.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 15.1300001144409 | .. | .. | .. | .. | .. | .. | .. | .. |
695 | Ethiopia | ETH | Share of youth not in education, employment or training, male (% of male youth population) | SL.UEM.NEET.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.65999984741211 | .. | .. | .. | .. | .. | .. | .. | .. |
696 | Ethiopia | ETH | Share of youth not in education, employment or training, total (% of youth population) | SL.UEM.NEET.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.4799995422363 | .. | .. | .. | .. | .. | .. | .. | .. |
697 | Ethiopia | ETH | Specialist surgical workforce (per 100,000 population) | SH.MED.SAOP.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.67 | .. | .. | .. | 0.56 | .. | 0.54 | .. | .. | .. | .. | .. |
698 | Ethiopia | ETH | Survey mean consumption or income per capita, bottom 40% of population (2011 PPP $ per day) | SI.SPR.PC40 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.44 | .. | .. | .. | .. | 1.51 | .. | .. | .. | .. | .. | .. |
699 | Ethiopia | ETH | Survey mean consumption or income per capita, total population (2011 PPP $ per day) | SI.SPR.PCAP | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.8 | .. | .. | .. | .. | 3.11 | .. | .. | .. | .. | .. | .. |
700 | Ethiopia | ETH | Unemployment with advanced education (% of total labor force with advanced education) | SL.UEM.ADVN.ZS | .. | .. | 8.39000034332275 | .. | .. | .. | .. | .. | 8.05000019073486 | .. | .. | .. | .. | .. | .. | .. | 5.48000001907349 | .. | .. | .. | .. | .. | .. | .. | .. |
701 | Ethiopia | ETH | Unemployment with advanced education, female (% of female labor force with advanced education) | SL.UEM.ADVN.FE.ZS | .. | .. | 9.96000003814697 | .. | .. | .. | .. | .. | 13.9399995803833 | .. | .. | .. | .. | .. | .. | .. | 7.11999988555908 | .. | .. | .. | .. | .. | .. | .. | .. |
702 | Ethiopia | ETH | Unemployment with advanced education, male (% of male labor force with advanced education) | SL.UEM.ADVN.MA.ZS | .. | .. | 7.84000015258789 | .. | .. | .. | .. | .. | 5.65000009536743 | .. | .. | .. | .. | .. | .. | .. | 4.90000009536743 | .. | .. | .. | .. | .. | .. | .. | .. |
703 | Ethiopia | ETH | Unemployment with basic education (% of total labor force with basic education) | SL.UEM.BASC.ZS | .. | .. | 6.67000007629395 | .. | .. | .. | .. | .. | 3.97000002861023 | .. | .. | .. | .. | .. | .. | .. | 3.20000004768372 | .. | .. | .. | .. | .. | .. | .. | .. |
704 | Ethiopia | ETH | Unemployment with basic education, female (% of female labor force with basic education) | SL.UEM.BASC.FE.ZS | .. | .. | 14.6599998474121 | .. | .. | .. | .. | .. | 7.55000019073486 | .. | .. | .. | .. | .. | .. | .. | 5.46000003814697 | .. | .. | .. | .. | .. | .. | .. | .. |
705 | Ethiopia | ETH | Unemployment with basic education, male (% of male labor force with basic education) | SL.UEM.BASC.MA.ZS | .. | .. | 4.13000011444092 | .. | .. | .. | .. | .. | 2.53999996185303 | .. | .. | .. | .. | .. | .. | .. | 1.94000005722046 | .. | .. | .. | .. | .. | .. | .. | .. |
706 | Ethiopia | ETH | Unemployment with intermediate education (% of total labor force with intermediate education) | SL.UEM.INTM.ZS | .. | .. | 23.8999996185303 | .. | .. | .. | .. | .. | 17.1399993896484 | .. | .. | .. | .. | .. | .. | .. | 7.94000005722046 | .. | .. | .. | .. | .. | .. | .. | .. |
707 | Ethiopia | ETH | Unemployment with intermediate education, female (% of female labor force with intermediate education) | SL.UEM.INTM.FE.ZS | .. | .. | 36.3499984741211 | .. | .. | .. | .. | .. | 26.4300003051758 | .. | .. | .. | .. | .. | .. | .. | 10.9300003051758 | .. | .. | .. | .. | .. | .. | .. | .. |
708 | Ethiopia | ETH | Unemployment with intermediate education, male (% of male labor force with intermediate education) | SL.UEM.INTM.MA.ZS | .. | .. | 16.8899993896484 | .. | .. | .. | .. | .. | 11.5100002288818 | .. | .. | .. | .. | .. | .. | .. | 6.05999994277954 | .. | .. | .. | .. | .. | .. | .. | .. |
709 | Ethiopia | ETH | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS | 4.31099987030029 | 4.68699979782104 | 4.98600006103516 | 4.70100021362305 | 4.41099977493286 | 4.16099977493286 | 3.89599990844727 | 3.5550000667572 | 3.28399991989136 | 3.24300003051758 | 3.19600009918213 | 3.15599989891052 | 3.11999988555908 | 3.06599998474121 | 3.02800011634827 | 2.99399995803833 | 2.9449999332428 | 2.9539999961853 | 2.96099996566772 | 2.97199988365173 | 2.98000001907349 | 2.99600005149841 | 2.99900007247925 | 4.04400014877319 | 4.7039999961853 |
710 | Ethiopia | ETH | Unemployment, female (% of female labor force) (national estimate) | SL.UEM.TOTL.FE.NE.ZS | .. | .. | 5.05999994277954 | .. | .. | .. | .. | .. | 3.25 | .. | .. | .. | .. | .. | .. | .. | 2.94000005722046 | .. | .. | .. | .. | .. | .. | .. | .. |
711 | Ethiopia | ETH | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS | 2.8050000667572 | 2.76900005340576 | 2.6800000667572 | 2.53800010681152 | 2.39100003242493 | 2.2720000743866 | 2.14100003242493 | 1.96200001239777 | 1.8289999961853 | 1.80799996852875 | 1.78299999237061 | 1.76199996471405 | 1.74500000476837 | 1.7150000333786 | 1.69599997997284 | 1.67900002002716 | 1.65299999713898 | 1.66700005531311 | 1.67900002002716 | 1.69400000572205 | 1.70700001716614 | 1.72599995136261 | 1.73599994182587 | 2.5460000038147 | 2.81800007820129 |
712 | Ethiopia | ETH | Unemployment, male (% of male labor force) (national estimate) | SL.UEM.TOTL.MA.NE.ZS | .. | .. | 2.72000002861023 | .. | .. | .. | .. | .. | 1.80999994277954 | .. | .. | .. | .. | .. | .. | .. | 1.64999997615814 | .. | .. | .. | .. | .. | .. | .. | .. |
713 | Ethiopia | ETH | Unemployment, total (% of total labor force) (modeled ILO estimate) | SL.UEM.TOTL.ZS | 3.47000002861023 | 3.62100005149841 | 3.71000003814697 | 3.5090000629425 | 3.30399990081787 | 3.13000011444092 | 2.94199991226196 | 2.69300007820129 | 2.5 | 2.47000002861023 | 2.43499994277954 | 2.40599989891052 | 2.38000011444092 | 2.33899998664856 | 2.31200003623962 | 2.28699994087219 | 2.25 | 2.26200008392334 | 2.2739999294281 | 2.28800010681152 | 2.29900002479553 | 2.31800007820129 | 2.32599997520447 | 3.23699998855591 | 3.69400000572205 |
714 | Ethiopia | ETH | Unemployment, total (% of total labor force) (national estimate) | SL.UEM.TOTL.NE.ZS | .. | .. | 3.71000003814697 | .. | .. | .. | .. | .. | 2.5 | .. | .. | .. | .. | .. | .. | .. | 2.25 | .. | .. | .. | .. | .. | .. | .. | .. |
715 | Ethiopia | ETH | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS | 6.42899990081787 | 6.91800022125244 | 7.31899976730347 | 6.86800003051758 | 6.42199993133545 | 6.01900005340576 | 5.60099983215332 | 5.10799980163574 | 4.68200016021729 | 4.65399980545044 | 4.62200021743774 | 4.59499979019165 | 4.57200002670288 | 4.52799987792969 | 4.49599981307983 | 4.46600008010864 | 4.4210000038147 | 4.46199989318848 | 4.50500011444092 | 4.55200004577637 | 4.59899997711182 | 4.65899991989136 | 4.70800018310547 | 6.08500003814697 | 7.1560001373291 |
716 | Ethiopia | ETH | Unemployment, youth female (% of female labor force ages 15-24) (national estimate) | SL.UEM.1524.FE.NE.ZS | .. | .. | 7.44999980926514 | .. | .. | .. | .. | .. | 4.59999990463257 | .. | .. | .. | .. | .. | .. | .. | 4.48000001907349 | .. | .. | .. | .. | .. | .. | .. | .. |
717 | Ethiopia | ETH | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS | 4.0310001373291 | 3.91599988937378 | 3.75799989700317 | 3.56399989128113 | 3.37199997901917 | 3.2039999961853 | 3.02800011634827 | 2.80999994277954 | 2.63299989700317 | 2.62800002098084 | 2.62100005149841 | 2.61700010299683 | 2.61400008201599 | 2.59800004959106 | 2.59100008010864 | 2.58500003814697 | 2.57100009918213 | 2.61100006103516 | 2.65300011634827 | 2.69799995422363 | 2.74300003051758 | 2.79800009727478 | 2.84599995613098 | 3.93300008773804 | 4.44299983978271 |
718 | Ethiopia | ETH | Unemployment, youth male (% of male labor force ages 15-24) (national estimate) | SL.UEM.1524.MA.NE.ZS | .. | .. | 3.82999992370605 | .. | .. | .. | .. | .. | 2.63000011444092 | .. | .. | .. | .. | .. | .. | .. | 2.65000009536743 | .. | .. | .. | .. | .. | .. | .. | .. |
719 | Ethiopia | ETH | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.ZS | 5.11899995803833 | 5.28499984741211 | 5.38899993896484 | 5.08300018310547 | 4.78000020980835 | 4.50799989700317 | 4.22300004959106 | 3.88000011444092 | 3.58899998664856 | 3.57399988174438 | 3.5550000667572 | 3.54099988937378 | 3.52800011634827 | 3.49699997901917 | 3.4779999256134 | 3.46099996566772 | 3.43300008773804 | 3.47399997711182 | 3.51799988746643 | 3.56500005722046 | 3.61299991607666 | 3.67300009727478 | 3.72300004959106 | 4.93499994277954 | 5.71799993515015 |
720 | Ethiopia | ETH | Unemployment, youth total (% of total labor force ages 15-24) (national estimate) | SL.UEM.1524.NE.ZS | .. | .. | 5.42000007629395 | .. | .. | .. | .. | .. | 3.60999989509583 | .. | .. | .. | .. | .. | .. | .. | 3.52999997138977 | .. | .. | .. | .. | .. | .. | .. | .. |
721 | Ethiopia | ETH | Vulnerable employment, female (% of female employment) (modeled ILO estimate) | SL.EMP.VULN.FE.ZS | 90.8199996948243 | 91.3299980163574 | 91.61000061035159 | 92.2299995422363 | 91.9499988555908 | 92.25 | 92.8500022888184 | 92.7600021362304 | 92.9399967193604 | 92.8399963378906 | 92.4600009918213 | 92.4199981689454 | 92.269998550415 | 91.8300018310547 | 91.40999984741211 | 91.0600013732911 | 90.7299995422363 | 90.1100006103515 | 89.3699989318848 | 88.6700019836426 | 87.9500007629394 | 87.1399993896484 | 86.4500007629394 | .. | .. |
722 | Ethiopia | ETH | Vulnerable employment, male (% of male employment) (modeled ILO estimate) | SL.EMP.VULN.MA.ZS | 87.8000011444091 | 87.7000007629395 | 87.480001449585 | 87.7099990844727 | 87.8300018310547 | 87.98000335693361 | 88.2999992370605 | 88.2999973297119 | 88.4500045776367 | 88.1399974822998 | 87.7800045013428 | 87.46999931335449 | 87.1300010681152 | 86.5900020599365 | 86.05000114440921 | 85.6299991607666 | 85.1299991607666 | 84.42000198364249 | 83.73000144958499 | 82.8999996185303 | 82.2800025939941 | 81.75 | 81.3199996948242 | .. | .. |
723 | Ethiopia | ETH | Vulnerable employment, total (% of total employment) (modeled ILO estimate) | SL.EMP.VULN.ZS | 89.1199989318848 | 89.29999923706049 | 89.29999923706049 | 89.7200012207031 | 89.6699981689454 | 89.9000015258789 | 90.3599967956543 | 90.31999969482419 | 90.4900016784668 | 90.2799987792969 | 89.92000198364249 | 89.7299995422363 | 89.4699974060059 | 88.9799995422363 | 88.5 | 88.11000061035159 | 87.68999862670901 | 87.0200004577637 | 86.3300018310546 | 85.560001373291 | 84.8899993896484 | 84.2400016784668 | 83.7000007629394 | .. | .. |
724 | Ethiopia | ETH | Wage and salaried workers, female (% of female employment) (modeled ILO estimate) | SL.EMP.WORK.FE.ZS | 8.78999996185303 | 8.3100004196167 | 8.0600004196167 | 7.48000001907349 | 7.73999977111816 | 7.46000003814697 | 6.86999988555908 | 6.98000001907349 | 6.80000019073486 | 6.92999982833862 | 7.30999994277954 | 7.36999988555908 | 7.53000020980835 | 7.98000001907349 | 8.42000007629395 | 8.77999973297119 | 9.11999988555908 | 9.72999954223633 | 10.460000038147 | 11.1700000762939 | 11.8999996185303 | 12.710000038147 | 13.3800001144409 | .. | .. |
725 | Ethiopia | ETH | Wage and salaried workers, male (% of male employment) (modeled ILO estimate) | SL.EMP.WORK.MA.ZS | 10.5100002288818 | 10.7200002670288 | 11.0900001525879 | 11.0100002288818 | 10.8599996566772 | 10.789999961853 | 10.4799995422363 | 10.5500001907349 | 10.460000038147 | 10.8299999237061 | 11.210000038147 | 11.5600004196167 | 11.9399995803833 | 12.5299997329712 | 13.1099996566772 | 13.5500001907349 | 14.0799999237061 | 14.8100004196167 | 15.5200004577637 | 16.3899993896484 | 17.0300006866455 | 17.5400009155273 | 17.9699993133545 | .. | .. |
726 | Ethiopia | ETH | Wage and salaried workers, total (% of total employment) (modeled ILO estimate) | SL.EMP.WORK.ZS | 9.76000022888184 | 9.65999984741211 | 9.76000022888184 | 9.4399995803833 | 9.47000026702881 | 9.28999996185303 | 8.85000038146973 | 8.93000030517578 | 8.78999996185303 | 9.05000019073486 | 9.43000030517578 | 9.64999961853027 | 9.93000030517578 | 10.4499998092651 | 10.9700002670288 | 11.3699998855591 | 11.8199996948242 | 12.4899997711182 | 13.1999998092651 | 13.9899997711182 | 14.6599998474121 | 15.3100004196167 | 15.8500003814697 | .. | .. |
727 | Ethiopia | ETH | Women Business and the Law Index Score (scale 1-100) | SG.LAW.INDX | 50 | 50 | 50 | 50 | 63.125 | 63.125 | 63.125 | 63.125 | 65.625 | 65.625 | 65.625 | 65.625 | 65.625 | 65.625 | 65.625 | 71.875 | 71.875 | 71.875 | 71.875 | 71.875 | 71.875 | 71.875 | 71.875 | 76.875 | 76.875 |
728 | Ethiopia | ETH | Women making their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women age 15-49) | SG.DMK.SRCR.FN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 53.4 | .. | .. | .. | .. | 45.2 | .. | .. | .. | .. | .. |
729 | Ethiopia | ETH | Women participating in the three decisions (own health care, major household purchases, and visiting family) (% of women age 15-49) | SG.DMK.ALLD.FN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 45.4 | .. | .. | .. | .. | .. | 54.4 | .. | .. | .. | .. | 70.6 | .. | .. | .. | .. | .. |
730 | Ethiopia | ETH | Women who believe a husband is justified in beating his wife (any of five reasons) (%) | SG.VAW.REAS.ZS | .. | .. | .. | 84.5 | .. | .. | .. | .. | 81 | .. | .. | .. | .. | .. | 68.4 | .. | .. | .. | .. | 63 | .. | .. | .. | .. | .. |
731 | Ethiopia | ETH | Women who believe a husband is justified in beating his wife when she argues with him (%) | SG.VAW.ARGU.ZS | .. | .. | .. | 61.3 | .. | .. | .. | .. | 58.7 | .. | .. | .. | .. | .. | 45.4 | .. | .. | .. | .. | 42.2 | .. | .. | .. | .. | .. |
732 | Ethiopia | ETH | Women who believe a husband is justified in beating his wife when she burns the food (%) | SG.VAW.BURN.ZS | .. | .. | .. | 64.5 | .. | .. | .. | .. | 61 | .. | .. | .. | .. | .. | 47.3 | .. | .. | .. | .. | 39.8 | .. | .. | .. | .. | .. |
733 | Ethiopia | ETH | Women who believe a husband is justified in beating his wife when she goes out without telling him (%) | SG.VAW.GOES.ZS | .. | .. | .. | 56.2 | .. | .. | .. | .. | 64.2 | .. | .. | .. | .. | .. | 43.2 | .. | .. | .. | .. | 43.3 | .. | .. | .. | .. | .. |
734 | Ethiopia | ETH | Women who believe a husband is justified in beating his wife when she neglects the children (%) | SG.VAW.NEGL.ZS | .. | .. | .. | 64.5 | .. | .. | .. | .. | 64.6 | .. | .. | .. | .. | .. | 51.8 | .. | .. | .. | .. | 47.5 | .. | .. | .. | .. | .. |
735 | Ethiopia | ETH | Women who believe a husband is justified in beating his wife when she refuses sex with him (%) | SG.VAW.REFU.ZS | .. | .. | .. | 50.9 | .. | .. | .. | .. | 44.3 | .. | .. | .. | .. | .. | 38.6 | .. | .. | .. | .. | 34.7 | .. | .. | .. | .. | .. |
736 | Uganda | UGA | Adequacy of social insurance programs (% of total welfare of beneficiary households) | per_si_allsi.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | 23.1558368042772 | .. | .. | .. | 15.3913032749909 | .. | .. | 19.0510001789636 | .. | .. | .. | 24.6148015587818 | .. | .. | .. | .. | .. |
737 | Uganda | UGA | Adequacy of social protection and labor programs (% of total welfare of beneficiary households) | per_allsp.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | 23.1558368042772 | .. | .. | .. | 12.7771603538373 | .. | .. | 13.509509563971 | .. | .. | .. | 19.9750611518732 | .. | .. | .. | .. | .. |
738 | Uganda | UGA | Adequacy of social safety net programs (% of total welfare of beneficiary households) | per_sa_allsa.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.25016721665183 | .. | .. | 9.45784741521498 | .. | .. | .. | 11.7647255847571 | .. | .. | .. | .. | .. |
739 | Uganda | UGA | Adequacy of unemployment benefits and ALMP (% of total welfare of beneficiary households) | per_lm_alllm.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
740 | Uganda | UGA | Adjusted net national income (annual % growth) | NY.ADJ.NNTY.KD.ZG | 10.435412525283084 | 0.9342353973101041 | 13.070184047488894 | -2.2069402315340056 | 0.9873845053857622 | 5.0273018501417255 | -2.893575301687008 | 15.359728291197783 | 7.92597590807496 | 11.685347024347578 | 5.081297821142556 | 5.704646823392821 | 17.99680216493347 | 6.198154543167831 | 3.7103062380321745 | -1.3862031744505998 | 5.221926833316971 | 12.294708654057132 | 4.620496875619978 | 6.599493031991827 | 4.320461064474188 | 15.158565394508926 | 8.766817350082377 | 5.533056563071412 | .. |
741 | Uganda | UGA | Adjusted net national income (constant 2015 US$) | NY.ADJ.NNTY.KD | 8745771739.42075 | 8827477834.778362 | 9981245434.535181 | 9760965313.432274 | 9857343572.513182 | 10352901988.308964 | 10053332973.367392 | 11597497602.286018 | 12516712468.18278 | 13979333756.129719 | 14689665337.690184 | 15527658864.743763 | 18322140911.47745 | 19457775520.787804 | 20179718579.717888 | 19899986680.170643 | 20939149424.44898 | 23513556840.82266 | 24600000000 | 26223475285.86999 | 27356450325.348015 | 31503295737.532246 | 34265132134.097984 | 36161041276.488785 | .. |
742 | Uganda | UGA | Adjusted net national income (current US$) | NY.ADJ.NNTY.CD | 4770000000 | 5040000000 | 4841000000 | 4931000000 | 4555000000 | 4769000000 | 4664000000 | 5998000000 | 7098000000 | 7739000000 | 8887000000 | 10620000000 | 19970000000 | 21090000000 | 21240000000 | 19400000000 | 20940000000 | 24210000000 | 24600000000 | 22000000000 | 23600000000 | 26960000000 | 29310000000 | 31950000000 | .. |
743 | Uganda | UGA | Adjusted net national income per capita (annual % growth) | NY.ADJ.NNTY.PC.KD.ZG | 7.260483761447816 | -1.9428773982261873 | 9.810857678858298 | -5.0921386284084775 | -2.071825549262158 | 1.7793765524686194 | -5.933361019716429 | 11.743608355176448 | 4.560514626485386 | 8.218530593075172 | 1.8209849974345218 | 2.4208028136433626 | 14.317797008225355 | 2.8673848873553567 | 0.46174162721335676 | -4.4735018278106224 | 1.8737079173009903 | 8.592236941999062 | 1.0243937510881977 | 2.7717090371915702 | 0.4751719570517139 | 10.94763897920285 | 4.981797528172677 | 2.138231103273 | .. |
744 | Uganda | UGA | Adjusted net national income per capita (constant 2015 US$) | NY.ADJ.NNTY.PC.KD | 403.8611602791928 | 396.0146330759144 | 434.86706511444515 | 412.7230313095262 | 404.17213009916617 | 411.36387421376384 | 386.956170451969 | 432.39878761603717 | 452.118397570012 | 489.2758863912248 | 498.1855268784738 | 510.245616130312 | 583.3015476912187 | 600.0270481174267 | 602.7976227731242 | 575.8314601003696 | 586.6208597585803 | 637.0247139802294 | 643.5503553431305 | 661.3876987010547 | 664.5304275726717 | 737.280819690281 | 774.0106573413026 | 790.5607939592222 | .. |
745 | Uganda | UGA | Adjusted net national income per capita (current US$) | NY.ADJ.NNTY.PC.CD | 220.26846708662674 | 226.10238032421196 | 210.91470759100375 | 208.49754117932144 | 186.76472409212457 | 189.49221371368145 | 179.5189300671768 | 223.62823576784123 | 256.38812061150264 | 270.86455984509024 | 301.3938490490595 | 348.97781375192096 | 635.7625980322367 | 650.3605939577708 | 634.4697750428267 | 561.3637087043205 | 586.6446890627662 | 655.8926167514595 | 643.5503553431305 | 554.8665542153931 | 573.2804477261997 | 630.9527442606236 | 662.0798156531255 | 698.4980651931528 | .. |
746 | Uganda | UGA | Adjusted net savings, excluding particulate emission damage (% of GNI) | NY.ADJ.SVNX.GN.ZS | 2.2145397 | -2.8814946 | 0.36792243 | -2.2105433 | -2.0854729 | -1.4485137 | -6.7710304 | 2.4703887 | 3.6550201 | 0.25332949 | -4.1902366 | 0.07076435 | 1.1789199 | 1.072127 | -3.7072792 | -6.5211714 | -1.4339631 | 2.9238253 | -4.4339093 | 2.3259836 | 3.7850067 | 7.1784707 | 9.3249229 | 9.911851 | .. |
747 | Uganda | UGA | Adjusted net savings, excluding particulate emission damage (current US$) | NY.ADJ.SVNX.CD | 138500000 | -189500000 | 22018551 | -134500000 | -118000000 | -87556278 | -438100000 | 190800000 | 327700000 | 24646256 | -489200000 | 10033177 | 291500000 | 281200000 | -1017000000 | -1743000000 | -405400000 | 931700000 | -1408000000 | 667400000 | 1136000000 | 2297000000 | 3211000000 | 3665000000 | .. |
748 | Uganda | UGA | Adjusted net savings, including particulate emission damage (% of GNI) | NY.ADJ.SVNG.GN.ZS | 0.20545497 | -4.9279191 | -1.6469501 | -4.2932022 | -4.1894549 | -3.4171266 | -8.6573499 | 0.59162148 | 1.7933306 | -1.4938174 | -5.8420177 | -1.4768588 | -0.31828707 | -0.43156485 | -5.1461208 | -7.9827386 | -2.9395715 | 1.4418731 | -5.8106895 | 0.98196617 | 2.5656969 | 6.0486179 | 8.2965899 | 8.9531439 | .. |
749 | Uganda | UGA | Adjusted net savings, including particulate emission damage (current US$) | NY.ADJ.SVNG.CD | 12846695 | -324100000 | -98562772 | -261300000 | -237100000 | -206600000 | -560100000 | 45701454 | 160800000 | -145300000 | -682000000 | -209400000 | -78691532 | -113200000 | -1412000000 | -2134000000 | -831100000 | 459500000 | -1845000000 | 281700000 | 770200000 | 1936000000 | 2857000000 | 3311000000 | .. |
750 | Uganda | UGA | Adjusted savings: carbon dioxide damage (% of GNI) | NY.ADJ.DCO2.GN.ZS | 0.2993838 | 0.33693856 | 0.3930458 | 0.41037244 | 0.46451594 | 0.51428363 | 0.53022123 | 0.50540086 | 0.57849779 | 0.65789986 | 0.65382898 | 0.603604 | 0.38114765 | 0.42140024 | 0.45157929 | 0.45739702 | 0.4891509 | 0.50155737 | 0.53361619 | 0.70839898 | 0.72788217 | 0.75052662 | 0.78430178 | 0.79395733 | .. |
751 | Uganda | UGA | Adjusted savings: carbon dioxide damage (current US$) | NY.ADJ.DCO2.CD | 18719880 | 22158144 | 23522074 | 24973588 | 26290618 | 31086182 | 34304212 | 39041102 | 51874371 | 64006635 | 76327949 | 85580739 | 94232832 | 110500000 | 123900000 | 122300000 | 138300000 | 159800000 | 169500000 | 203300000 | 218500000 | 240200000 | 270100000 | 293600000 | .. |
752 | Uganda | UGA | Adjusted savings: consumption of fixed capital (% of GNI) | NY.ADJ.DKAP.GN.ZS | 6.8218416 | 6.5533585 | 6.6167226 | 6.7062794 | 6.6555492 | 6.5332958 | 6.5837227 | 6.7444378 | 6.623675 | 6.892362 | 7.4148964 | 8.4035731 | 9.6118612 | 11.37632 | 13.305586 | 16.532571 | 15.216777 | 13.483462 | 11.538487 | 10.378964 | 8.9562134 | 7.5827115 | 7.3167313 | 6.2069699 | .. |
753 | Uganda | UGA | Adjusted savings: consumption of fixed capital (current US$) | NY.ADJ.DKAP.CD | 426600000 | 431000000 | 396000000 | 408100000 | 376700000 | 394900000 | 426000000 | 521000000 | 594000000 | 670600000 | 865600000 | 1191000000 | 2376000000 | 2984000000 | 3651000000 | 4419000000 | 4302000000 | 4297000000 | 3665000000 | 2978000000 | 2689000000 | 2427000000 | 2520000000 | 2295000000 | .. |
754 | Uganda | UGA | Adjusted savings: education expenditure (% of GNI) | NY.ADJ.AEDU.GN.ZS | 1.9365775 | 1.9365775 | 2.2471479 | 2.5577183 | 2.8682887 | 3.1788592 | 3.4894296 | 3.8 | 3.6 | 3.4 | 3.2 | 3 | 2.8 | 2.1 | 2.5 | 2.4 | 2 | 1.72096 | 1.72096 | 1.72096 | 1.72096 | 1.72096 | 1.72096 | 1.72096 | .. |
755 | Uganda | UGA | Adjusted savings: education expenditure (current US$) | NY.ADJ.AEDU.CD | 121100000 | 127400000 | 134500000 | 155700000 | 162300000 | 192100000 | 225800000 | 293500000 | 322800000 | 330800000 | 373600000 | 425300000 | 692300000 | 550900000 | 686000000 | 641500000 | 565500000 | 548400000 | 546600000 | 493800000 | 516600000 | 550700000 | 592600000 | 636300000 | .. |
756 | Uganda | UGA | Adjusted savings: energy depletion (% of GNI) | NY.ADJ.DNGY.GN.ZS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
757 | Uganda | UGA | Adjusted savings: energy depletion (current US$) | NY.ADJ.DNGY.CD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
758 | Uganda | UGA | Adjusted savings: gross savings (% of GNI) | NY.ADJ.ICTR.GN.ZS | 24.293777 | 18.885736 | 17.623445 | 14.610463 | 15.028682 | 16.984194 | 18.181233 | 21.527738 | 21.476519 | 17.968826 | 17.133927 | 22.789796 | 17.989027 | 19.006549 | 16.848669 | 18.942324 | 22.98123 | 25.729116 | 16.907064 | 24.626447 | 24.166087 | 21.944773 | 23.287784 | 22.588572 | .. |
759 | Uganda | UGA | Adjusted savings: mineral depletion (% of GNI) | NY.ADJ.DMIN.GN.ZS | 0 | 0.0001703 | 7.648e-05 | 0.00138594 | 0 | 0.00012532 | 7.132e-05 | 0.01630199 | 0.02658234 | 0.06416412 | 0.06049333 | 0.05979425 | 1.383e-05 | 0.00064918 | 0.0001627 | 0.00039973 | 0.105726 | 0.0773632 | 0.05797831 | 0.08248592 | 0.03834297 | 0 | 0 | 1.6e-05 | .. |
760 | Uganda | UGA | Adjusted savings: mineral depletion (current US$) | NY.ADJ.DMIN.CD | 0 | 11199.7 | 4576.9394 | 84342.809 | 0 | 7574.8371 | 4614.0666 | 1259292.9 | 2383659.8 | 6242483.9 | 7061986.7 | 8477803.3 | 3419.01 | 170286.75 | 44646.888 | 106843.03 | 29892742 | 24652220 | 18413452 | 23666788 | 11510853 | 0 | 0 | 5914.7942 | .. |
761 | Uganda | UGA | Adjusted savings: natural resources depletion (% of GNI) | NY.ADJ.DRES.GN.ZS | 16.894589 | 16.8135103 | 12.492902480000001 | 12.262072940000001 | 12.862378 | 14.56398732 | 21.32774932 | 15.60751099 | 14.219326339999999 | 13.56523412 | 16.45543833 | 16.71185525 | 9.617098030000001 | 8.23670178 | 9.2987827 | 10.87352773 | 10.709265 | 10.5412312 | 10.989830309999999 | 12.93406092 | 12.41794497 | 8.1540237 | 7.5827884 | 7.3967534 | .. |
762 | Uganda | UGA | Adjusted savings: net forest depletion (% of GNI) | NY.ADJ.DFOR.GN.ZS | 16.894589 | 16.81334 | 12.492826 | 12.260687 | 12.862378 | 14.563862 | 21.327678 | 15.591209 | 14.192744 | 13.50107 | 16.394945 | 16.652061 | 9.6170842 | 8.2360526 | 9.29862 | 10.873128 | 10.603539 | 10.463868 | 10.931852 | 12.851575 | 12.379602 | 8.1540237 | 7.5827884 | 7.3967374 | .. |
763 | Uganda | UGA | Adjusted savings: net forest depletion (current US$) | NY.ADJ.DFOR.CD | 1056000000 | 1106000000 | 747600000 | 746100000 | 728000000 | 880300000 | 1380000000 | 1204000000 | 1273000000 | 1314000000 | 1914000000 | 2361000000 | 2378000000 | 2160000000 | 2552000000 | 2906000000 | 2998000000 | 3334000000 | 3472000000 | 3687000000 | 3716000000 | 2609000000 | 2611000000 | 2735000000 | .. |
764 | Uganda | UGA | Adjusted savings: net national savings (% of GNI) | NY.ADJ.NNAT.GN.ZS | 17.471935 | 12.332377 | 11.006722 | 7.904184 | 8.3731325 | 10.450898 | 11.59751 | 14.7833 | 14.852844 | 11.076464 | 9.7190307 | 14.386223 | 8.3771656 | 7.630229 | 3.5430828 | 2.4097529 | 7.7644526 | 12.245654 | 5.368577 | 14.247483 | 15.209874 | 14.362061 | 15.971053 | 16.381602 | .. |
765 | Uganda | UGA | Adjusted savings: net national savings (current US$) | NY.ADJ.NNAT.CD | 1092000000 | 811000000 | 658700000 | 481000000 | 473900000 | 631700000 | 750300000 | 1142000000 | 1332000000 | 1078000000 | 1135000000 | 2040000000 | 2071000000 | 2001000000 | 972200000 | 644100000 | 2195000000 | 3902000000 | 1705000000 | 4088000000 | 4566000000 | 4596000000 | 5500000000 | 6057000000 | .. |
766 | Uganda | UGA | Adjusted savings: particulate emission damage (% of GNI) | NY.ADJ.DPEM.GN.ZS | 2.0090847 | 2.0464245 | 2.0148726 | 2.0826589 | 2.103982 | 1.9686129 | 1.8863194 | 1.8787672 | 1.8616895 | 1.7471469 | 1.6517812 | 1.5476232 | 1.497207 | 1.5036919 | 1.4388416 | 1.4615672 | 1.5056084 | 1.4819522 | 1.3767802 | 1.3440174 | 1.2193097 | 1.1298528 | 1.028333 | 0.95870709 | .. |
767 | Uganda | UGA | Adjusted savings: particulate emission damage (current US$) | NY.ADJ.DPEM.CD | 125600000 | 134600000 | 120600000 | 126700000 | 119100000 | 119000000 | 122000000 | 145100000 | 166900000 | 170000000 | 192800000 | 219400000 | 370200000 | 394400000 | 394800000 | 390700000 | 425700000 | 472200000 | 437300000 | 385600000 | 366000000 | 361600000 | 354100000 | 354500000 | .. |
768 | Uganda | UGA | Agriculture, forestry, and fishing, value added (annual % growth) | NV.AGR.TOTL.KD.ZG | 1.0891816574710305 | 1.769947271114745 | 5.822426355460351 | -0.4383317120407355 | 7.856684045589347 | 7.066710547083275 | 2.139936527974882 | 1.5886157448124578 | 2.049354400060068 | 0.45858600264512006 | 0.11923778450525901 | 1.3458424837918983 | 3.3039289600511665 | 2.876958527100257 | 3.1100634952851465 | 0.5941486272483587 | 1.8620029575457693 | 2.697698295493794 | 2.345716238531608 | 2.809330657106827 | 2.758074789477405 | 4.389182904089168 | 5.315755577438523 | 4.822808974941935 | 3.818014111327713 |
769 | Uganda | UGA | Agriculture, forestry, and fishing, value added (constant 2015 US$) | NV.AGR.TOTL.KD | 4833209262.882644 | 4918754518.3383 | 5205145377.7744255 | 5182329574.9258175 | 5589488835.828873 | 5984481832.918434 | 6112545945.671077 | 6209650812.972903 | 6336908565.1369295 | 6365968740.817067 | 6373559380.905915 | 6459337450.783852 | 6672749371.44773 | 6864721603.481625 | 7078218804.12446 | 7120273943.9828005 | 7252853655.405121 | 7448513764.841644 | 7623234761.752797 | 7837396632.977942 | 8053557893.663458 | 8407043279.903057 | 8853941151.952175 | 9280949820.464602 | 9635297794.275185 |
770 | Uganda | UGA | Agriculture, forestry, and fishing, value added per worker (constant 2015 US$) | NV.AGR.EMPL.KD | 905.07666397156 | 902.7232506011547 | 937.4563247840279 | 911.6312382752592 | 961.5400515680188 | 1008.8726275197799 | 1003.7649906730777 | 979.5512457151045 | 960.9375341756108 | 941.9209735978088 | 918.400678506466 | 906.9559527130835 | 913.2796892438222 | 909.2847147575927 | 909.3125681346642 | 885.3972255619641 | 787.0896120282406 | 773.9343331474574 | 763.5876644784635 | 752.1704435017084 | 738.1593619275204 | 741.101634208238 | 753.2478148117546 | .. | .. |
771 | Uganda | UGA | Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%) | SI.SPR.PC40.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.05 | .. | .. |
772 | Uganda | UGA | Annualized average growth rate in per capita real survey mean consumption or income, total population (%) | SI.SPR.PCAP.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -0.26 | .. | .. |
773 | Uganda | UGA | Average working hours of children, study and work, ages 7-14 (hours per week) | SL.TLF.0714.SW.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
774 | Uganda | UGA | Average working hours of children, study and work, female, ages 7-14 (hours per week) | SL.TLF.0714.SW.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
775 | Uganda | UGA | Average working hours of children, study and work, male, ages 7-14 (hours per week) | SL.TLF.0714.SW.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
776 | Uganda | UGA | Average working hours of children, working only, ages 7-14 (hours per week) | SL.TLF.0714.WK.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 33.2 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
777 | Uganda | UGA | Average working hours of children, working only, female, ages 7-14 (hours per week) | SL.TLF.0714.WK.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 33.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
778 | Uganda | UGA | Average working hours of children, working only, male, ages 7-14 (hours per week) | SL.TLF.0714.WK.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 32.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
779 | Uganda | UGA | Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits) | per_si_allsi.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | 0 | .. | .. | .. | 0.024305121105773 | .. | .. | 0.460287378914602 | .. | .. | .. | 0.148549952765491 | .. | .. | .. | .. | .. |
780 | Uganda | UGA | Benefit incidence of social protection and labor programs to poorest quintile (% of total SPL benefits) | per_allsp.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | 0 | .. | .. | .. | 0.124285098426065 | .. | .. | 0.890421276506836 | .. | .. | .. | 0.96287810052452 | .. | .. | .. | .. | .. |
781 | Uganda | UGA | Benefit incidence of social safety net programs to poorest quintile (% of total safety net benefits) | per_sa_allsa.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.610690636586254 | .. | .. | 1.51554551528568 | .. | .. | .. | 3.39534676245857 | .. | .. | .. | .. | .. |
782 | Uganda | UGA | Benefit incidence of unemployment benefits and ALMP to poorest quintile (% of total U/ALMP benefits) | per_lm_alllm.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
783 | Uganda | UGA | Child employment in agriculture (% of economically active children ages 7-14) | SL.AGR.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 95.48 | .. | .. | .. | .. | .. | 95.29 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
784 | Uganda | UGA | Child employment in agriculture, female (% of female economically active children ages 7-14) | SL.AGR.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 94.89 | .. | .. | .. | .. | .. | 96.19 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
785 | Uganda | UGA | Child employment in agriculture, male (% of male economically active children ages 7-14) | SL.AGR.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 96.02 | .. | .. | .. | .. | .. | 94.36 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
786 | Uganda | UGA | Child employment in manufacturing (% of economically active children ages 7-14) | SL.MNF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.36 | .. | .. | .. | .. | .. | 1.09 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
787 | Uganda | UGA | Child employment in manufacturing, female (% of female economically active children ages 7-14) | SL.MNF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.71 | .. | .. | .. | .. | .. | 0.88 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
788 | Uganda | UGA | Child employment in manufacturing, male (% of male economically active children ages 7-14) | SL.MNF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.03 | .. | .. | .. | .. | .. | 1.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
789 | Uganda | UGA | Child employment in services (% of economically active children ages 7-14) | SL.SRV.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.99 | .. | .. | .. | .. | .. | 3.14 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
790 | Uganda | UGA | Child employment in services, female (% of female economically active children ages 7-14) | SL.SRV.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.32 | .. | .. | .. | .. | .. | 2.69 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
791 | Uganda | UGA | Child employment in services, male (% of male economically active children ages 7-14) | SL.SRV.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.69 | .. | .. | .. | .. | .. | 3.61 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
792 | Uganda | UGA | Children in employment, female (% of female children ages 7-14) | SL.TLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 36.49879 | .. | .. | .. | .. | .. | 36.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
793 | Uganda | UGA | Children in employment, male (% of male children ages 7-14) | SL.TLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 39.82124 | .. | .. | .. | .. | .. | 37.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
794 | Uganda | UGA | Children in employment, self-employed (% of children in employment, ages 7-14) | SL.SLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.4 | .. | .. | .. | .. | .. | 11.15 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
795 | Uganda | UGA | Children in employment, self-employed, female (% of female children in employment, ages 7-14) | SL.SLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.34 | .. | .. | .. | .. | .. | 11.79 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
796 | Uganda | UGA | Children in employment, self-employed, male (% of male children in employment, ages 7-14) | SL.SLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.46 | .. | .. | .. | .. | .. | 10.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
797 | Uganda | UGA | Children in employment, study and work (% of children in employment, ages 7-14) | SL.TLF.0714.SW.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 92.26758 | .. | .. | .. | .. | .. | 93.3810372264772 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
798 | Uganda | UGA | Children in employment, study and work, female (% of female children in employment, ages 7-14) | SL.TLF.0714.SW.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 93.9282268163292 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
799 | Uganda | UGA | Children in employment, study and work, male (% of male children in employment, ages 7-14) | SL.TLF.0714.SW.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 92.8199776562071 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
800 | Uganda | UGA | Children in employment, total (% of children ages 7-14) | SL.TLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 38.17033 | .. | .. | .. | .. | .. | 36.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
801 | Uganda | UGA | Children in employment, unpaid family workers (% of children in employment, ages 7-14) | SL.FAM.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 97.07 | .. | .. | .. | .. | .. | 85.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
802 | Uganda | UGA | Children in employment, unpaid family workers, female (% of female children in employment, ages 7-14) | SL.FAM.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 96.95 | .. | .. | .. | .. | .. | 86.47 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
803 | Uganda | UGA | Children in employment, unpaid family workers, male (% of male children in employment, ages 7-14) | SL.FAM.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 97.18 | .. | .. | .. | .. | .. | 84.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
804 | Uganda | UGA | Children in employment, wage workers (% of children in employment, ages 7-14) | SL.WAG.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.53 | .. | .. | .. | .. | .. | 2.98 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
805 | Uganda | UGA | Children in employment, wage workers, female (% of female children in employment, ages 7-14) | SL.WAG.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.71 | .. | .. | .. | .. | .. | 1.72 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
806 | Uganda | UGA | Children in employment, wage workers, male (% of male children in employment, ages 7-14) | SL.WAG.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.36 | .. | .. | .. | .. | .. | 4.29 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
807 | Uganda | UGA | Children in employment, work only (% of children in employment, ages 7-14) | SL.TLF.0714.WK.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.732421 | .. | .. | .. | .. | .. | 6.61896277352278 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
808 | Uganda | UGA | Children in employment, work only, female (% of female children in employment, ages 7-14) | SL.TLF.0714.WK.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.07177318367076 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
809 | Uganda | UGA | Children in employment, work only, male (% of male children in employment, ages 7-14) | SL.TLF.0714.WK.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.18002234379292 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
810 | Uganda | UGA | Community health workers (per 1,000 people) | SH.MED.CMHW.P3 | .. | .. | .. | .. | .. | .. | .. | .. | 0.194 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
811 | Uganda | UGA | Contributing family workers, female (% of female employment) (modeled ILO estimate) | SL.FAM.WORK.FE.ZS | 48.0299987792969 | 47.25 | 46.1699981689453 | 45.4500007629395 | 44.2299995422363 | 42.6100006103516 | 42.8199996948242 | 39.5299987792969 | 36.8499984741211 | 34.3899993896484 | 30.3799991607666 | 27.7999992370605 | 27.8999996185303 | 25.2700004577637 | 21.9300003051758 | 19.6700000762939 | 19.1800003051758 | 19.0300006866455 | 18.3500003814697 | 17.4599990844727 | 17.5799999237061 | 16.5200004577637 | 15.8400001525879 | .. | .. |
812 | Uganda | UGA | Contributing family workers, male (% of male employment) (modeled ILO estimate) | SL.FAM.WORK.MA.ZS | 14.4700002670288 | 14.039999961853 | 13.5100002288818 | 13.0900001525879 | 12.4899997711182 | 11.710000038147 | 11.2600002288818 | 11.3900003433228 | 11.6199998855591 | 11.9799995422363 | 11.8800001144409 | 12.1899995803833 | 13.4399995803833 | 13.539999961853 | 13.1700000762939 | 13.3000001907349 | 12.4899997711182 | 12.039999961853 | 11.460000038147 | 10.8599996566772 | 10.6099996566772 | 9.89999961853027 | 9.43000030517578 | .. | .. |
813 | Uganda | UGA | Contributing family workers, total (% of total employment) (modeled ILO estimate) | SL.FAM.WORK.ZS | 30.1299991607666 | 29.5799999237061 | 28.8099994659424 | 28.2800006866455 | 27.3799991607666 | 26.2000007629395 | 26.0699996948242 | 24.6900005340576 | 23.6000003814697 | 22.6499996185303 | 20.7099990844727 | 19.6599998474121 | 20.3700008392334 | 19.1800003051758 | 17.3899993896484 | 16.3700008392334 | 15.7299995422363 | 15.4300003051758 | 14.8199996948242 | 14.0799999237061 | 14.0299997329712 | 13.1499996185303 | 12.5799999237061 | .. | .. |
814 | Uganda | UGA | Coverage of social insurance programs (% of population) | per_si_allsi.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | 0.963110468060397 | .. | .. | .. | 0.861091584516169 | .. | .. | 0.881115931846307 | .. | .. | .. | 0.569601271182531 | .. | .. | .. | .. | .. |
815 | Uganda | UGA | Coverage of social insurance programs in 2nd quintile (% of population) | per_si_allsi.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | 0.514537885814161 | .. | .. | .. | 0.10387846948866 | .. | .. | 0.978483431831308 | .. | .. | .. | 0.185679512981656 | .. | .. | .. | .. | .. |
816 | Uganda | UGA | Coverage of social insurance programs in 3rd quintile (% of population) | per_si_allsi.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | 0.487759841600244 | .. | .. | .. | 0.745964951191858 | .. | .. | 0.721035407398354 | .. | .. | .. | 0.469023347937595 | .. | .. | .. | .. | .. |
817 | Uganda | UGA | Coverage of social insurance programs in 4th quintile (% of population) | per_si_allsi.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | 1.00761779095469 | .. | .. | .. | 0.683353656336496 | .. | .. | 0.679422846599253 | .. | .. | .. | 0.356207306443917 | .. | .. | .. | .. | .. |
818 | Uganda | UGA | Coverage of social insurance programs in poorest quintile (% of population) | per_si_allsi.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | 0 | .. | .. | .. | 0.0090603482463608 | .. | .. | 0.0156208127748498 | .. | .. | .. | 0.0274347258577449 | .. | .. | .. | .. | .. |
819 | Uganda | UGA | Coverage of social insurance programs in richest quintile (% of population) | per_si_allsi.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | 2.80394157878477 | .. | .. | .. | 2.75816836870973 | .. | .. | 2.01167559205172 | .. | .. | .. | 1.80904875743398 | .. | .. | .. | .. | .. |
820 | Uganda | UGA | Coverage of social protection and labor programs (% of population) | per_allsp.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | 10.5921138800537 | .. | .. | .. | 7.19779980293905 | .. | .. | 60.7139317597764 | .. | .. | .. | 1.18878183126531 | .. | .. | .. | .. | .. |
821 | Uganda | UGA | Coverage of social safety net programs (% of population) | per_sa_allsa.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | 9.84115656062756 | .. | .. | .. | 6.46920982732836 | .. | .. | 60.472307628686 | .. | .. | .. | 0.64220113605108 | .. | .. | .. | .. | .. |
822 | Uganda | UGA | Coverage of social safety net programs in 2nd quintile (% of population) | per_sa_allsa.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | 9.43746273999006 | .. | .. | .. | 5.79899248631246 | .. | .. | 71.8811420243086 | .. | .. | .. | 0.650277951503752 | .. | .. | .. | .. | .. |
823 | Uganda | UGA | Coverage of social safety net programs in 3rd quintile (% of population) | per_sa_allsa.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | 8.8659466944775 | .. | .. | .. | 5.53506205934488 | .. | .. | 63.4294304393803 | .. | .. | .. | 0.509347351393551 | .. | .. | .. | .. | .. |
824 | Uganda | UGA | Coverage of social safety net programs in 4th quintile (% of population) | per_sa_allsa.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | 8.41205219309416 | .. | .. | .. | 9.28860209860811 | .. | .. | 56.4987350493327 | .. | .. | .. | 0.465479230678406 | .. | .. | .. | .. | .. |
825 | Uganda | UGA | Coverage of social safety net programs in poorest quintile (% of population) | per_sa_allsa.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | 13.0360788441012 | .. | .. | .. | 5.10232647837888 | .. | .. | 75.68675157312 | .. | .. | .. | 0.455521668202752 | .. | .. | .. | .. | .. |
826 | Uganda | UGA | Coverage of social safety net programs in richest quintile (% of population) | per_sa_allsa.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | 9.45624457909354 | .. | .. | .. | 6.62643632733282 | .. | .. | 34.8991498072085 | .. | .. | .. | 1.13007345086202 | .. | .. | .. | .. | .. |
827 | Uganda | UGA | Coverage of unemployment benefits and ALMP (% of population) | per_lm_alllm.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
828 | Uganda | UGA | Coverage of unemployment benefits and ALMP in 2nd quintile (% of population) | per_lm_alllm.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
829 | Uganda | UGA | Coverage of unemployment benefits and ALMP in 3rd quintile (% of population) | per_lm_alllm.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
830 | Uganda | UGA | Coverage of unemployment benefits and ALMP in 4th quintile (% of population) | per_lm_alllm.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
831 | Uganda | UGA | Coverage of unemployment benefits and ALMP in poorest quintile (% of population) | per_lm_alllm.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
832 | Uganda | UGA | Coverage of unemployment benefits and ALMP in richest quintile (% of population) | per_lm_alllm.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
833 | Uganda | UGA | Current health expenditure (% of GDP) | SH.XPD.CHEX.GD.ZS | .. | .. | .. | 5.0709548 | 5.03950405 | 4.75769854 | 4.29922581 | 4.70028543 | 5.80522776 | 6.46337509 | 6.11315584 | 5.45659018 | 5.78845501 | 6.80890226 | 6.69590998 | 6.10853958 | 5.78252459 | 5.33653069 | 5.11239147 | 4.9682045 | 4.0002389 | 4.03115654 | 3.82522416 | .. | .. |
834 | Uganda | UGA | Current health expenditure per capita (current US$) | SH.XPD.CHEX.PC.CD | .. | .. | .. | 16.63032341 | 16.18933678 | 15.92738056 | 14.43743706 | 18.83850098 | 26.12890434 | 31.8495903 | 36.30623245 | 40.19852066 | 44.42363358 | 51.82595825 | 55.00610352 | 54.68679047 | 52.37650299 | 50.24546432 | 39.37041855 | 38.24341202 | 30.68274689 | 32.0545311 | 32.40844345 | .. | .. |
835 | Uganda | UGA | Current health expenditure per capita, PPP (current international $) | SH.XPD.CHEX.PP.CD | .. | .. | .. | 48.75408554 | 49.53538132 | 52.34505081 | 48.97396469 | 52.33834839 | 74.92816925 | 94.51382446 | 97.00923157 | 102.76470184 | 117.88221741 | 141.24189758 | 162.08204651 | 136.51908875 | 130.02079773 | 121.65574646 | 113.36191559 | 107.92300415 | 87.20411682 | 92.1367569 | 92.3787384 | .. | .. |
836 | Uganda | UGA | Domestic general government health expenditure (% of current health expenditure) | SH.XPD.GHED.CH.ZS | .. | .. | .. | 24.78430367 | 26.53934669 | 30.53055382 | 33.96677399 | 28.94309998 | 17.19150734 | 14.61253929 | 14.92760944 | 16.36199188 | 14.00690651 | 15.62244892 | 13.56997776 | 15.1402874 | 16.84941292 | 17.81628418 | 15.15355301 | 15.6786232 | 15.97236443 | 16.77466774 | 15.11674786 | .. | .. |
837 | Uganda | UGA | Domestic general government health expenditure (% of GDP) | SH.XPD.GHED.GD.ZS | .. | .. | .. | 1.25680089 | 1.33745134 | 1.45255184 | 1.46030819 | 1.36040831 | 0.99800611 | 0.94446313 | 0.91254807 | 0.89280677 | 0.81078357 | 1.06371725 | 0.90863341 | 0.92485046 | 0.97432137 | 0.95077145 | 0.77470893 | 0.77894604 | 0.63893265 | 0.67621309 | 0.57824951 | .. | .. |
838 | Uganda | UGA | Domestic general government health expenditure (% of general government expenditure) | SH.XPD.GHED.GE.ZS | .. | .. | .. | 8.25269794 | 8.25269794 | 8.6661396 | 8.87241268 | 8.72451782 | 6.89650869 | 6.89650869 | 6.89650869 | 6.89650869 | 6.89650869 | 6.89650869 | 6.89701271 | 7.05044508 | 7.32427692 | 7.00898075 | 5.0845356 | 4.87623453 | 4.1288538 | 4.16571712 | 3.14519548 | .. | .. |
839 | Uganda | UGA | Domestic general government health expenditure per capita (current US$) | SH.XPD.GHED.PC.CD | .. | .. | .. | 4.12171013 | 4.29654422 | 4.86271749 | 4.90393166 | 5.45244608 | 4.4919521 | 4.65403401 | 5.41965247 | 6.57727829 | 6.2223775 | 8.09648391 | 7.46431583 | 8.27973695 | 8.82513294 | 8.95187458 | 5.96601784 | 5.99604044 | 4.9007599 | 5.37704109 | 4.89910268 | .. | .. |
840 | Uganda | UGA | Domestic general government health expenditure per capita, PPP (current international $) | SH.XPD.GHED.PP.CD | .. | .. | .. | 12.08336064 | 13.1463662 | 15.98123475 | 16.63487553 | 15.14834011 | 12.88127969 | 13.81087037 | 14.48115828 | 16.81435159 | 16.51165295 | 22.06544368 | 21.99449903 | 20.66938332 | 21.9077415 | 21.67453544 | 17.17835778 | 16.92083947 | 13.92855861 | 15.45563456 | 13.96466147 | .. | .. |
841 | Uganda | UGA | Domestic private health expenditure (% of current health expenditure) | SH.XPD.PVTD.CH.ZS | .. | .. | .. | 43.67525101 | 44.05714798 | 45.26638794 | 47.10068512 | 40.19876862 | 50.22623062 | 55.57507706 | 56.09165573 | 54.3511734 | 44.22179413 | 38.74053955 | 36.24131393 | 38.84606934 | 45.71915817 | 46.20917892 | 41.92140579 | 43.05946732 | 40.88721466 | 39.71256638 | 42.86341858 | .. | .. |
842 | Uganda | UGA | Domestic private health expenditure per capita (current US$) | SH.XPD.PVTD.PC.CD | .. | .. | .. | 7.26333607 | 7.13256066 | 7.20975016 | 6.80013183 | 7.57284479 | 13.12356238 | 17.70043467 | 20.36476673 | 21.8483672 | 19.64492868 | 20.0776561 | 19.93493362 | 21.24366834 | 23.94609517 | 23.21801449 | 16.50463554 | 16.46741007 | 12.54532128 | 12.72967674 | 13.89136746 | .. | .. |
843 | Uganda | UGA | Domestic private health expenditure per capita, PPP (current international $) | SH.XPD.PVTD.PP.CD | .. | .. | .. | 21.29346958 | 21.82387742 | 23.69471597 | 23.06707237 | 21.03936962 | 37.63358866 | 52.52613282 | 54.41408135 | 55.8538215 | 52.12963126 | 54.71787446 | 58.74066533 | 53.0323036 | 59.44441478 | 56.21612253 | 47.52291095 | 46.47106786 | 35.65533639 | 36.58986951 | 39.59668872 | .. | .. |
844 | Uganda | UGA | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 0.150000005960464 | 0.159999996423721 | 0.159999996423721 | 0.159999996423721 | 0.159999996423721 | 0.170000001788139 | 0.189999997615814 | 0.259999990463257 | 0.349999994039536 | 0.479999989271164 | 0.660000026226044 | 0.899999976158142 | 1.29999995231628 | 1.66999995708466 | 1.95000004768372 | 2.59999990463257 | 2.79999995231628 | 2.98000001907349 | 3.04999995231628 | 3.22000002861023 | 3.25999999046326 | 3.28999996185303 | 3.36999988555908 | .. | .. |
845 | Uganda | UGA | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 0.349999994039536 | 0.349999994039536 | 0.349999994039536 | 0.349999994039536 | 0.360000014305115 | 0.360000014305115 | 0.400000005960464 | 0.540000021457672 | 0.689999997615814 | 0.899999976158142 | 1.16999995708466 | 1.55999994277954 | 2.25999999046326 | 2.79999995231628 | 3.03999996185303 | 3.96000003814697 | 4.28000020980835 | 4.55000019073486 | 4.59999990463257 | 4.86999988555908 | 4.94000005722046 | 4.94000005722046 | 5.01999998092651 | .. | .. |
846 | Uganda | UGA | Employers, total (% of total employment) (modeled ILO estimate) | SL.EMP.MPYR.ZS | 0.259999990463257 | 0.259999990463257 | 0.259999990463257 | 0.259999990463257 | 0.259999990463257 | 0.270000010728836 | 0.300000011920929 | 0.409999996423721 | 0.529999971389771 | 0.699999988079071 | 0.930000007152557 | 1.25 | 1.79999995231628 | 2.25999999046326 | 2.51999998092651 | 3.29999995231628 | 3.55999994277954 | 3.78999996185303 | 3.83999991416931 | 4.05999994277954 | 4.11999988555908 | 4.13000011444092 | 4.21000003814697 | .. | .. |
847 | Uganda | UGA | Employment in agriculture (% of total employment) (modeled ILO estimate) | SL.AGR.EMPL.ZS | 70.879997253418 | 70.5999984741211 | 70.1699981689453 | 69.9499969482422 | 69.6100006103516 | 69.0800018310547 | 68.6999969482422 | 68.5100021362305 | 68.3399963378906 | 67.9199981689453 | 67.6100006103516 | 67.2600021362305 | 67.0599975585938 | 66.8399963378906 | 66.4499969482422 | 66.1399993896484 | 71.9199981689453 | 72.3899993896484 | 72.2600021362305 | 72.4100036621094 | 72.6800003051758 | 72.4499969482422 | 72.129997253418 | .. | .. |
848 | Uganda | UGA | Employment in agriculture, female (% of female employment) (modeled ILO estimate) | SL.AGR.EMPL.FE.ZS | 78.2900009155273 | 78.0100021362305 | 77.5800018310547 | 77.3399963378906 | 77.0599975585938 | 76.620002746582 | 76.0100021362305 | 75.6100006103516 | 75.0999984741211 | 74.5500030517578 | 74.129997253418 | 73.4599990844727 | 72.7300033569336 | 72.5 | 71.7200012207031 | 71.1699981689453 | 77.1600036621094 | 77.4300003051758 | 77.2699966430664 | 77.3499984741211 | 77.3399963378906 | 77.1699981689453 | 76.7699966430664 | .. | .. |
849 | Uganda | UGA | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 64.3899993896484 | 64.0899963378906 | 63.6399993896484 | 63.4099998474121 | 63.0200004577637 | 62.4300003051758 | 62.2299995422363 | 62.1500015258789 | 62.2299995422363 | 61.8899993896484 | 61.6500015258789 | 61.5800018310547 | 61.8400001525879 | 61.6100006103516 | 61.5499992370605 | 61.439998626709 | 66.9800033569336 | 67.629997253418 | 67.4899978637695 | 67.6900024414063 | 68.1999969482422 | 67.9000015258789 | 67.6600036621094 | .. | .. |
850 | Uganda | UGA | Employment in industry (% of total employment) (modeled ILO estimate) | SL.IND.EMPL.ZS | 7.8899998664856 | 7.88000011444092 | 7.88000011444092 | 7.84999990463257 | 7.84000015258789 | 7.82000017166138 | 7.80000019073486 | 7.76999998092651 | 7.75 | 7.76000022888184 | 7.78000020980835 | 7.82000017166138 | 7.80000019073486 | 7.88000011444092 | 7.94000005722046 | 8.02000045776367 | 7 | 6.84000015258789 | 6.80000019073486 | 6.73000001907349 | 6.59000015258789 | 6.53999996185303 | 6.51000022888184 | .. | .. |
851 | Uganda | UGA | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 5.57000017166138 | 5.53999996185303 | 5.48999977111816 | 5.44000005722046 | 5.3600001335144 | 5.26999998092651 | 5.21999979019165 | 5.15999984741211 | 5.13000011444092 | 5.05000019073486 | 4.98000001907349 | 4.96999979019165 | 4.92000007629395 | 4.88000011444092 | 4.90000009536743 | 4.86999988555908 | 3.53999996185303 | 3.5 | 3.49000000953674 | 3.36999988555908 | 3.29999995231628 | 3.23000001907349 | 3.19000005722046 | .. | .. |
852 | Uganda | UGA | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 9.92000007629395 | 9.94999980926514 | 9.98999977111816 | 9.98999977111816 | 10.0299997329712 | 10.0799999237061 | 10.0799999237061 | 10.1099996566772 | 10.1199998855591 | 10.2200002670288 | 10.3400001525879 | 10.4399995803833 | 10.4499998092651 | 10.6400003433228 | 10.7600002288818 | 10.9499998092651 | 10.2700004577637 | 10 | 9.94999980926514 | 9.93000030517578 | 9.73999977111816 | 9.73999977111816 | 9.69999980926514 | .. | .. |
853 | Uganda | UGA | Employment in services (% of total employment) (modeled ILO estimate) | SL.SRV.EMPL.ZS | 21.2299995422363 | 21.5100002288818 | 21.9500007629395 | 22.2000007629395 | 22.5499992370605 | 23.0900001525879 | 23.5 | 23.7199993133545 | 23.9099998474121 | 24.3199996948242 | 24.6200008392334 | 24.9200000762939 | 25.1399993896484 | 25.2800006866455 | 25.6100006103516 | 25.8500003814697 | 21.0799999237061 | 20.7700004577637 | 20.9400005340576 | 20.8600006103516 | 20.7399997711182 | 21.0100002288818 | 21.3600006103516 | .. | .. |
854 | Uganda | UGA | Employment in services, female (% of female employment) (modeled ILO estimate) | SL.SRV.EMPL.FE.ZS | 16.1399993896484 | 16.4500007629395 | 16.9300003051758 | 17.2199993133545 | 17.5699996948242 | 18.1100006103516 | 18.7700004577637 | 19.2299995422363 | 19.7700004577637 | 20.3999996185303 | 20.8899993896484 | 21.5799999237061 | 22.3500003814697 | 22.6200008392334 | 23.3799991607666 | 23.9599990844727 | 19.3099994659424 | 19.0699996948242 | 19.2399997711182 | 19.2800006866455 | 19.3700008392334 | 19.6000003814697 | 20.0400009155273 | .. | .. |
855 | Uganda | UGA | Employment in services, male (% of male employment) (modeled ILO estimate) | SL.SRV.EMPL.MA.ZS | 25.6900005340576 | 25.9599990844727 | 26.3700008392334 | 26.5900001525879 | 26.9500007629395 | 27.4899997711182 | 27.6900005340576 | 27.7399997711182 | 27.6499996185303 | 27.8899993896484 | 28.0200004577637 | 27.9799995422363 | 27.7099990844727 | 27.75 | 27.6900005340576 | 27.6100006103516 | 22.75 | 22.3799991607666 | 22.5599994659424 | 22.3799991607666 | 22.0499992370605 | 22.3600006103516 | 22.6399993896484 | .. | .. |
856 | Uganda | UGA | Employment to population ratio, 15+, female (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.FE.ZS | 61.4500007629395 | 61.3930015563965 | 61.3540000915527 | 61.2550010681152 | 61.2000007629395 | 61.1570014953613 | 61.2159996032715 | 62.1749992370605 | 63.1380004882813 | 63.0050010681152 | 62.8320007324219 | 62.6679992675781 | 62.4780006408691 | 62.6450004577637 | 62.8530006408691 | 62.9850006103516 | 64.2470016479492 | 64.3290023803711 | 64.4089965820313 | 64.4970016479492 | 64.5950012207031 | 64.7220001220703 | 64.8560028076172 | 60.9309997558594 | 61.8009986877441 |
857 | Uganda | UGA | Employment to population ratio, 15+, female (%) (national estimate) | SL.EMP.TOTL.SP.FE.NE.ZS | 60.9000015258789 | .. | .. | .. | .. | .. | 35.7099990844727 | .. | 79 | .. | .. | .. | 75.4000015258789 | .. | .. | 62.9000015258789 | 81.7099990844727 | .. | .. | .. | 64.5500030517578 | .. | .. | .. | .. |
858 | Uganda | UGA | Employment to population ratio, 15+, male (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.MA.ZS | 74.995002746582 | 74.7720031738281 | 74.5699996948242 | 74.3089981079102 | 74.0930023193359 | 73.8889999389648 | 73.7559967041016 | 74.0370025634766 | 74.3170013427734 | 73.9889984130859 | 73.6289978027344 | 73.2900009155273 | 72.9339981079102 | 72.8679962158203 | 72.8320007324219 | 72.7170028686523 | 73.6340026855469 | 73.4240036010742 | 73.1900024414063 | 72.9120025634766 | 72.5950012207031 | 72.2590026855469 | 71.879997253418 | 69.2750015258789 | 69.7320022583008 |
859 | Uganda | UGA | Employment to population ratio, 15+, male (%) (national estimate) | SL.EMP.TOTL.SP.MA.NE.ZS | 58.7000007629395 | .. | .. | .. | .. | .. | 37.8499984741211 | .. | 82 | .. | .. | .. | 75.5 | .. | .. | 72.629997253418 | 86.9700012207031 | .. | .. | .. | 71.0599975585938 | .. | .. | .. | .. |
860 | Uganda | UGA | Employment to population ratio, 15+, total (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.ZS | 68.0260009765625 | 67.8789978027344 | 67.7529983520508 | 67.5699996948242 | 67.4349975585938 | 67.3140029907227 | 67.2819976806641 | 67.9130020141602 | 68.5439987182617 | 68.3109970092773 | 68.0400009155273 | 67.7829971313477 | 67.5039978027344 | 67.5510025024414 | 67.6389999389648 | 67.6500015258789 | 68.745002746582 | 68.6869964599609 | 68.6169967651367 | 68.5350036621094 | 68.4400024414063 | 68.3499984741211 | 68.2429962158203 | 64.9609985351563 | 65.6370010375977 |
861 | Uganda | UGA | Employment to population ratio, 15+, total (%) (national estimate) | SL.EMP.TOTL.SP.NE.ZS | 59.9000015258789 | .. | .. | .. | .. | 77.5 | 36.75 | .. | 80.4000015258789 | .. | .. | .. | 75.4000015258789 | .. | .. | 67.6500015258789 | 84.2099990844727 | .. | .. | .. | 67.6900024414063 | .. | .. | .. | .. |
862 | Uganda | UGA | Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate) | SL.EMP.1524.SP.FE.ZS | 50.6529998779297 | 50.3009986877441 | 49.9729995727539 | 49.601001739502 | 49.2620010375977 | 48.9370002746582 | 48.7599983215332 | 49.6339988708496 | 50.4910011291504 | 50.0390014648438 | 49.560001373291 | 49.0880012512207 | 48.5989990234375 | 48.5060005187988 | 48.4269981384277 | 48.2939987182617 | 49.4420013427734 | 49.185001373291 | 48.9020004272461 | 48.5620002746582 | 48.1730003356934 | 47.7760009765625 | 47.3409996032715 | 42.9150009155273 | 44.4850006103516 |
863 | Uganda | UGA | Employment to population ratio, ages 15-24, female (%) (national estimate) | SL.EMP.1524.SP.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 48.1199989318848 | .. | .. | .. | .. | 50.9700012207031 | .. | .. | .. | .. |
864 | Uganda | UGA | Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate) | SL.EMP.1524.SP.MA.ZS | 55.0309982299805 | 54.9039993286133 | 54.798999786377 | 54.6469993591309 | 54.5 | 54.3660011291504 | 54.3520011901855 | 54.8650016784668 | 55.3709983825684 | 55.0250015258789 | 54.6619987487793 | 54.3190002441406 | 53.9669990539551 | 53.9819984436035 | 54.0060005187988 | 53.9679985046387 | 54.9790000915527 | 54.4749984741211 | 53.9309997558594 | 53.2890014648438 | 52.5470008850098 | 51.7719993591309 | 50.9129981994629 | 47.3889999389648 | 48.6629981994629 |
865 | Uganda | UGA | Employment to population ratio, ages 15-24, male (%) (national estimate) | SL.EMP.1524.SP.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 53.5800018310547 | .. | .. | .. | .. | 53.9599990844727 | .. | .. | .. | .. |
866 | Uganda | UGA | Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) | SL.EMP.1524.SP.ZS | 52.8279991149902 | 52.5849990844727 | 52.3660011291504 | 52.0999984741211 | 51.8540000915527 | 51.6220016479492 | 51.523998260498 | 52.2190017700195 | 52.9010009765625 | 52.4949989318848 | 52.0660018920898 | 51.6500015258789 | 51.2220001220703 | 51.1759986877441 | 51.1459999084473 | 51.0589981079102 | 52.1399993896484 | 51.7649993896484 | 51.3580017089844 | 50.8769989013672 | 50.3230018615723 | 49.7470016479492 | 49.109001159668 | 45.1370010375977 | 46.5660018920898 |
867 | Uganda | UGA | Employment to population ratio, ages 15-24, total (%) (national estimate) | SL.EMP.1524.SP.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 50.810001373291 | .. | .. | .. | .. | 52.4099998474121 | .. | .. | .. | .. |
868 | Uganda | UGA | Exports of goods and services (annual % growth) | NE.EXP.GNFS.KD.ZG | 29.4956414134914 | -14.905425411063987 | 26.26666665223874 | -21.606199188175466 | 29.060055082046375 | 16.685866968485726 | 3.3016414972984194 | 23.694138151641212 | 14.78217604228422 | 7.763543790115676 | 12.138573115915193 | 84.44024270668834 | -8.564912902084274 | -8.960843393050695 | 5.489204278762344 | 13.987101700435801 | 6.946943691756061 | 0.0022858601009119184 | -2.3698752291894323 | 4.013332900409793 | 32.85466364539542 | 9.419934119439219 | 4.317491782156949 | -1.1700194157365758 | -0.6998285702998714 |
869 | Uganda | UGA | Exports of goods and services (constant 2015 US$) | NE.EXP.GNFS.KD | 962356725.103136 | 818913361.25453 | 1034014604.025901 | 810603349.045241 | 1046165128.7747008 | 1220726850.4327347 | 1261030874.6952858 | 1559821272.2804363 | 1790396798.6939282 | 1929395038.1773605 | 2163596065.5813594 | 3990541834.550619 | 3648755402.1001225 | 3321796144.7224536 | 3504136320.830321 | 3994263431.746766 | 4271742663.250617 | 4271840309.31177 | 4170603023.990861 | 4337983207.298172 | 5763212999.049723 | 6306103866.723164 | 6578369382.943217 | 6501401183.923911 | 6455902520.968997 |
870 | Uganda | UGA | External health expenditure (% of current health expenditure) | SH.XPD.EHEX.CH.ZS | .. | .. | .. | 31.54044151 | 29.40350533 | 24.20305634 | 18.9325428 | 30.85813522 | 32.58226776 | 29.81238365 | 28.98073578 | 29.28683472 | 41.77129745 | 45.63701248 | 50.18870926 | 46.01364517 | 37.431427 | 35.9745369 | 42.92503738 | 41.26190948 | 43.14041901 | 43.51276779 | 42.01983261 | .. | .. |
871 | Uganda | UGA | External health expenditure per capita (current US$) | SH.XPD.EHEX.PC.CD | .. | .. | .. | 5.24527785 | 4.76023286 | 3.85491269 | 2.73337387 | 5.81320988 | 8.51338912 | 9.49512195 | 10.52181345 | 11.77287372 | 18.55633043 | 23.6518187 | 27.60685191 | 25.16338422 | 19.60527239 | 18.07557388 | 16.89976907 | 15.77996221 | 13.2366662 | 13.94781313 | 13.61797324 | .. | .. |
872 | Uganda | UGA | External health expenditure per capita, PPP (current international $) | SH.XPD.EHEX.PP.CD | .. | .. | .. | 15.37725408 | 14.56513912 | 12.66910215 | 9.27201627 | 16.15063755 | 24.41329382 | 28.17682423 | 28.11398827 | 30.09652763 | 49.24093533 | 64.45858222 | 81.34688981 | 62.81741038 | 48.66864245 | 43.76509785 | 48.66064559 | 44.53108846 | 37.62022317 | 40.09125077 | 38.81739138 | .. | .. |
873 | Uganda | UGA | Female share of employment in senior and middle management (%) | SL.EMP.SMGT.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 31.5 | .. | .. | .. | .. | 25.3999996185303 | .. | .. | .. | .. |
874 | Uganda | UGA | Final consumption expenditure (annual % growth) | NE.CON.TOTL.KD.ZG | 3.0432537075953263 | 7.015809148106044 | 6.606988196678614 | 0.9022998596066998 | 3.8713312623901146 | 8.522331231752744 | 3.8552088200260073 | 2.6630270545135346 | 5.242964495885346 | 11.082716997663923 | 7.663421427941273 | 0.84309911403912 | 16.519976710138778 | 5.23457781138201 | 10.017380922651611 | 3.580395262246185 | 0.12379641718926848 | 2.9600066515616703 | 11.357783348090194 | 0.953890254516665 | 1.134760390627747 | 9.803452268812237 | 6.992365559558493 | 3.2252449698356003 | 6.610347191233032 |
875 | Uganda | UGA | Final consumption expenditure (constant 2015 US$) | NE.CON.TOTL.KD | 9853965209.857328 | 10545300602.501686 | 11242027368.613253 | 11343464165.777197 | 11782607240.26495 | 12786760057.01681 | 13279716358.530485 | 13633358797.92081 | 14348150959.29246 | 15938315924.508444 | 17159736242.3202 | 17304409826.55065 | 20163094299.723785 | 21218547160.025158 | 23344089855.29735 | 24179900542.49091 | 24209834393.042442 | 24926447101.40856 | 27757538959.562855 | 28022315418.591793 | 28340301554.498745 | 31118629490.23148 | 33294557821.313038 | 34368388872.67394 | 36640258701.19079 |
876 | Uganda | UGA | GDP (constant 2015 US$) | NY.GDP.MKTP.KD | 10452668548.4275 | 10965399690.913668 | 11848547321.286543 | 12220817699.079922 | 12854303475.460258 | 13976829405.107397 | 14881585726.567234 | 15894609992.306484 | 16901146520.038298 | 18723891970.577995 | 20299025520.45422 | 22066817291.41839 | 23567695697.643364 | 24896350853.11454 | 27234530355.52049 | 28279643367.39322 | 29294007543.00416 | 30789849595.778374 | 32387183844.66986 | 33935615198.680294 | 34998276925.53742 | 37204541627.54605 | 39600047203.88117 | 40768765939.9636 | 42146600779.21149 |
877 | Uganda | UGA | GDP growth (annual %) | NY.GDP.MKTP.KD.ZG | 5.100001863416111 | 4.905265484222227 | 8.053948376406964 | 3.1419073385019516 | 5.18366112627659 | 8.732685763877583 | 6.473258671449628 | 6.807233344298496 | 6.332565116218717 | 10.78474438629722 | 8.412425965452755 | 8.708751901330743 | 6.801517347989531 | 5.637611638052647 | 9.39165549281067 | 3.837455605915679 | 3.586905826332014 | 5.106307324384645 | 5.187859862460982 | 4.781000291463329 | 3.1314055178774254 | 6.303923780884119 | 6.43874503364799 | 2.9513064215940688 | 3.3796334215190598 |
878 | Uganda | UGA | GDP per capita (constant 2015 US$) | NY.GDP.PCAP.KD | 482.6820289573839 | 491.9251927226108 | 516.2224527261561 | 516.7330037434388 | 527.0538840813991 | 555.357589572715 | 572.7972442830874 | 592.6114689558852 | 610.4893198721129 | 655.3351540506045 | 688.4214508332154 | 725.1252029022858 | 750.2984199482681 | 767.738526705198 | 813.5351387977457 | 818.3074990492472 | 820.6864348838589 | 834.1526237405595 | 847.267628934983 | 855.8971759305117 | 850.1621976914245 | 870.7087403137532 | 894.520366857752 | 891.2959038928664 | 894.3854184110407 |
879 | Uganda | UGA | GDP per capita growth (annual %) | NY.GDP.PCAP.KD.ZG | 2.0784618395681633 | 1.914959167879644 | 4.939218475286793 | 0.09890135823933122 | 1.9973332965363966 | 5.370173021425757 | 3.1402568431252007 | 3.4592039103814614 | 3.0167912456582116 | 7.34588349356973 | 5.048759642772964 | 5.331581696742148 | 3.471568350572767 | 2.324422695456633 | 5.965131421642582 | 0.5866200516616971 | 0.29071416764180924 | 1.6408445764802195 | 1.572254863338145 | 1.0185148943287317 | -0.6700545813639991 | 2.416779136748488 | 2.734740728043988 | -0.36046836766976753 | 0.3466317420152336 |
880 | Uganda | UGA | GDP per capita, PPP (constant 2017 international $) | NY.GDP.PCAP.PP.KD | 1177.8898777149561 | 1200.445987915785 | 1259.7386379367606 | 1260.9845365599458 | 1286.1706005728327 | 1355.2401871743045 | 1397.7982098928283 | 1446.150900228683 | 1489.7782539857894 | 1599.2156288361227 | 1679.956182105719 | 1769.5244184241556 | 1830.954668089825 | 1873.5137939384276 | 1985.271353949457 | 1996.9173537916204 | 2002.722675455191 | 2035.5842418573363 | 2067.5888140972834 | 2088.647514122339 | 2074.652435765417 | 2124.7922029930405 | 2182.8997607545934 | 2175.0310976191345 | 2182.570445802185 |
881 | Uganda | UGA | GDP per capita, PPP (current international $) | NY.GDP.PCAP.PP.CD | 1016.0168220912497 | 1047.1277222290014 | 1114.332969146699 | 1140.705772596713 | 1189.7023322399832 | 1273.1290214732849 | 1339.024043920322 | 1422.5318914393588 | 1511.4005395929935 | 1672.4875701821911 | 1804.4088787244677 | 1937.0648844721552 | 2017.1581448094612 | 2088.850951610929 | 2259.4428885965053 | 2013.8807107731927 | 2014.27496126568 | 2088.407330590071 | 2128.744955489978 | 2092.475565899197 | 2074.652435765417 | 2175.55372017659 | 2275.028150358042 | 2294.1479835326704 | 2397.761004793073 |
882 | Uganda | UGA | GDP per person employed (constant 2017 PPP $) | SL.GDP.PCAP.EM.KD | 3421.7002904954475 | 3503.4633912941513 | 3689.516060913508 | 3707.132214778967 | 3794.4459770912504 | 4008.395698221528 | 4136.395880575276 | 4236.739548720389 | 4318.199894747281 | 4646.226584932282 | 4891.170105069474 | 5158.856941071688 | 5344.809440746459 | 5448.085353322316 | 5747.352027656384 | 5757.969234965533 | 5657.717065385672 | 5727.450176797216 | 5793.285305565991 | 5824.235637570382 | 5754.25424769784 | 5857.781256083588 | 5978.910421218166 | 6202.214476428505 | 6106.749840879842 |
883 | Uganda | UGA | GDP, PPP (constant 2017 international $) | NY.GDP.MKTP.PP.KD | 25507667034.74944 | 26758885821.635338 | 28914032671.81153 | 29822484786.184032 | 31368381336.9352 | 34107683508.304573 | 36315562088.63649 | 38787647140.30357 | 41243900152.51244 | 45691949358.90056 | 49535750770.890236 | 53849696407.9886 | 57512292851.01763 | 60754612566.097534 | 66460476474.29727 | 69010867754.47847 | 71486222590.76614 | 75136528810.84433 | 79034506631.06856 | 82813146623.45656 | 85406362066.3514 | 90790314035.04012 | 96636070871.00467 | 99488097436.19682 | 102850430427.58398 |
884 | Uganda | UGA | GDP, PPP (current international $) | NY.GDP.MKTP.PP.CD | 22002242560.98027 | 23341301018.001835 | 25576622727.040512 | 26977872894.130104 | 29015619248.740314 | 32041170370.092766 | 34788577107.20199 | 38154154619.86247 | 41842504264.41079 | 47785436799.27122 | 53205404675.04403 | 58948243304.99736 | 63361148133.791885 | 67737601230.39526 | 75638854428.5666 | 69597099319.39754 | 71898575876.12209 | 77086309835.29533 | 81372227472.59952 | 82964925710.61017 | 85406362066.3514 | 92959304527.14456 | 100714556629.72441 | 104936622914.76788 | 112990969835.47954 |
885 | Uganda | UGA | General government final consumption expenditure (annual % growth) | NE.CON.GOVT.KD.ZG | 7.000048361176141 | 7.999987085559596 | 0.8520685752707635 | -4.609404288598881 | 12.541468918559048 | 9.632009262931263 | 5.086310083513098 | 3.6938798151227275 | 4.1233755678587585 | 4.895302698599096 | 0.9079539465459874 | -1.3072194212979582 | -0.35460299372964244 | 18.405846820532673 | 49.23481639164004 | -27.07553874665662 | 0.14443706844011217 | 7.527744505116345 | 15.484794224386306 | -5.053855918272163 | 12.873426553231738 | 15.900213789311834 | 7.928306255929712 | 12.739407860040359 | 6.532580354937949 |
886 | Uganda | UGA | General government final consumption expenditure (constant 2015 US$) | NE.CON.GOVT.KD | 1195341149.2523313 | 1290968286.8208976 | 1301968221.9096098 | 1241955242.8527136 | 1397714673.6175013 | 1532342680.4496884 | 1610282380.7193758 | 1669764276.5472465 | 1738614928.767229 | 1823725392.2934182 | 1840283978.9669077 | 1816227429.3868175 | 1809787032.549273 | 2142893661.538156 | 3197943421.2645597 | 2332083011.1439176 | 2335451403.4788036 | 2511258218.173842 | 2900121385.7010517 | 2753553429.4127226 | 3108030107.752163 | 3602213539.520936 | 3887808060.926721 | 4383091786.623702 | 4669420779.6155815 |
887 | Uganda | UGA | Gini index | SI.POV.GINI | .. | .. | 43 | .. | .. | 45.2 | .. | .. | 42.9 | .. | .. | .. | 44.2 | .. | .. | 41 | .. | .. | .. | 42.8 | .. | .. | 42.7 | .. | .. |
888 | Uganda | UGA | GNI (constant 2015 US$) | NY.GNP.MKTP.KD | 10419206158.716291 | 10946893182.43079 | 11816005435.4121 | 12007275417.553127 | 12465817958.457397 | 13686288347.460379 | 14586208554.953781 | 15481416636.786186 | 16424036875.447706 | 18276204286.123146 | 19920922128.356197 | 21682762731.049488 | 23195128803.54336 | 24486818550.457222 | 26822667197.93766 | 27688745776.585052 | 28653385968.66278 | 30066847498.93458 | 31759208216.18977 | 33324358712.021496 | 34162627157.942867 | 36128700840.3767 | 38534703930.12345 | 40047587017.780655 | 41405419203.4562 |
889 | Uganda | UGA | GNI growth (annual %) | NY.GNP.MKTP.KD.ZG | 5.648923727307405 | 5.064560732134666 | 7.9393508139477404 | 1.6187364095805066 | 3.818872516523925 | 9.790535952556212 | 6.5753415728698315 | 6.137359674103763 | 6.088720824305653 | 11.277175183673904 | 8.999231002697101 | 8.84417192809272 | 6.974969431954264 | 5.568797474047813 | 9.539208381306125 | 3.228905508375334 | 3.4838710278219764 | 4.9329651016381035 | 5.628660328673149 | 4.92817857793402 | 2.515482602877441 | 5.755042413290283 | 6.65953392671635 | 3.926027537153459 | 3.390546813900869 |
890 | Uganda | UGA | GNI per capita (constant 2015 US$) | NY.GNP.PCAP.KD | 481.1368068846914 | 491.09496144890664 | 514.8046542664024 | 507.70379250106214 | 511.1251485387371 | 543.8131844168652 | 561.4280775132942 | 577.2060502953319 | 593.2555575302978 | 639.6661105568804 | 675.5984468180327 | 712.5050031999323 | 738.4374236270954 | 755.1096186160038 | 801.2321856461448 | 801.2091246657152 | 802.739097525387 | 814.5651913896439 | 830.8394200384307 | 840.4805495444128 | 829.8629742630812 | 845.5305245477291 | 870.4554648346607 | 875.529328562573 | 878.6569377863965 |
891 | Uganda | UGA | GNI per capita growth (annual %) | NY.GNP.PCAP.KD.ZG | 2.6116026439703717 | 2.069713732502265 | 4.82792426693679 | -1.379331306835013 | 0.6738882175413039 | 6.395309636315162 | 3.2391441769322995 | 2.810328413199855 | 2.7805507628955013 | 7.823028783714747 | 5.617358129207489 | 5.462794734908556 | 3.6396123972039334 | 2.2577667999296125 | 6.108062444586054 | -0.002878189474003534 | 0.19095799243551426 | 1.4732176245947812 | 1.9979037676558562 | 1.1604082899119277 | -1.2632743597799134 | 1.887968347854141 | 2.9478463004353017 | 0.5828975671806376 | 0.357224952013695 |
892 | Uganda | UGA | GNI per capita, Atlas method (current US$) | NY.GNP.PCAP.CD | 300 | 290 | 290 | 270 | 250 | 250 | 260 | 280 | 310 | 350 | 390 | 430 | 550 | 680 | 850 | 830 | 800 | 820 | 830 | 800 | 740 | 750 | 780 | 800 | 840 |
893 | Uganda | UGA | GNI per capita, PPP (constant 2017 international $) | NY.GNP.PCAP.PP.KD | 1174.5358860463439 | 1198.845416573012 | 1256.7247653627999 | 1239.390367233402 | 1247.7424728875294 | 1327.539467492503 | 1370.5403848502644 | 1409.05707070009 | 1448.2366178290742 | 1561.53258529814 | 1649.2494629186085 | 1739.3445757444342 | 1802.6499765533233 | 1843.3496092428832 | 1955.9425544474711 | 1955.8862587147519 | 1959.6211798487157 | 1988.4906644455384 | 2028.2187943499807 | 2051.75441337717 | 2025.8351259473238 | 2064.08225190492 | 2124.928224205641 | 2137.314379128871 | 2144.949399394095 |
894 | Uganda | UGA | GNI per capita, PPP (current international $) | NY.GNP.PCAP.PP.CD | 1010 | 1050 | 1110 | 1130 | 1170 | 1260 | 1320 | 1400 | 1480 | 1650 | 1780 | 1920 | 1980 | 2050 | 2220 | 1970 | 1970 | 2040 | 2090 | 2060 | 2030 | 2110 | 2220 | 2260 | 2360 |
895 | Uganda | UGA | GNI, Atlas method (current US$) | NY.GNP.ATLS.CD | 6449969346.166573 | 6469454514.800362 | 6572754408.069364 | 6398433460.210805 | 6050661894.462221 | 6302717143.101218 | 6628439184.009862 | 7556670917.853916 | 8665661438.83518 | 10044048114.553703 | 11401532674.532606 | 13210848504.534475 | 17246365451.266945 | 21935101853.655033 | 28599612797.197243 | 28539804200.070015 | 28694330694.716335 | 30240345439.582367 | 31764484074.352646 | 31612983281.629604 | 30589558122.252773 | 32026794792.68532 | 34751587486.248985 | 36526209778.65071 | 39490174876.00351 |
896 | Uganda | UGA | GNI, PPP (constant 2017 international $) | NY.GNP.MKTP.PP.KD | 25435035030.400906 | 26723207826.75528 | 28844857044.86172 | 29311779248.138348 | 30431158729.94966 | 33410532266.184837 | 35607388884.00038 | 37792742410.368324 | 40093836987.58461 | 44615289222.53117 | 48630322162.18817 | 52931271463.39748 | 56623211467.914185 | 59776443437.86413 | 65478642940.33558 | 67592886449.045494 | 69947735436.9124 | 73398232815.40143 | 77529570027.82909 | 81350365689.50493 | 83396719985.80159 | 88196236592.2774 | 94069694890.22713 | 97762897015.73369 | 101077593805.67783 |
897 | Uganda | UGA | GNI, PPP (current international $) | NY.GNP.MKTP.PP.CD | 21966385384.330723 | 23322677659.743866 | 25539726527.12875 | 26688015523.873722 | 28460693338.0073 | 31611638583.477436 | 34342397048.73605 | 37516397573.348465 | 41080720137.886894 | 47049184547.16854 | 52573873295.59468 | 58286886293.77864 | 62341532650.621506 | 66614102246.86919 | 74468592859.38593 | 68126892521.025085 | 70302250671.61586 | 75321006669.92789 | 79794449795.69475 | 81510174709.67325 | 83396719985.80159 | 90344063119.99931 | 98104959292.35353 | 103161497425.75815 | 111108380628.70268 |
898 | Uganda | UGA | Gross capital formation (annual % growth) | NE.GDI.TOTL.KD.ZG | -2.6570998853075736 | 3.7136506582276354 | 13.95879066130621 | -6.987483129257882 | 3.926258859832174 | 6.51940502330271 | 13.516910856169744 | 10.614276529884407 | 12.457399698122046 | 20.347842324813342 | 15.971501466169101 | 6.013270228014477 | 2.458463912928991 | 9.516875477480141 | 8.761994043499826 | 3.1186187746442613 | 13.029707439964056 | -2.1260938747790448 | -0.9678984608323447 | 11.878110798532788 | 2.1042752837242773 | 9.748869853180679 | 9.689959152085393 | 0.1462327968942958 | 4.544934579266439 |
899 | Uganda | UGA | Gross capital formation (constant 2015 US$) | NE.GDI.TOTL.KD | 2128604375.8329146 | 2207653306.247096 | 2515815009.7935333 | 2340022860.4208727 | 2431898215.300246 | 2590443509.710139 | 2940591449.697093 | 3252713957.782079 | 3657917536.539598 | 4402224829.246372 | 5105326232.393517 | 5412323294.769048 | 5545383309.821994 | 6073130534.16672 | 6605257869.824377 | 6811250681.866387 | 7698736718.716135 | 7535054348.904146 | 7462122673.8382225 | 8348481872.959164 | 8524156913.578045 | 9355165877.163671 | 10261677629.270662 | 10276683567.476221 | 10743752112.53624 |
900 | Uganda | UGA | Gross fixed capital formation (annual % growth) | NE.GDI.FTOT.KD.ZG | -1.72610664115102 | 1.9196797002655615 | 15.83584323965168 | -7.949508223563541 | 3.829903683567366 | 6.549614679835145 | 13.320362706362772 | 11.09653545042653 | 12.887505000193315 | 20.174773958306474 | 15.929493936516522 | 6.04713165805974 | 2.5050558757070576 | 10.75505055360324 | 8.943363292327476 | 3.04931165589133 | 12.966991035339362 | -2.4701409270680585 | -1.0677857048215174 | 12.165120692137648 | 1.9757073346383152 | 9.766575939130234 | 9.694319707668882 | -0.07332642889439 | 4.4125592683414965 |
901 | Uganda | UGA | Gross fixed capital formation (constant 2015 US$) | NE.GDI.FTOT.KD | 2072603601.4324684 | 2112390952.0361404 | 2446905871.8091693 | 2252388888.3068404 | 2338653213.3083663 | 2491825987.477648 | 2823746247.021076 | 3137084250.3518586 | 3541376139.976231 | 4255840771.2298346 | 4933774668.830689 | 5232126518.766882 | 5363194211.549679 | 5940008460.289769 | 6471244996.488471 | 6668573424.447679 | 7533286742.580832 | 7347203943.598949 | 7268751550.185117 | 8153003949.076762 | 8314083446.092024 | 9126084719.497257 | 10010796548.998037 | 10003455989.384773 | 10444864413.798834 |
902 | Uganda | UGA | Gross national expenditure (constant 2015 US$) | NE.DAB.TOTL.KD | 11982569585.690243 | 12752953908.748783 | 13757842378.406786 | 13683487026.19807 | 14214505455.565195 | 15377203566.726948 | 16220307808.227577 | 16886072755.70289 | 18006068495.832058 | 20340540753.754814 | 22265062474.713715 | 22716733121.3197 | 25708477609.54578 | 27291677694.19188 | 29949347725.121727 | 30991151224.357296 | 31908571111.758575 | 32461501450.312706 | 35219661633.40108 | 36370797291.55096 | 36864458468.07679 | 40473795367.39515 | 43556235450.5837 | 44645072440.15016 | 47384010813.72703 |
903 | Uganda | UGA | Gross value added at basic prices (GVA) (constant 2015 US$) | NY.GDP.FCST.KD | 10169319358.840414 | 10741403500.481047 | 11539502203.078812 | 12051385641.85342 | 12679222861.637064 | 13838288649.962713 | 14746970132.365326 | 15691999325.37689 | 16720660261.577421 | 18441325780.355537 | 19713420946.116478 | 21269356445.144653 | 22366751853.160866 | 23689181914.97405 | 25877763123.472607 | 26685748810.522705 | 27697299065.873413 | 29067677996.98415 | 30481476042.522923 | 32220767457.182026 | 33054502549.473076 | 35185276073.940216 | 37504382215.195694 | 38735040680.99136 | 39967254718.67016 |
904 | Uganda | UGA | Hospital beds (per 1,000 people) | SH.MED.BEDS.ZS | .. | .. | .. | .. | .. | .. | .. | 0.7 | 1 | 1.1 | .. | .. | 0.4 | 0.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
905 | Uganda | UGA | Households and NPISHs Final consumption expenditure (annual % growth) | NE.CON.PRVT.KD.ZG | 2.629391186357992 | 6.908484755724615 | 7.806443205854066 | 1.976958886951465 | 2.2900311915590663 | 8.299659773555135 | 3.6051330436747406 | 2.450634468760285 | 5.476439172417443 | 12.356463971519489 | 9.417547204238488 | 1.13328979795358 | 18.742287947780568 | 4.04111824890596 | 5.973229427112798 | 8.032206734976825 | 0.12177309245882384 | 2.512147283814656 | 10.933338457110082 | 1.597110927611638 | -0.039766986970676044 | 9.114628618905456 | 6.880045213750691 | 2.072271230561597 | 6.620756244606852 |
906 | Uganda | UGA | Households and NPISHs Final consumption expenditure (constant 2015 US$) | NE.CON.PRVT.KD | 8516875763.682303 | 9105262827.480299 | 9816059998.851292 | 10010119469.34707 | 10239354327.507444 | 11089185899.699356 | 11488965804.843937 | 11770518360.961525 | 12415123639.27781 | 13949193918.784773 | 15262865840.697094 | 15435838342.145056 | 18328867611.3838 | 19069558825.245247 | 20208627324.615383 | 21831826049.629505 | 21858411339.35037 | 22407526826.096893 | 24857417573.861805 | 25254418106.25601 | 25244375185.09817 | 27545306230.383 | 29440435753.29944 | 30050521433.56703 | 32040093207.91684 |
907 | Uganda | UGA | Households and NPISHs Final consumption expenditure per capita (constant 2015 US$) | NE.CON.PRVT.PC.KD | 393.29116844109694 | 408.4764433794326 | 427.67012980455974 | 423.2579532885487 | 419.83532047542866 | 440.61942830194357 | 442.2140917951586 | 438.8495899801484 | 448.44881880352904 | 488.22091692966336 | 517.6249756916966 | 507.22827400588693 | 583.5156062547982 | 588.0553651699142 | 603.661074097516 | 631.7315932684045 | 612.3743507461163 | 607.0602681089113 | 650.2844469064887 | 635.2728392767467 | 613.2247639872302 | 643.2397196264674 | 662.0569138324425 | 655.3192358202408 | .. |
908 | Uganda | UGA | Households and NPISHs Final consumption expenditure per capita growth (annual %) | NE.CON.PRVT.PC.KD.ZG | -0.321120779338429 | 3.861077023042796 | 4.698847812699498 | -1.0316775029453993 | -0.808639929037966 | 4.95053817839306 | 0.36191402166730313 | -0.7608309815166905 | 2.187361921385161 | 8.868815449720017 | 6.022695411526044 | -2.0085394202466205 | 15.040039398124279 | 0.7780012850476794 | 2.6537822545148657 | 4.650046255318756 | -3.064156158810931 | -0.8677833470213727 | 7.120245067631842 | -2.30846788680779 | -3.4706466145503896 | 4.894609187678228 | 2.9253781493627997 | -1.0176886414793813 | .. |
909 | Uganda | UGA | Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $) | NE.CON.PRVT.PP.KD | 21255133358.1377 | 22723541005.993576 | 24497441328.985428 | 24981745672.414528 | 25553835440.508774 | 27674716841.16516 | 28672427202.74942 | 29375083586.810196 | 30983792171.28864 | 34812293287.9444 | 38090757441.2145 | 38522436109.259026 | 45742422009.35614 | 47590927372.667816 | 50433642651.12789 | 54484577092.84593 | 54550924647.285 | 55921324219.10756 | 62035391865.68046 | 63026165888.15394 | 63001102280.97707 | 68743418779.70491 | 73472997073.2266 | 74995556853.80641 | 79960829867.38248 |
910 | Uganda | UGA | Households and NPISHs Final consumption expenditure, PPP (current international $) | NE.CON.PRVT.PP.CD | 13823516016.537117 | 17874305982.398457 | 18086313334.93233 | 20396898552.575066 | 22624552035.367573 | 24281160235.675735 | 26087567945.526566 | 31405010255.830868 | 30354329459.24247 | 34930480663.53941 | 39698314733.11779 | 39953095447.25449 | 46233730849.14877 | 48919769614.94047 | 49215036190.716896 | 53298843046.9198 | 51049407210.56475 | 52844704659.24872 | 62331139364.986565 | 61551262150.56769 | 63001102280.97707 | 71214892399.32458 | 76066997261.06384 | 78543407230.64929 | .. |
911 | Uganda | UGA | Imports of goods and services (annual % growth) | NE.IMP.GNFS.KD.ZG | 1.9574742646537118 | 3.093897954367037 | 8.868843823047683 | 1.844189246416292 | 7.069865643013813 | 9.413695542279129 | 0.5058076789665762 | 1.3108311703451392 | 12.578558755376818 | 19.516513811778637 | 16.35712534632738 | 17.36898068588954 | 16.838343541682903 | -2.0807671498327096 | 14.752820304658982 | 5.959924754265586 | 0.9379025117747659 | -6.456709381908098 | 14.157189733614501 | -8.718115059855123 | 2.414037578850767 | 8.414283887815316 | 7.094081020395677 | 0.44132796660257156 | 20.57480888045393 |
912 | Uganda | UGA | Imports of goods and services (constant 2015 US$) | NE.IMP.GNFS.KD | 2139031454.8839414 | 2205210905.309863 | 2400787616.470611 | 2445062683.522856 | 2617925330.1353903 | 2864368850.2385416 | 2878857047.8369746 | 2916594003.3696995 | 3283459493.739354 | 3924276319.339152 | 4566175115.8296995 | 5359273189.782055 | 6261686020.814865 | 6131394915.068083 | 7035948589.0570755 | 7455285830.713689 | 7525209143.779941 | 7039328258.985295 | 8035899316.581786 | 7335320368.068074 | 7512397758.282332 | 8144512232.446081 | 8722290528.931843 | 8760784436.364346 | 10563299090.574863 |
913 | Uganda | UGA | Income share held by fourth 20% | SI.DST.04TH.20 | .. | .. | 20.3 | .. | .. | 19.1 | .. | .. | 20.4 | .. | .. | .. | 19.6 | .. | .. | 20.6 | .. | .. | .. | 20.4 | .. | .. | 20.3 | .. | .. |
914 | Uganda | UGA | Income share held by highest 10% | SI.DST.10TH.10 | .. | .. | 34.9 | .. | .. | 37.5 | .. | .. | 34.5 | .. | .. | .. | 36.4 | .. | .. | 32.9 | .. | .. | .. | 34.2 | .. | .. | 34.5 | .. | .. |
915 | Uganda | UGA | Income share held by highest 20% | SI.DST.05TH.20 | .. | .. | 49.7 | .. | .. | 52.1 | .. | .. | 49.8 | .. | .. | .. | 51.2 | .. | .. | 48.3 | .. | .. | .. | 49.8 | .. | .. | 49.5 | .. | .. |
916 | Uganda | UGA | Income share held by lowest 10% | SI.DST.FRST.10 | .. | .. | 2.3 | .. | .. | 2.4 | .. | .. | 2.4 | .. | .. | .. | 2.3 | .. | .. | 2.5 | .. | .. | .. | 2.5 | .. | .. | 2.4 | .. | .. |
917 | Uganda | UGA | Income share held by lowest 20% | SI.DST.FRST.20 | .. | .. | 5.9 | .. | .. | 5.9 | .. | .. | 6.1 | .. | .. | .. | 5.9 | .. | .. | 6.4 | .. | .. | .. | 6.1 | .. | .. | 6.1 | .. | .. |
918 | Uganda | UGA | Income share held by second 20% | SI.DST.02ND.20 | .. | .. | 10 | .. | .. | 9.6 | .. | .. | 9.9 | .. | .. | .. | 9.8 | .. | .. | 10.4 | .. | .. | .. | 9.8 | .. | .. | 10 | .. | .. |
919 | Uganda | UGA | Income share held by third 20% | SI.DST.03RD.20 | .. | .. | 14.1 | .. | .. | 13.3 | .. | .. | 13.8 | .. | .. | .. | 13.5 | .. | .. | 14.3 | .. | .. | .. | 13.8 | .. | .. | 14.1 | .. | .. |
920 | Uganda | UGA | Industry (including construction), value added (annual % growth) | NV.IND.TOTL.KD.ZG | 11.359623302845705 | 8.713504448868264 | 10.384625303652001 | 10.17522128134938 | 3.2594914777532864 | 7.416359808233381 | 9.4687888402012 | 8.020691577802168 | 11.558077322799875 | 14.734832422162583 | 9.602454645724762 | 8.819368629920717 | 5.746860454081414 | 7.866218658359031 | 11.297059972677033 | 3.0565898688267055 | 2.1425314342962167 | 6.341763372343777 | 7.753654800045595 | 4.527155093831041 | 6.848101437414172 | 4.842582489412649 | 9.038936315837944 | 3.248208876111235 | 3.3501514399735726 |
921 | Uganda | UGA | Industry (including construction), value added (constant 2015 US$) | NV.IND.TOTL.KD | 2099704915.6053894 | 2282662796.8397713 | 2519708775.237445 | 2776094718.763433 | 2866581289.5358863 | 3079177272.163364 | 3370738066.07998 | 3641094570.2558284 | 4061935096.082265 | 4660454425.586995 | 5107972448.088658 | 5558463367.800383 | 5877900500.939105 | 6340269006.863756 | 7056532998.998209 | 7272222271.736002 | 7428031919.879836 | 7899100127.46078 | 8511569083.654051 | 8896901016.989643 | 9506169823.419426 | 9966513938.702164 | 10867380786.530563 | 11220376013.839457 | 11596275602.437548 |
922 | Uganda | UGA | Industry (including construction), value added per worker (constant 2015 US$) | NV.IND.EMPL.KD | 3532.2768043878136 | 3753.355565344338 | 4041.0457724192656 | 4351.575248996172 | 4378.396763491241 | 4585.535462315768 | 4875.251423336455 | 5064.363900430697 | 5431.552039826353 | 6035.5126215256705 | 6396.317848258086 | 6712.790352788338 | 6916.559804644352 | 7123.5231432881765 | 7586.737307543573 | 7457.588085509787 | 8282.103529610402 | 8686.2948874352 | 9059.79317178187 | 9189.088527514425 | 9609.425220948273 | 9884.619553791239 | 10502.136897961216 | .. | .. |
923 | Uganda | UGA | International migrant stock (% of population) | SM.POP.TOTL.ZS | .. | .. | .. | 2.67157473075183 | .. | .. | .. | .. | 2.3285014738211 | .. | .. | .. | .. | 1.59628750032014 | .. | .. | .. | .. | 1.92012616805897 | .. | .. | .. | .. | .. | .. |
924 | Uganda | UGA | International migrant stock, total | SM.POP.TOTL | .. | .. | .. | 634703 | .. | .. | .. | .. | 652968 | .. | .. | .. | .. | 529160 | .. | .. | .. | .. | 749471 | .. | .. | .. | .. | .. | .. |
925 | Uganda | UGA | Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.FE.ZS | 52.7360000610352 | 52.6549987792969 | 52.576000213623 | 52.4990005493164 | 52.4129981994629 | 52.3279991149902 | 52.2439994812012 | 52.1609992980957 | 52.0779991149902 | 51.9879989624023 | 51.8979988098145 | 51.806999206543 | 51.7130012512207 | 51.6129989624023 | 51.4949989318848 | 51.3730010986328 | 51.1430015563965 | 50.8959999084473 | 50.6269989013672 | 50.3009986877441 | 49.9259986877441 | 49.5340003967285 | 49.1059989929199 | 45.064998626709 | 46.9679985046387 |
926 | Uganda | UGA | Labor force participation rate for ages 15-24, female (%) (national estimate) | SL.TLF.ACTI.1524.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 59.9900016784668 | .. | .. | .. | .. | .. | .. | 51.2099990844727 | 74.5999984741211 | .. | .. | .. | 54.189998626709 | .. | .. | .. | .. |
927 | Uganda | UGA | Labor force participation rate for ages 15-24, male (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.MA.ZS | 57.101001739502 | 57.1150016784668 | 57.1310005187988 | 57.1440010070801 | 57.1230010986328 | 57.101001739502 | 57.0800018310547 | 57.060001373291 | 57.0419998168945 | 56.9830017089844 | 56.9280014038086 | 56.8730010986328 | 56.818000793457 | 56.7630004882813 | 56.6949996948242 | 56.625 | 56.1590003967285 | 55.6619987487793 | 55.1269989013672 | 54.4939994812012 | 53.7599983215332 | 52.9830017089844 | 52.1240005493164 | 49.0009994506836 | 50.3930015563965 |
928 | Uganda | UGA | Labor force participation rate for ages 15-24, male (%) (national estimate) | SL.TLF.ACTI.1524.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 59.5900001525879 | .. | .. | .. | .. | .. | .. | 56.2599983215332 | 77.0999984741211 | .. | .. | .. | 57.1500015258789 | .. | .. | .. | .. |
929 | Uganda | UGA | Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.ZS | 54.9049987792969 | 54.8680000305176 | 54.8339996337891 | 54.7999992370605 | 54.7430000305176 | 54.6879997253418 | 54.6339988708496 | 54.5810012817383 | 54.5289993286133 | 54.4480018615723 | 54.3689994812012 | 54.2890014648438 | 54.2070007324219 | 54.1240005493164 | 54.0289993286133 | 53.931999206543 | 53.5880012512207 | 53.2200012207031 | 52.8250007629395 | 52.3549995422363 | 51.8110008239746 | 51.2350006103516 | 50.5999984741211 | 47.0190010070801 | 48.673999786377 |
930 | Uganda | UGA | Labor force participation rate for ages 15-24, total (%) (national estimate) | SL.TLF.ACTI.1524.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 59.7999992370605 | .. | .. | .. | .. | .. | .. | 53.689998626709 | 75.8199996948242 | .. | .. | .. | 55.6199989318848 | .. | .. | .. | .. |
931 | Uganda | UGA | Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.FE.ZS | 63.0309982299805 | 63.2210006713867 | 63.4090003967285 | 63.5950012207031 | 63.7770004272461 | 63.9570007324219 | 64.1370010375977 | 64.3170013427734 | 64.4990005493164 | 64.6839981079102 | 64.8710021972656 | 65.0589981079102 | 65.2470016479492 | 65.4339981079102 | 65.6159973144531 | 65.7969970703125 | 65.8679962158203 | 65.9449996948242 | 66.0279998779297 | 66.1220016479492 | 66.2300033569336 | 66.3509979248047 | 66.4869995117188 | 63.0830001831055 | 64.1719970703125 |
932 | Uganda | UGA | Labor force participation rate, female (% of female population ages 15+) (national estimate) | SL.TLF.CACT.FE.NE.ZS | .. | .. | .. | .. | .. | 81.9000015258789 | 37.3800010681152 | .. | 75.5800018310547 | .. | .. | .. | 84.3300018310547 | .. | .. | 65.7200012207031 | 83.75 | .. | .. | .. | 67.3300018310547 | .. | .. | .. | .. |
933 | Uganda | UGA | Labor force participation rate, female (% of female population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.FE.ZS | 64.96 | 65.13 | 65.3 | 65.46 | 65.64 | 65.8 | 65.97 | 66.13 | 66.29 | 66.47 | 66.66 | 66.84 | 67.03 | 67.22 | 67.43 | 67.64 | 67.7 | 67.76 | 67.82 | 67.9 | 67.99 | 68.07 | 68.15 | .. | .. |
934 | Uganda | UGA | Labor force participation rate, male (% of male population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.MA.ZS | 76.484001159668 | 76.3820037841797 | 76.2779998779297 | 76.1719970703125 | 76.0599975585938 | 75.9469985961914 | 75.8330001831055 | 75.7200012207031 | 75.609001159668 | 75.5019989013672 | 75.3960037231445 | 75.2919998168945 | 75.1869964599609 | 75.0810012817383 | 74.9700012207031 | 74.8570022583008 | 74.6660003662109 | 74.4520034790039 | 74.2200012207031 | 73.9449996948242 | 73.6330032348633 | 73.2880020141602 | 72.9069976806641 | 70.8000030517578 | 71.3059997558594 |
935 | Uganda | UGA | Labor force participation rate, male (% of male population ages 15+) (national estimate) | SL.TLF.CACT.MA.NE.ZS | .. | .. | .. | .. | .. | 83 | 38.9000015258789 | .. | 78.1900024414063 | .. | .. | .. | 86.5599975585938 | .. | .. | 74.7699966430664 | 88.1699981689453 | .. | .. | .. | 73.379997253418 | .. | .. | .. | .. |
936 | Uganda | UGA | Labor force participation rate, male (% of male population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.MA.ZS | 77.67 | 77.56 | 77.46 | 77.35 | 77.28 | 77.2 | 77.12 | 77.04 | 76.96 | 76.94 | 76.91 | 76.88 | 76.84 | 76.8 | 76.77 | 76.75 | 76.49 | 76.17 | 75.83 | 75.42 | 74.99 | 74.47 | 73.9 | .. | .. |
937 | Uganda | UGA | Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.ZS | 69.5630035400391 | 69.6009979248047 | 69.6399993896484 | 69.6790008544922 | 69.7170028686523 | 69.7559967041016 | 69.7939987182617 | 69.8330001831055 | 69.8710021972656 | 69.9100036621094 | 69.947998046875 | 69.9869995117188 | 70.0250015258789 | 70.0630035400391 | 70.1019973754883 | 70.1399993896484 | 70.0839996337891 | 70.0210037231445 | 69.9540023803711 | 69.8759994506836 | 69.7880020141602 | 69.6910018920898 | 69.5830001831055 | 66.8099975585938 | 67.6220016479492 |
938 | Uganda | UGA | Labor force participation rate, total (% of total population ages 15+) (national estimate) | SL.TLF.CACT.NE.ZS | .. | .. | .. | .. | .. | 82.3000030517578 | 38.1199989318848 | .. | 76.8399963378906 | .. | .. | .. | 85.3899993896484 | .. | .. | 70.1399993896484 | 85.8499984741211 | .. | .. | .. | 70.25 | .. | .. | .. | .. |
939 | Uganda | UGA | Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.ZS | 71.18 | 71.21 | 71.23 | 71.26 | 71.31 | 71.36 | 71.41 | 71.45 | 71.49 | 71.57 | 71.64 | 71.71 | 71.78 | 71.85 | 71.94 | 72.04 | 71.94 | 71.82 | 71.68 | 71.53 | 71.37 | 71.17 | 70.94 | .. | .. |
940 | Uganda | UGA | Labor force with advanced education (% of total working-age population with advanced education) | SL.TLF.ADVN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 90.2799987792969 | 93.9400024414063 | .. | .. | .. | 65.2799987792969 | .. | .. | .. | .. |
941 | Uganda | UGA | Labor force with advanced education, female (% of female working-age population with advanced education) | SL.TLF.ADVN.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 89.6699981689453 | 88.5899963378906 | .. | .. | .. | 51.7700004577637 | .. | .. | .. | .. |
942 | Uganda | UGA | Labor force with advanced education, male (% of male working-age population with advanced education) | SL.TLF.ADVN.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 90.6800003051758 | 97.6100006103516 | .. | .. | .. | 71.1600036621094 | .. | .. | .. | .. |
943 | Uganda | UGA | Labor force with basic education (% of total working-age population with basic education) | SL.TLF.BASC.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 67.1699981689453 | 84.7900009155273 | .. | .. | .. | 36.1500015258789 | .. | .. | .. | .. |
944 | Uganda | UGA | Labor force with basic education, female (% of female working-age population with basic education) | SL.TLF.BASC.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 59.5999984741211 | 82.2099990844727 | .. | .. | .. | 34.3400001525879 | .. | .. | .. | .. |
945 | Uganda | UGA | Labor force with basic education, male (% of male working-age population with basic education) | SL.TLF.BASC.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 73.5500030517578 | 87.3899993896484 | .. | .. | .. | 37.6500015258789 | .. | .. | .. | .. |
946 | Uganda | UGA | Labor force with intermediate education (% of total working-age population with intermediate education) | SL.TLF.INTM.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 59.0200004577637 | 80.1999969482422 | .. | .. | .. | 24.9300003051758 | .. | .. | .. | .. |
947 | Uganda | UGA | Labor force with intermediate education, female (% of female working-age population with intermediate education) | SL.TLF.INTM.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 43.5900001525879 | 71.7900009155273 | .. | .. | .. | 21.4799995422363 | .. | .. | .. | .. |
948 | Uganda | UGA | Labor force with intermediate education, male (% of male working-age population with intermediate education) | SL.TLF.INTM.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 66.4300003051758 | 85.0999984741211 | .. | .. | .. | 27.7099990844727 | .. | .. | .. | .. |
949 | Uganda | UGA | Labor force, female (% of total labor force) | SL.TLF.TOTL.FE.ZS | 46.618165027134594 | 46.79919812043516 | 46.96663829117377 | 47.119476394678024 | 47.23987366313492 | 47.34416376059652 | 47.44429306411645 | 47.550934538586944 | 47.67498530467419 | 47.828653903133045 | 48.005390532682476 | 48.195539181015036 | 48.388641437959954 | 48.573953406819605 | 48.71056518756716 | 48.84256304831753 | 48.94979728326583 | 49.05325512367597 | 49.14912408859889 | 49.220145015570886 | 49.29284051401574 | 49.37279719995632 | 49.47158382620785 | 48.81345800093821 | 48.99797307772328 |
950 | Uganda | UGA | Labor force, total | SL.TLF.TOTL.IN | 7623110 | 7831600 | 8055073 | 8295714 | 8546674 | 8817750 | 9107304 | 9413897 | 9736089 | 10064402 | 10411587 | 10777707 | 11162258 | 11566242 | 11984747 | 12426422 | 12881275 | 13373455 | 13908256 | 14496926 | 15134634 | 15803182 | 16480192 | 16497309 | 17351430 |
951 | Uganda | UGA | Manufacturing, value added (annual % growth) | NV.IND.MANF.KD.ZG | 13.446091426475661 | 14.399897807237963 | 14.180890099523097 | 5.510551861771205 | 3.7077378193011867 | 6.747932839484122 | 4.425760100919462 | 6.306619073328079 | 9.45471397040032 | 7.287671909476174 | 5.634565817173254 | 7.256131404939154 | 10.037067262214606 | 6.285156637988436 | 10.309967041685326 | 2.510239896137236 | -0.0837736651650971 | 4.744724056212291 | 9.640572568572779 | 3.0107923602796802 | 3.5698101428673397 | 4.6246635754549175 | 7.701220738214616 | 1.2555954891245733 | 2.2051739954816867 |
952 | Uganda | UGA | Manufacturing, value added (constant 2015 US$) | NV.IND.MANF.KD | 1589112561.6156511 | 1817943146.5302863 | 2075743666.2115583 | 2190128597.4555774 | 2271332823.7547684 | 2424600837.2628984 | 2531907853.725039 | 2691585637.347154 | 2946067360.626704 | 3160767084.1013427 | 3338862585.782581 | 3581134842.437314 | 3940575755.323351 | 4188247113.9840193 | 4620054011.060108 | 4736028450.068828 | 4732060905.452943 | 4956584137.588586 | 5434427228.29518 | 5598046548.109651 | 5797886181.586504 | 6066018911.97267 | 6533176418.40553 | 6615206686.81158 | 6761083504.416513 |
953 | Uganda | UGA | Multidimensional poverty headcount ratio (% of total population) | SI.POV.MDIM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
954 | Uganda | UGA | Multidimensional poverty headcount ratio, children (% of population ages 0-17) | SI.POV.MDIM.17 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
955 | Uganda | UGA | Multidimensional poverty headcount ratio, female (% of female population) | SI.POV.MDIM.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
956 | Uganda | UGA | Multidimensional poverty headcount ratio, household (% of total households) | SI.POV.MDIM.HH | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
957 | Uganda | UGA | Multidimensional poverty headcount ratio, male (% of male population) | SI.POV.MDIM.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
958 | Uganda | UGA | Multidimensional poverty index (scale 0-1) | SI.POV.MDIM.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
959 | Uganda | UGA | Multidimensional poverty index, children (population ages 0-17) (scale 0-1) | SI.POV.MDIM.17.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
960 | Uganda | UGA | Multidimensional poverty intensity (average share of deprivations experienced by the poor) | SI.POV.MDIM.IT | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
961 | Uganda | UGA | Net bilateral aid flows from DAC donors, Australia (current US$) | DC.DAC.AUSL.CD | 2029999.97138977 | 2000000 | 699999.988079071 | 1490000.0095367401 | 270000.010728836 | 600000.023841858 | 469999.998807907 | 560000.002384186 | 330000.013113022 | 2779999.97138977 | 3039999.96185303 | 1080000.04291534 | 1789999.96185303 | 2519999.98092651 | 11090000.1525879 | 7929999.82833862 | 6659999.84741211 | 3579999.92370605 | 3720000.02861023 | 1399999.97615814 | 7239999.771118159 | 1090000.0333786 | 899999.976158142 | 1720000.02861023 | .. |
962 | Uganda | UGA | Net bilateral aid flows from DAC donors, Austria (current US$) | DC.DAC.AUTL.CD | 11100000.3814697 | 12779999.7329712 | 4619999.88555908 | 4519999.98092651 | 1830000.04291534 | 5380000.11444092 | 5420000.07629395 | 8130000.11444092 | 8420000.07629395 | 10300000.1907349 | 10260000.2288818 | 14229999.5422363 | 11189999.5803833 | 13069999.6948242 | 13069999.6948242 | 8189999.580383301 | 17430000.3051758 | 10850000.3814697 | 9560000.4196167 | 10649999.6185303 | 13159999.8474121 | 6989999.771118159 | 13760000.2288818 | 11409999.8474121 | .. |
963 | Uganda | UGA | Net bilateral aid flows from DAC donors, Belgium (current US$) | DC.DAC.BELL.CD | 2819999.9332428 | 8590000.15258789 | 2119999.8855590797 | 6730000.01907349 | 3529999.97138977 | 2140000.10490417 | 6639999.8664856 | 8140000.34332275 | 13319999.6948242 | 14850000.3814697 | 15000000 | 17030000.6866455 | 22159999.8474121 | 28299999.237060502 | 14159999.8474121 | 21559999.4659424 | 15680000.3051758 | 24170000.0762939 | 16799999.237060502 | 18389999.3896484 | 22340000.1525879 | 26139999.3896484 | 34049999.237060495 | 23500000 | .. |
964 | Uganda | UGA | Net bilateral aid flows from DAC donors, Canada (current US$) | DC.DAC.CANL.CD | 3160000.08583069 | 3460000.03814697 | 2619999.8855590797 | 1610000.01430511 | 2599999.90463257 | 6429999.82833862 | 6739999.771118159 | 10159999.8474121 | 12829999.923706101 | 14109999.6566772 | 19989999.7711182 | 21200000.762939498 | 16850000.3814697 | 5730000.01907349 | 6400000.09536743 | 13590000.1525879 | 12359999.6566772 | 7320000.17166138 | 8710000.03814697 | 5969999.79019165 | 18670000.0762939 | 15539999.961853001 | 14050000.1907349 | 14659999.8474121 | .. |
965 | Uganda | UGA | Net bilateral aid flows from DAC donors, Czech Republic (current US$) | DC.DAC.CZEL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 39999.9991059303 | 330000.013113022 | 90000.0035762787 | 50000.0007450581 | 300000.011920929 | 140000.000596046 | 19999.9995529652 | 50000.0007450581 | 9999.99977648258 | 9999.99977648258 | 79999.9982118607 | 79999.9982118607 | 170000.00178813902 | 9999.99977648258 | 59999.9986588955 | 19999.9995529652 | .. |
966 | Uganda | UGA | Net bilateral aid flows from DAC donors, Denmark (current US$) | DC.DAC.DNKL.CD | 58360000.6103516 | 70779998.7792969 | 58900001.5258789 | 59810001.373291 | 58680000.3051758 | 43090000.1525879 | 53009998.3215332 | 61310001.373291 | 63720001.220703095 | 78500000 | 109849998.47412099 | 82580001.8310547 | 93470001.2207031 | 77010002.1362305 | 68180000.3051758 | 62900001.5258789 | 55240001.6784668 | 50240001.6784668 | 29280000.6866455 | 41500000 | 46409999.8474121 | 37470001.220703095 | 29129999.1607666 | 68500000 | .. |
967 | Uganda | UGA | Net bilateral aid flows from DAC donors, European Union institutions (current US$) | DC.DAC.CECL.CD | 53959999.0844727 | 55909999.8474121 | 60380001.0681152 | 36139999.3896484 | 63270000.4577637 | 33490001.678466797 | 89379997.253418 | 112690002.441406 | 83199996.9482422 | 155470001.220703 | 116349998.47412099 | 258890014.648438 | 128039993.286133 | 128940002.441406 | 171759994.506836 | 120599998.47412099 | 67959999.0844727 | 148009994.506836 | 106220001.22070299 | 70330001.8310547 | 150820007.32421902 | 86779998.7792969 | 144880004.882813 | 166100006.10351598 | .. |
968 | Uganda | UGA | Net bilateral aid flows from DAC donors, Finland (current US$) | DC.DAC.FINL.CD | 1080000.04291534 | 1129999.99523163 | 1169999.95708466 | 699999.988079071 | 759999.990463257 | 779999.971389771 | 1029999.97138977 | 2420000.07629395 | 5329999.92370605 | 6070000.17166138 | 6099999.90463257 | 5610000.1335144 | 4570000.17166138 | 5849999.90463257 | 4889999.8664856 | 3430000.0667572 | 4139999.8664856004 | 4650000.09536743 | 6119999.88555908 | 3069999.9332428 | 4940000.05722046 | 5320000.17166138 | 4949999.80926514 | 6780000.20980835 | .. |
969 | Uganda | UGA | Net bilateral aid flows from DAC donors, France (current US$) | DC.DAC.FRAL.CD | 5150000.09536743 | 2920000.07629395 | 1559999.9427795399 | 7579999.92370605 | 6519999.98092651 | 5480000.01907349 | 4650000.09536743 | 6179999.82833862 | 7630000.11444092 | 5389999.8664856 | 8979999.54223633 | 17440000.5340576 | 14569999.6948242 | 1769999.98092651 | 600000.023841858 | -140000.000596046 | 2579999.92370605 | 7289999.96185303 | 8260000.22888184 | 11829999.923706101 | 51389999.3896484 | 59700000.762939505 | 13949999.8092651 | 77660003.6621094 | .. |
970 | Uganda | UGA | Net bilateral aid flows from DAC donors, Germany (current US$) | DC.DAC.DEUL.CD | 38549999.237060495 | 28280000.6866455 | 28590000.1525879 | 18260000.2288818 | 33209999.084472697 | 33860000.6103516 | 26670000.0762939 | 41750000 | 51380001.0681152 | 54560001.373291 | 47580001.8310547 | 37840000.1525879 | 60060001.373291 | 40939998.626709 | 61880001.0681152 | 47470001.220703095 | 42069999.6948242 | 45270000.4577637 | 47740001.6784668 | 39540000.9155273 | 64239997.8637695 | 52630001.0681152 | 66519996.643066406 | 60840000.1525879 | .. |
971 | Uganda | UGA | Net bilateral aid flows from DAC donors, Greece (current US$) | DC.DAC.GRCL.CD | .. | 79999.9982118607 | 79999.9982118607 | 100000.00149011599 | 70000.0002980232 | 59999.9986588955 | 170000.00178813902 | 70000.0002980232 | 59999.9986588955 | 29999.999329447703 | 180000.00715255702 | 270000.010728836 | 219999.998807907 | 189999.99761581398 | 200000.00298023198 | 180000.00715255702 | 39999.9991059303 | 50000.0007450581 | 39999.9991059303 | 0 | 9999.99977648258 | 9999.99977648258 | 19999.9995529652 | .. | .. |
972 | Uganda | UGA | Net bilateral aid flows from DAC donors, Hungary (current US$) | DC.DAC.HUNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | 50000.0007450581 | 29999.999329447703 | 720000.028610229 | 70000.0002980232 | 340000.00357627904 | 8180000.305175779 | 1110000.01430511 | .. |
973 | Uganda | UGA | Net bilateral aid flows from DAC donors, Iceland (current US$) | DC.DAC.ISLL.CD | .. | .. | .. | .. | 360000.01430511504 | 479999.989271164 | 959999.978542328 | 1220000.02861023 | 1610000.01430511 | 2279999.97138977 | 2559999.94277954 | 3200000.04768372 | 3170000.07629395 | 3069999.9332428 | 3319999.9332428 | 2970000.02861023 | 4170000.07629395 | 3329999.92370605 | 3380000.1144409203 | 4920000.07629395 | 5170000.07629395 | 8149999.61853027 | 6380000.11444092 | 5519999.98092651 | .. |
974 | Uganda | UGA | Net bilateral aid flows from DAC donors, Ireland (current US$) | DC.DAC.IRLL.CD | 9810000.4196167 | 8720000.26702881 | 11930000.3051758 | 13020000.4577637 | 23489999.7711182 | 37009998.3215332 | 44400001.5258789 | 47619998.9318848 | 47750000 | 57630001.0681152 | 65849998.474121094 | 80870002.746582 | 64459999.0844727 | 58009998.3215332 | 59479999.5422363 | 30629999.1607666 | 31670000.0762939 | 37040000.9155273 | 25450000.762939498 | 26389999.3896484 | 28049999.237060502 | 31049999.237060502 | 23760000.2288818 | 25940000.5340576 | .. |
975 | Uganda | UGA | Net bilateral aid flows from DAC donors, Italy (current US$) | DC.DAC.ITAL.CD | 73349998.4741211 | 3480000.01907349 | 3640000.10490417 | 82089996.3378906 | 3740000.00953674 | 26680000.3051758 | 8850000.38146973 | 8229999.54223633 | 3920000.07629395 | 9560000.4196167 | 13279999.7329712 | 12399999.6185303 | 8949999.80926514 | 11399999.6185303 | 9289999.96185303 | 5760000.228881841 | 3349999.90463257 | 7079999.92370605 | 3460000.03814697 | 4050000.1907348596 | 4199999.80926514 | 6900000.09536743 | 6550000.19073486 | 5860000.1335144 | .. |
976 | Uganda | UGA | Net bilateral aid flows from DAC donors, Japan (current US$) | DC.DAC.JPNL.CD | 26860000.6103516 | 23909999.8474121 | 28219999.3133545 | 22370000.8392334 | 14569999.6948242 | 8079999.923706049 | 9539999.96185303 | 11840000.1525879 | 14439999.5803833 | 21780000.6866455 | 27510000.2288818 | 57009998.3215332 | 54049999.237060495 | 71239997.8637695 | 58000000 | 68870002.746582 | 57509998.3215332 | 85730003.3569336 | 70480003.3569336 | 66839996.337890595 | 64220001.220703095 | 71389999.3896484 | 65139999.38964839 | 42409999.8474121 | .. |
977 | Uganda | UGA | Net bilateral aid flows from DAC donors, Korea, Rep. (current US$) | DC.DAC.KORL.CD | 340000.00357627904 | 150000.005960464 | -39999.9991059303 | 19999.9995529652 | 140000.000596046 | 280000.001192093 | 129999.995231628 | 209999.993443489 | 119999.997317791 | 159999.99642372102 | 1289999.96185303 | 680000.007152557 | 1240000.0095367401 | 1879999.99523163 | 2410000.08583069 | 3990000.00953674 | 11420000.076293899 | 12159999.8474121 | 22950000.762939498 | 27700000.762939498 | 28940000.5340576 | 24370000.8392334 | 27090000.1525879 | 23360000.6103516 | .. |
978 | Uganda | UGA | Net bilateral aid flows from DAC donors, Luxembourg (current US$) | DC.DAC.LUXL.CD | 59999.9986588955 | 100000.00149011599 | .. | .. | .. | 50000.0007450581 | 109999.999403954 | 109999.999403954 | 109999.999403954 | 109999.999403954 | 1549999.95231628 | 1620000.00476837 | 1039999.96185303 | 270000.010728836 | 790000.021457672 | 280000.001192093 | 289999.99165535 | 109999.999403954 | 79999.9982118607 | 79999.9982118607 | 230000.004172325 | 360000.01430511504 | 330000.013113022 | 500000 | .. |
979 | Uganda | UGA | Net bilateral aid flows from DAC donors, Netherlands (current US$) | DC.DAC.NLDL.CD | 33349998.4741211 | 35319999.6948242 | 26450000.762939498 | 43330001.8310547 | 40819999.6948242 | 43500000 | 57770000.4577637 | 70919998.1689453 | 80120002.746582 | 82379997.253418 | 70430000.3051758 | 82849998.4741211 | 45009998.3215332 | 36650001.5258789 | 14859999.6566772 | 25819999.6948242 | 36169998.1689453 | 21920000.0762939 | 14689999.5803833 | 17229999.5422363 | 19069999.6948242 | 30430000.3051758 | 32669998.168945298 | 36759998.3215332 | .. |
980 | Uganda | UGA | Net bilateral aid flows from DAC donors, New Zealand (current US$) | DC.DAC.NZLL.CD | 340000.00357627904 | 50000.0007450581 | 270000.010728836 | 409999.99642372096 | 330000.013113022 | 219999.998807907 | 460000.00834465 | 209999.993443489 | 560000.002384186 | 150000.005960464 | 730000.019073486 | 159999.99642372102 | 200000.00298023198 | .. | .. | .. | .. | 29999.999329447703 | 119999.997317791 | 50000.0007450581 | 29999.999329447703 | 109999.999403954 | 90000.0035762787 | 189999.99761581398 | .. |
981 | Uganda | UGA | Net bilateral aid flows from DAC donors, Norway (current US$) | DC.DAC.NORL.CD | 27809999.4659424 | 31290000.915527303 | 25450000.762939498 | 21000000 | 19729999.5422363 | 32619998.931884803 | 38369998.9318848 | 41669998.1689453 | 45529998.779296905 | 50459999.0844727 | 69769996.6430664 | 74980003.3569336 | 67319999.6948242 | 71449996.9482422 | 80970001.2207031 | 52569999.6948242 | 69970001.2207031 | 65069999.694824204 | 44599998.4741211 | 43700000.762939505 | 29870000.8392334 | 35349998.4741211 | 35540000.9155273 | 33189998.626709 | .. |
982 | Uganda | UGA | Net bilateral aid flows from DAC donors, Poland (current US$) | DC.DAC.POLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | 19999.9995529652 | 29999.999329447703 | 9999.99977648258 | 29999.999329447703 | 189999.99761581398 | .. | 79999.9982118607 | 360000.01430511504 | 230000.004172325 | 50000.0007450581 | 9999.99977648258 | 289999.99165535 | 349999.99403953605 | 589999.973773956 | .. |
983 | Uganda | UGA | Net bilateral aid flows from DAC donors, Portugal (current US$) | DC.DAC.PRTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 50000.0007450581 | 39999.9991059303 | 29999.999329447703 | .. |
984 | Uganda | UGA | Net bilateral aid flows from DAC donors, Slovak Republic (current US$) | DC.DAC.SVKL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 39999.9991059303 | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | 19999.9995529652 | 9999.99977648258 | 50000.0007450581 | 9999.99977648258 | 79999.9982118607 | 140000.000596046 | .. |
985 | Uganda | UGA | Net bilateral aid flows from DAC donors, Slovenia (current US$) | DC.DAC.SVNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29999.999329447703 | 50000.0007450581 | 119999.997317791 | 59999.9986588955 | 39999.9991059303 | 39999.9991059303 | 29999.999329447703 | 29999.999329447703 | 79999.9982118607 | 59999.9986588955 | 59999.9986588955 | 59999.9986588955 | .. |
986 | Uganda | UGA | Net bilateral aid flows from DAC donors, Spain (current US$) | DC.DAC.ESPL.CD | -879999.995231628 | -1029999.97138977 | -4750000 | -3210000.03814697 | -2309999.94277954 | 2779999.97138977 | 9770000.45776367 | 3279999.97138977 | -550000.011920929 | 2740000.00953674 | 2650000.09536743 | 11460000.038146999 | 5889999.8664856 | 4289999.96185303 | 2319999.9332428 | 460000.00834465 | 529999.971389771 | 189999.99761581398 | 150000.005960464 | 219999.998807907 | 560000.002384186 | 709999.978542328 | 1080000.04291534 | 1690000.0572204601 | .. |
987 | Uganda | UGA | Net bilateral aid flows from DAC donors, Sweden (current US$) | DC.DAC.SWEL.CD | 31329999.9237061 | 9649999.61853027 | 20340000.1525879 | 22649999.6185303 | 29399999.6185303 | 23409999.8474121 | 32919998.168945298 | 42740001.6784668 | 47930000.3051758 | 62590000.1525879 | 56549999.237060495 | 64069999.694824204 | 52650001.5258789 | 43290000.9155273 | 41159999.8474121 | 34389999.3896484 | 41310001.373291 | 36009998.3215332 | 41759998.3215332 | 42610000.6103516 | 54549999.237060495 | 59729999.5422363 | 53759998.3215332 | 72959999.0844727 | .. |
988 | Uganda | UGA | Net bilateral aid flows from DAC donors, Switzerland (current US$) | DC.DAC.CHEL.CD | 330000.013113022 | 1120000.00476837 | 1769999.98092651 | 1210000.03814697 | 360000.01430511504 | 569999.992847443 | 1620000.00476837 | 3160000.08583069 | 3349999.90463257 | 3569999.9332428 | 4440000.05722046 | 3759999.99046326 | 3339999.91416931 | 1789999.96185303 | 1399999.97615814 | 2079999.9237060498 | 1370000.00476837 | 1139999.98569489 | 2400000.09536743 | 2029999.97138977 | 3150000.09536743 | 3480000.01907349 | 3599999.90463257 | 2900000.09536743 | .. |
989 | Uganda | UGA | Net bilateral aid flows from DAC donors, Total (current US$) | DC.DAC.TOTL.CD | 493089997.13882816 | 439999997.26936245 | 417800002.463162 | 614320005.502552 | 450070002.75701284 | 500320001.61707395 | 677750001.1026862 | 797970006.8458905 | 775650008.7659808 | 1096440006.3082569 | 1121750005.0552194 | 1267850029.1872778 | 1144809996.3888528 | 1129819984.2590833 | 1161569990.2437627 | 1043690009.7522883 | 1029239982.4541065 | 1177080009.6858294 | 1064690006.7627431 | 1127820022.2402806 | 1438279989.2108881 | 1319139976.082369 | 1299699993.4054914 | 1441230016.5873022 | .. |
990 | Uganda | UGA | Net bilateral aid flows from DAC donors, United Kingdom (current US$) | DC.DAC.GBRL.CD | 78180000.3051758 | 105559997.558594 | 96379997.253418 | 216570007.32421902 | 82220001.2207031 | 83980003.3569336 | 104650001.52587901 | 107639999.38964799 | 55630001.0681152 | 214410003.66210902 | 166130004.882813 | 65660003.662109405 | 117349998.47412099 | 179259994.506836 | 142979995.727539 | 149220001.220703 | 88089996.3378906 | 135300003.05175802 | 188460006.71386698 | 149720001.220703 | 180660003.66210902 | 143270004.272461 | 196229995.727539 | 114569999.69482401 | .. |
991 | Uganda | UGA | Net bilateral aid flows from DAC donors, United States (current US$) | DC.DAC.USAL.CD | 36000000 | 35750000 | 47400001.5258789 | 57919998.1689453 | 66480003.356933594 | 109349998.47412099 | 174020004.272461 | 207710006.71386698 | 228820007.32421902 | 246220001.220703 | 301570007.324219 | 352880004.88281304 | 366880004.88281304 | 342679992.675781 | 392029998.779297 | 380820007.324219 | 459079986.57226604 | 470070007.324219 | 409869995.11718804 | 538710021.972656 | 639979980.46875 | 611409973.144531 | 516500000 | 642260009.765625 | .. |
992 | Uganda | UGA | Net migration | SM.POP.NETM | -180002 | .. | .. | .. | .. | -250002 | .. | .. | .. | .. | -500000 | .. | .. | .. | .. | -299994 | .. | .. | .. | .. | 843469 | .. | .. | .. | .. |
993 | Uganda | UGA | Net ODA provided to the least developed countries (% of GNI) | DC.ODA.TLDC.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
994 | Uganda | UGA | Net ODA provided, to the least developed countries (current US$) | DC.ODA.TLDC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
995 | Uganda | UGA | Net ODA provided, total (% of GNI) | DC.ODA.TOTL.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
996 | Uganda | UGA | Net ODA provided, total (constant 2020 US$) | DC.ODA.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
997 | Uganda | UGA | Net ODA provided, total (current US$) | DC.ODA.TOTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
998 | Uganda | UGA | Net ODA received (% of central government expense) | DT.ODA.ODAT.XP.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 46.972063645457425 | 53.349619508509626 | 58.12419568805669 | 49.920132515250025 | 42.44481605740062 | 59.96533112773823 | .. |
999 | Uganda | UGA | Net ODA received (% of GNI) | DT.ODA.ODAT.GN.ZS | 13.009205018958173 | 10.007122391012883 | 10.154124310890596 | 14.064862160089453 | 14.646131167079263 | 12.126275434883368 | 15.513790593662238 | 15.822328600740363 | 13.330199755881884 | 16.335090417494573 | 14.889078988239133 | 11.590888410105496 | 7.225327693664889 | 6.443283812290755 | 5.732110981378834 | 6.144915260149768 | 6.002344366167966 | 5.121861514099798 | 5.154662373541674 | 6.143194856652245 | 6.701332431400182 | 6.079463816740163 | 5.889038037223304 | 8.339367756949697 | .. |
1000 | Uganda | UGA | Net ODA received (% of gross capital formation) | DT.ODA.ODAT.GI.ZS | 71.37477821848212 | 60.76558981136404 | 51.82036505250183 | 70.93257211816262 | 73.53077339778463 | 58.67847234118078 | 72.39696251874031 | 76.41557341486663 | 57.87285396451044 | 75.37919307257653 | 66.12833064910149 | 49.52829170983425 | 27.246178310563284 | 24.196150747032586 | 21.723588067808866 | 23.65400637086634 | 19.04341379860143 | 19.16925170044855 | 21.93852912381351 | 23.74727844011422 | 26.584841058981684 | 24.2857738844386 | 22.469756850077736 | 33.85467019085969 | .. |
1001 | Uganda | UGA | Net ODA received (% of imports of goods, services and primary income) | DT.ODA.ODAT.MP.ZS | 46.030919805869644 | 33.67342636903835 | 38.68601939621728 | 54.3792879717777 | 50.26313107931796 | 43.52635044779965 | 57.79641215672703 | 54.6789341409878 | 45.21708412019411 | 48.34497749852378 | 40.761848677793125 | 28.929585893434513 | 31.679721501777834 | 26.002306745644898 | 19.965594455510416 | 19.841168143368755 | 21.162773699521868 | 19.50819312809397 | 20.988164844318984 | 24.554505382938732 | 24.7455949127671 | 19.98453388437796 | 19.222014175381666 | 28.146998729821682 | .. |
1002 | Uganda | UGA | Net ODA received per capita (current US$) | DT.ODA.ODAT.PC.ZS | 37.56293132174223 | 29.523406938747293 | 26.47565543567768 | 36.19129971497363 | 33.98830973543233 | 29.124344539072013 | 38.63313662998166 | 45.56975203418104 | 43.176725971187935 | 55.62295892909799 | 58.9476455590042 | 54.00250983556967 | 56.87003011884526 | 52.11950990035822 | 46.985415557548684 | 47.52725017054316 | 47.54483358692437 | 44.216806655035974 | 42.826966969272846 | 44.45489885970484 | 48.869973352995636 | 45.53040122002132 | 45.81045695695399 | 67.39227581143022 | .. |
1003 | Uganda | UGA | Net official aid received (constant 2020 US$) | DT.ODA.OATL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1004 | Uganda | UGA | Net official aid received (current US$) | DT.ODA.OATL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1005 | Uganda | UGA | Net official development assistance and official aid received (constant 2020 US$) | DT.ODA.ALLD.KD | 1126219970.70313 | 920940002.441406 | 844859985.351563 | 1257859985.35156 | 1261680053.71094 | 1064689941.40625 | 1273510009.76563 | 1423920043.94531 | 1367790039.0625 | 1726910034.17969 | 1762319946.28906 | 1603760009.76563 | 1814369995.11719 | 1706660034.17969 | 1514640014.64844 | 1606160034.17969 | 1651719970.70313 | 1578800048.82813 | 1717310058.59375 | 1860040039.0625 | 2090340087.89063 | 1945469970.70313 | 2132649902.34375 | .. | .. |
1006 | Uganda | UGA | Net official development assistance and official aid received (current US$) | DT.ODA.ALLD.CD | 813440002.441406 | 658099975.585938 | 607679992.675781 | 855929992.675781 | 828940002.441406 | 732979980.46875 | 1003710021.97266 | 1222239990.23438 | 1195329956.05469 | 1589229980.46875 | 1738150024.41406 | 1643390014.64844 | 1786349975.58594 | 1690140014.64844 | 1572920043.94531 | 1642479980.46875 | 1697089965.82031 | 1632109985.35156 | 1637079956.05469 | 1762599975.58594 | 2011810058.59375 | 1945469970.70313 | 2028010009.76563 | 3082590087.89063 | .. |
1007 | Uganda | UGA | Net official development assistance received (constant 2020 US$) | DT.ODA.ODAT.KD | 1131020019.53125 | 925590026.855469 | 850239990.234375 | 1275180053.71094 | 1271400024.41406 | 1069030029.29688 | 1281430053.71094 | 1434030029.29688 | 1376619995.11719 | 1742050048.82813 | 1772599975.58594 | 1612719970.70313 | 1827219970.70313 | 1721030029.29688 | 1526430053.71094 | 1624150024.41406 | 1668020019.53125 | 1595050048.82813 | 1734989990.23438 | 1881310058.59375 | 2117600097.65625 | 1968089965.82031 | 2079959960.9375 | 3082590087.89063 | .. |
1008 | Uganda | UGA | Net official development assistance received (current US$) | DT.ODA.ODAT.CD | 813440002.441406 | 658099975.585938 | 607679992.675781 | 855929992.675781 | 828940002.441406 | 732979980.46875 | 1003710021.97266 | 1222239990.23438 | 1195329956.05469 | 1589229980.46875 | 1738150024.41406 | 1643390014.64844 | 1786349975.58594 | 1690140014.64844 | 1572920043.94531 | 1642479980.46875 | 1697089965.82031 | 1632109985.35156 | 1637079956.05469 | 1762599975.58594 | 2011810058.59375 | 1945469970.70313 | 2028010009.76563 | 3082590087.89063 | .. |
1009 | Uganda | UGA | Net official flows from UN agencies, FAO (current US$) | DT.NFL.FAOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 183922.231197357 | .. | .. | .. | .. | 510689.973831177 | 433851.808309555 | .. | .. |
1010 | Uganda | UGA | Net official flows from UN agencies, IAEA (current US$) | DT.NFL.IAEA.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | 319999.99284744303 | 349999.99403953605 | 600000.023841858 | 439999.997615814 | 400000.00596046395 | 280000.001192093 | 200000.00298023198 | 569999.992847443 | 439999.997615814 | 384758.740663528 | 442121.297121048 | 1066824.43618774 | 697079.002857208 | 509558.97569656407 | 546119.451522827 | .. |
1011 | Uganda | UGA | Net official flows from UN agencies, IFAD (current US$) | DT.NFL.IFAD.CD | 100000.00149011599 | 4659999.84741211 | 159999.99642372102 | 980000.019073486 | 2529999.97138977 | 3259999.99046326 | 3390000.10490417 | 5889999.8664856 | 6219999.79019165 | 5309999.94277954 | 9409999.84741211 | 8600000.38146973 | 15039999.961853001 | 15840000.1525879 | 12489999.7711182 | 18229999.5422363 | 23360000.6103516 | 11140000.3433228 | 11595305.4428101 | 9544647.21679688 | 11960596.0845947 | 15407045.364379901 | 22555458.068847697 | 10188297.271728499 | .. |
1012 | Uganda | UGA | Net official flows from UN agencies, ILO (current US$) | DT.NFL.ILOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 360276.699066162 | 373512.17865943897 | 403600.00729560904 | 240989.997982979 | 363350.003957748 | 332269.996404648 | 643224.954605103 | 611829.996109009 | 730278.313159943 | .. |
1013 | Uganda | UGA | Net official flows from UN agencies, UNAIDS (current US$) | DT.NFL.UNAI.CD | .. | .. | .. | .. | .. | .. | .. | .. | 519999.980926514 | 469999.998807907 | 990000.009536743 | 649999.976158142 | 1019999.98092651 | 1019999.98092651 | 1000000 | 961118.996143341 | 1529559.96990204 | 991333.305835724 | 1061607.00321198 | 754697.799682617 | 941600.024700165 | 675385.117530823 | 1101847.64862061 | .. | .. |
1014 | Uganda | UGA | Net official flows from UN agencies, UNDP (current US$) | DT.NFL.UNDP.CD | 16969999.3133545 | 12449999.8092651 | 6159999.84741211 | 4139999.8664856004 | 4250000 | 4010000.2288818406 | 4489999.771118159 | 5429999.82833862 | 6130000.11444092 | 7110000.1335144 | 7900000.09536743 | 12510000.2288818 | 11180000.3051758 | 4900000.09536743 | 3640000.10490417 | 7449924.46899414 | 8857489.58587646 | 10790377.6168823 | 8546315.19317627 | 7154526.2336731 | 7301125.04959106 | 6756734.84802246 | 7689563.751220699 | 9909634.59014893 | .. |
1015 | Uganda | UGA | Net official flows from UN agencies, UNECE (current US$) | DT.NFL.UNEC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1016 | Uganda | UGA | Net official flows from UN agencies, UNEP (current US$) | DT.NFL.UNEP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1017 | Uganda | UGA | Net official flows from UN agencies, UNFPA (current US$) | DT.NFL.UNFP.CD | 3019999.98092651 | 6039999.96185303 | 4059999.94277954 | 2619999.8855590797 | 4829999.92370605 | 5369999.88555908 | 6219999.79019165 | 3829999.92370605 | 3430000.0667572 | 3619999.8855590797 | 4289999.96185303 | 6429999.82833862 | 7230000.01907349 | 6780000.20980835 | 6219999.79019165 | 6677663.803100591 | 6467065.81115723 | 6324778.0799865695 | 5697184.08584595 | 4192166.3284301804 | 3002966.1655425997 | 2836220.02601624 | 4261070.728302 | 4210810.18447876 | .. |
1018 | Uganda | UGA | Net official flows from UN agencies, UNHCR (current US$) | DT.NFL.UNCR.CD | 22610000.6103516 | 19059999.4659424 | 16600000.381469702 | 11399999.6185303 | 12439999.5803833 | 14710000.038146999 | 11949999.8092651 | 9270000.45776367 | 2130000.1144409203 | 1259999.9904632599 | 2990000.00953674 | 270000.010728836 | 3619999.8855590797 | 2210000.03814697 | .. | 16487199.783325199 | 12190.000154078 | .. | .. | .. | .. | 3254798.65074158 | .. | .. | .. |
1019 | Uganda | UGA | Net official flows from UN agencies, UNICEF (current US$) | DT.NFL.UNCF.CD | 6230000.01907349 | 4659999.84741211 | 6179999.82833862 | 6469999.79019165 | 5349999.90463257 | 5019999.98092651 | 5360000.1335144 | 7789999.96185303 | 9560000.4196167 | 11670000.076293899 | 18510000.2288818 | 22409999.8474121 | 22100000.3814697 | 20180000.3051758 | 22860000.6103516 | 24810560.2264404 | 21020969.390869103 | 22660026.550293002 | 20364892.9595947 | 21715518.951416 | 24841289.5202637 | 19669013.9770508 | 21642000.1983643 | 19877000.808715798 | .. |
1020 | Uganda | UGA | Net official flows from UN agencies, UNIDIR (current US$) | DT.NFL.UNID.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1021 | Uganda | UGA | Net official flows from UN agencies, UNPBF (current US$) | DT.NFL.UNPB.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 610000.014305115 | 6829999.92370605 | 6462810.03952026 | 403258.770704269 | 322077.840566635 | 662502.825260162 | 20246.999338269197 | -32843.999564647704 | -441.000011051074 | 995100.021362305 | 746320.009231567 | .. |
1022 | Uganda | UGA | Net official flows from UN agencies, UNRWA (current US$) | DT.NFL.UNRW.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1023 | Uganda | UGA | Net official flows from UN agencies, UNTA (current US$) | DT.NFL.UNTA.CD | 2809999.94277954 | 2150000.09536743 | 2710000.03814697 | 2680000.0667572 | 2200000.04768372 | 3279999.97138977 | 4309999.94277954 | 2880000.1144409203 | 2920000.07629395 | 1629999.99523163 | 2440000.05722046 | 1070000.05245209 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1024 | Uganda | UGA | Net official flows from UN agencies, UNWTO (current US$) | DT.NFL.UNWT.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1025 | Uganda | UGA | Net official flows from UN agencies, WFP (current US$) | DT.NFL.WFPG.CD | 19549999.237060502 | 14829999.923706101 | 2960000.03814697 | 8609999.65667725 | 18850000.3814697 | 14899999.6185303 | 19639999.3896484 | 12310000.4196167 | .. | 9649999.61853027 | 2519999.98092651 | 3880000.1144409203 | 12289999.961853001 | 7010000.228881841 | 2700000.04768372 | 11837491.0354614 | 8177076.33972168 | 5755819.79751587 | 9112096.78649902 | 6673320.77026367 | 13428250.3128052 | 3481143.23616028 | 757040.023803711 | 5186927.79541016 | .. |
1026 | Uganda | UGA | Net official flows from UN agencies, WHO (current US$) | DT.NFL.WHOL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1289999.96185303 | 2006588.9358520498 | 1375765.44284821 | 1436913.84792328 | 2319881.20079041 | 1726434.94606018 | 1516763.5679245 | 2059521.91352844 | 1372714.16187286 | 1030359.1489791899 | .. |
1027 | Uganda | UGA | Number of surgical procedures (per 100,000 population) | SH.SGR.PROC.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 241 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1028 | Uganda | UGA | Nurses and midwives (per 1,000 people) | SH.MED.NUMW.P3 | .. | .. | .. | .. | .. | .. | .. | .. | 1.3591 | .. | .. | .. | .. | .. | .. | 1.1811 | 1.3209 | 1.2296 | 1.5565 | 1.6401 | 1.4686 | 1.2382 | .. | .. | .. |
1029 | Uganda | UGA | Out-of-pocket expenditure (% of current health expenditure) | SH.XPD.OOPC.CH.ZS | .. | .. | .. | 43.13160324 | 43.49900436 | 44.13851166 | 45.41794586 | 38.377491 | 48.59852982 | 54.05283737 | 54.48326874 | 52.72429657 | 42.84917831 | 37.39066315 | 33.01005173 | 37.51226807 | 42.51777649 | 40.14643478 | 39.4708519 | 40.60963821 | 38.08950424 | 35.62893295 | 38.26028824 | .. | .. |
1030 | Uganda | UGA | Out-of-pocket expenditure per capita (current US$) | SH.XPD.OOPC.PC.CD | .. | .. | .. | 7.17292543 | 7.04220101 | 7.03010849 | 6.55718773 | 7.22974371 | 12.69826296 | 17.21560742 | 19.7808227 | 21.19438738 | 19.0351641 | 19.3780707 | 18.15754123 | 20.51425409 | 22.26932424 | 20.1717616 | 15.53984085 | 15.53051196 | 11.68690669 | 11.42068746 | 12.39956304 | .. | .. |
1031 | Uganda | UGA | Out-of-pocket expenditure per capita, PPP (current international $) | SH.XPD.OOPC.PP.CD | .. | .. | .. | 21.02841832 | 21.54739914 | 23.10432683 | 22.24296937 | 20.0861439 | 36.41398511 | 51.0874054 | 52.85379941 | 54.18196789 | 50.51156468 | 52.81128607 | 53.50336612 | 51.21140728 | 55.28195464 | 48.84044767 | 44.74491249 | 43.8271393 | 33.21561722 | 32.82734294 | 35.34437049 | .. | .. |
1032 | Uganda | UGA | Part time employment, female (% of total female employment) | SL.TLF.PART.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 57.8600006103516 | 69.0599975585938 | .. | .. | .. | 46.9199981689453 | .. | .. | .. | .. |
1033 | Uganda | UGA | Part time employment, male (% of total male employment) | SL.TLF.PART.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 48.8499984741211 | 56.5099983215332 | .. | .. | .. | 38.3800010681152 | .. | .. | .. | .. |
1034 | Uganda | UGA | Part time employment, total (% of total employment) | SL.TLF.PART.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 53.1399993896484 | 62.8899993896484 | .. | .. | .. | 42.1100006103516 | .. | .. | .. | .. |
1035 | Uganda | UGA | Physicians (per 1,000 people) | SH.MED.PHYS.ZS | .. | .. | .. | .. | .. | 0.047 | .. | 0.0824 | 0.1214 | .. | .. | .. | .. | .. | .. | 0.0975 | .. | .. | 0.0954 | .. | 0.168 | .. | .. | .. | .. |
1036 | Uganda | UGA | Poverty gap at $1.90 a day (2011 PPP) (%) | SI.POV.GAPS | .. | .. | 28.8 | .. | .. | 26.9 | .. | .. | 21.6 | .. | .. | .. | 15 | .. | .. | 10.7 | .. | .. | .. | 13.1 | .. | .. | 13 | .. | .. |
1037 | Uganda | UGA | Poverty gap at $3.20 a day (2011 PPP) (%) | SI.POV.LMIC.GP | .. | .. | 49.3 | .. | .. | 47.4 | .. | .. | 41.5 | .. | .. | .. | 34 | .. | .. | 28.1 | .. | .. | .. | 31.1 | .. | .. | 31 | .. | .. |
1038 | Uganda | UGA | Poverty gap at $5.50 a day (2011 PPP) (%) | SI.POV.UMIC.GP | .. | .. | 67.3 | .. | .. | 65.6 | .. | .. | 61 | .. | .. | .. | 54.8 | .. | .. | 49.6 | .. | .. | .. | 51.8 | .. | .. | 52.2 | .. | .. |
1039 | Uganda | UGA | Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) | SI.POV.DDAY | .. | .. | 67.5 | .. | .. | 65.6 | .. | .. | 57 | .. | .. | .. | 45.3 | .. | .. | 35.7 | .. | .. | .. | 41.3 | .. | .. | 41 | .. | .. |
1040 | Uganda | UGA | Poverty headcount ratio at $3.20 a day (2011 PPP) (% of population) | SI.POV.LMIC | .. | .. | 87.4 | .. | .. | 85.2 | .. | .. | 80.2 | .. | .. | .. | 73.5 | .. | .. | 67.3 | .. | .. | .. | 69.6 | .. | .. | 70.5 | .. | .. |
1041 | Uganda | UGA | Poverty headcount ratio at $5.50 a day (2011 PPP) (% of population) | SI.POV.UMIC | .. | .. | 95.4 | .. | .. | 94.4 | .. | .. | 92.6 | .. | .. | .. | 89.3 | .. | .. | 87 | .. | .. | .. | 87.6 | .. | .. | 89 | .. | .. |
1042 | Uganda | UGA | Poverty headcount ratio at national poverty lines (% of population) | SI.POV.NAHC | .. | .. | 33.8 | .. | .. | 38.8 | .. | .. | 31.1 | .. | .. | .. | 24.5 | .. | .. | 19.7 | .. | .. | .. | 21.4 | .. | .. | 20.3 | .. | .. |
1043 | Uganda | UGA | PPP conversion factor, GDP (LCU per international $) | PA.NUS.PPP | 487.771588124204 | 524.719874076397 | 516.842738428452 | 561.578889148203 | 574.109142568546 | 547.381320140951 | 578.692882617279 | 651.410411489468 | 620.607005369483 | 616.513420099795 | 644.239157925539 | 672.345189447078 | 765.377105370609 | 798.924684188794 | 856.168212890625 | 1003.27728271484 | 1042.08117675781 | 1073.74743652344 | 1125.47131347656 | 1211.94018554688 | 1270.6083984375 | 1296.10239736914 | 1311.52615083067 | 1331.17534401369 | 1309.50548602194 |
1044 | Uganda | UGA | PPP conversion factor, private consumption (LCU per international $) | PA.NUS.PRVT.PP | 563.969376958452 | 555.730916555642 | 575.250896121259 | 575.33527946619 | 569.958014196209 | 559.446340498274 | 594.512940328614 | 600.558113526278 | 629.92583659904 | 654.852498852342 | 675.773097250919 | 729.21426983824 | 827.078606614418 | 846.091555728811 | 944.255554199219 | 1017.30548095703 | 1064.89892578125 | 1081.15966796875 | 1127.6865234375 | 1172.62976074219 | 1221.08764648438 | 1223.24978672194 | 1235.94800180476 | 1267.21295269912 | .. |
1045 | Uganda | UGA | Price level ratio of PPP conversion factor (GDP) to market exchange rate | PA.NUS.PPPC.RF | 0.46099558174945066 | 0.4564160684001444 | 0.37944287036281 | 0.3714095244517505 | 0.32565730424969264 | 0.31197622661221297 | 0.30725742936431655 | 0.3366611354082098 | 0.357239997792737 | 0.3378119076296021 | 0.36193213152738885 | 0.3963244158849436 | 0.3965806540214808 | 0.3937760000764924 | 0.36848423229219474 | 0.3923427273308972 | 0.40217468349265206 | 0.42306341849984014 | 0.3980127477225028 | 0.3520040374261728 | 0.3599787318847057 | 0.3542090352431025 | 0.3510223528479322 | 0.3583150204050321 | 0.3578578144415232 |
1046 | Uganda | UGA | Proportion of people living below 50 percent of median income (%) | SI.DST.50MD | .. | .. | 14 | .. | .. | 12.9 | .. | .. | 12.9 | .. | .. | .. | 12.7 | .. | .. | 12.2 | .. | .. | .. | 13.1 | .. | .. | 13.4 | .. | .. |
1047 | Uganda | UGA | Proportion of seats held by women in national parliaments (%) | SG.GEN.PARL.ZS | 18.1159420289855 | 18.1159420289855 | 17.921146953405 | 17.7935943060498 | 24.6710526315789 | 24.6710526315789 | 24.6710526315789 | 23.9344262295082 | 23.9344262295082 | 29.8192771084337 | 30.7228915662651 | 30.7228915662651 | 31.4814814814815 | 31.2883435582822 | 34.9740932642487 | 34.9740932642487 | 34.9740932642487 | 34.9740932642487 | 34.9740932642487 | 33.4894613583138 | 34.2984409799555 | 34.2984409799555 | 34.8583877995643 | 34.8583877995643 | 33.8129496402878 |
1048 | Uganda | UGA | Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day) | SG.TIM.UWRK.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.58333 | .. | .. | .. |
1049 | Uganda | UGA | Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day) | SG.TIM.UWRK.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.5 | .. | .. | .. |
1050 | Uganda | UGA | Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of ever-partnered women ages 15-49) | SG.VAW.1549.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29.9 | .. | .. | .. | .. | .. |
1051 | Uganda | UGA | Ratio of female to male labor force participation rate (%) (modeled ILO estimate) | SL.TLF.CACT.FM.ZS | 82.41069671341721 | 82.76949744604772 | 83.1288189231549 | 83.4886883194097 | 83.85091043174786 | 84.21267714933664 | 84.57663666574345 | 84.94057092696939 | 85.30598151020413 | 85.67190147165611 | 86.04037216013874 | 86.40891232286253 | 86.77963573487737 | 87.15120601864629 | 87.52300419642134 | 87.89691690200746 | 88.21685357828272 | 88.57384168771395 | 88.96254216109027 | 89.42051784547837 | 89.94608456439465 | 90.53459788954926 | 91.19426341341722 | 89.10027890392766 | 89.99522801731605 |
1052 | Uganda | UGA | Ratio of female to male labor force participation rate (%) (national estimate) | SL.TLF.CACT.FM.NE.ZS | .. | .. | .. | .. | .. | 98.67470063358904 | 96.09254396364871 | .. | 96.66197655856645 | .. | .. | .. | 97.42375717371111 | .. | .. | 87.89622063838553 | 94.98695898748234 | .. | .. | .. | 91.75525259088029 | .. | .. | .. | .. |
1053 | Uganda | UGA | Refugee population by country or territory of asylum | SM.POP.REFG | 188512 | 204543 | 218191 | 236622 | 199735 | 217301 | 230904 | 250477 | 257252 | 272003 | 228956 | 162132 | 127340 | 135799 | 139442 | 197872 | 220548 | 385503 | 477187 | 940825 | 1350495 | 1165646 | 1359458 | 1421133 | 1529903 |
1054 | Uganda | UGA | Refugee population by country or territory of origin | SM.POP.REFG.OR | 55232 | 13294 | 13929 | 32405 | 40133 | 40414 | 35240 | 31955 | 34208 | 21735 | 21325 | 7533 | 7543 | 6421 | 5658 | 5588 | 8166 | 7177 | 6311 | 6229 | 6409 | 7034 | 7301 | 7442 | 7886 |
1055 | Uganda | UGA | Self-employed, female (% of female employment) (modeled ILO estimate) | SL.EMP.SELF.FE.ZS | 94.3199996948242 | 94.1699981689453 | 93.8899993896484 | 93.870002746582 | 93.6800003051758 | 93.25 | 93.0999984741211 | 92.2900009155273 | 91.7099990844727 | 90.8899993896484 | 89.6699981689453 | 88.6699981689453 | 88.3000030517578 | 87.6100006103516 | 86.8099975585938 | 85.9100036621094 | 85.5100021362305 | 85.2799987792969 | 84.9700012207031 | 84.379997253418 | 84.370002746582 | 83.7600021362305 | 83.1800003051758 | .. | .. |
1056 | Uganda | UGA | Self-employed, male (% of male employment) (modeled ILO estimate) | SL.EMP.SELF.MA.ZS | 81.4300003051758 | 81.129997253418 | 80.629997253418 | 80.3099975585938 | 79.8300018310547 | 79.0599975585938 | 78.8099975585938 | 78.1999969482422 | 77.5800018310547 | 76.879997253418 | 75.9899978637695 | 75.4599990844727 | 76 | 75.4100036621094 | 73.870002746582 | 73.5400009155273 | 73.3000030517578 | 73.1100006103516 | 72.6399993896484 | 72.5199966430664 | 72.4700012207031 | 71.9599990844727 | 71.6600036621094 | .. | .. |
1057 | Uganda | UGA | Self-employed, total (% of total employment) (modeled ILO estimate) | SL.EMP.SELF.ZS | 87.4499969482422 | 87.2300033569336 | 86.8399963378906 | 86.6699981689453 | 86.3199996948242 | 85.7099990844727 | 85.5100021362305 | 84.8600006103516 | 84.2900009155273 | 83.5500030517578 | 82.5199966430664 | 81.7799987792969 | 81.8899993896484 | 81.2699966430664 | 80.0999984741211 | 79.5100021362305 | 79.2200012207031 | 79.0299987792969 | 78.6500015258789 | 78.3099975585938 | 78.3000030517578 | 77.7600021362305 | 77.3199996948242 | .. | .. |
1058 | Uganda | UGA | Services, value added (annual % growth) | NV.SRV.TOTL.KD.ZG | 8.489661105750756 | 7.102490245964361 | 6.956206867089065 | 4.865010907405193 | 10.981631153855616 | 7.362717967253943 | 7.85333972293148 | 6.161219224668457 | 12.171083123625294 | 8.04840382909613 | 9.66188302792257 | -8.812786715058039 | 7.0403119644864915 | 6.918991940082634 | 12.204658068680317 | 4.748127020437181 | 5.907326353710474 | 5.474099696932285 | 4.658903778748737 | 7.988587715166389 | 0.10803460685220045 | 8.516257023722403 | 5.837169246548996 | 2.505025414292831 | 2.7433130993324255 |
1059 | Uganda | UGA | Services, value added (constant 2015 US$) | NV.SRV.TOTL.KD | 4593192132.955487 | 4919423156.177053 | 5261628407.588211 | 5517607203.5245075 | 6123530475.134137 | 6574388753.657109 | 7090697837.188003 | 7527571275.49598 | 8443758232.626737 | 9123345993.541086 | 10004833011.669685 | 9123128417.153519 | 9765425118.641846 | 10441094095.51548 | 11715393928.502314 | 12271655713.17219 | 12996582465.153027 | 13708028346.489523 | 14346672197.116072 | 15492768689.79008 | 15509506241.534615 | 16830335656.173971 | 17812750833.18713 | 18258964768.543125 | 18759865340.84106 |
1060 | Uganda | UGA | Services, value added per worker (constant 2015 US$) | NV.SRV.EMPL.KD | 2765.554179379655 | 2853.7900579561765 | 2917.42272926752 | 2945.2607057132946 | 3131.600535356037 | 3193.2848087135776 | 3278.172669382262 | 3302.9214892040904 | 3524.46309469495 | 3630.632530132687 | 3812.6502152735384 | 3329.621986282918 | 3433.463968457779 | 3521.489438584001 | 3760.7595430858178 | 3760.0388501891034 | 4634.123235156609 | 4780.745582623223 | 4775.690238918111 | 4897.732490358664 | 4797.451307891959 | 4884.551193949467 | 4879.172735744089 | .. | .. |
1061 | Uganda | UGA | Share of youth not in education, employment or training, female (% of female youth population) | SL.UEM.NEET.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 11.3000001907349 | .. | .. | .. | 9.64000034332275 | .. | .. | 19.0300006866455 | 8.38000011444092 | .. | .. | .. | 19.75 | .. | .. | .. | .. |
1062 | Uganda | UGA | Share of youth not in education, employment or training, male (% of male youth population) | SL.UEM.NEET.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 4.53000020980835 | .. | .. | .. | 3.80999994277954 | .. | .. | 9.88000011444092 | 3.30999994277954 | .. | .. | .. | 10.5299997329712 | .. | .. | .. | .. |
1063 | Uganda | UGA | Share of youth not in education, employment or training, total (% of youth population) | SL.UEM.NEET.ZS | .. | .. | .. | .. | .. | .. | .. | .. | 8.09000015258789 | .. | .. | .. | 6.94999980926514 | .. | .. | 14.5299997329712 | 5.90999984741211 | .. | .. | .. | 15.3100004196167 | .. | .. | .. | .. |
1064 | Uganda | UGA | Specialist surgical workforce (per 100,000 population) | SH.MED.SAOP.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.95 | .. | .. | .. | 1.05 | .. | .. | .. | .. | .. |
1065 | Uganda | UGA | Survey mean consumption or income per capita, bottom 40% of population (2011 PPP $ per day) | SI.SPR.PC40 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.28 | .. | .. | 1.28 | .. | .. |
1066 | Uganda | UGA | Survey mean consumption or income per capita, total population (2011 PPP $ per day) | SI.SPR.PCAP | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.2 | .. | .. | 3.18 | .. | .. |
1067 | Uganda | UGA | Unemployment with advanced education (% of total labor force with advanced education) | SL.UEM.ADVN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.85000038146973 | .. | .. | .. | .. | 1.4099999666214 | .. | .. | .. | .. |
1068 | Uganda | UGA | Unemployment with advanced education, female (% of female labor force with advanced education) | SL.UEM.ADVN.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.6300001144409 | .. | .. | .. | .. | 5.84000015258789 | .. | .. | .. | .. |
1069 | Uganda | UGA | Unemployment with advanced education, male (% of male labor force with advanced education) | SL.UEM.ADVN.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.11999988555908 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1070 | Uganda | UGA | Unemployment with basic education (% of total labor force with basic education) | SL.UEM.BASC.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.11999988555908 | .. | .. | .. | .. | 1.11000001430511 | .. | .. | .. | .. |
1071 | Uganda | UGA | Unemployment with basic education, female (% of female labor force with basic education) | SL.UEM.BASC.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.17999982833862 | .. | .. | .. | .. | 0.850000023841858 | .. | .. | .. | .. |
1072 | Uganda | UGA | Unemployment with basic education, male (% of male labor force with basic education) | SL.UEM.BASC.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.72000002861023 | .. | .. | .. | .. | 1.29999995231628 | .. | .. | .. | .. |
1073 | Uganda | UGA | Unemployment with intermediate education (% of total labor force with intermediate education) | SL.UEM.INTM.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.1499996185303 | .. | .. | .. | .. | 7.42999982833862 | .. | .. | .. | .. |
1074 | Uganda | UGA | Unemployment with intermediate education, female (% of female labor force with intermediate education) | SL.UEM.INTM.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.0300006866455 | .. | .. | .. | .. | 5.71000003814697 | .. | .. | .. | .. |
1075 | Uganda | UGA | Unemployment with intermediate education, male (% of male labor force with intermediate education) | SL.UEM.INTM.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.03999996185303 | .. | .. | .. | .. | 8.5 | .. | .. | .. | .. |
1076 | Uganda | UGA | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS | 2.50999999046326 | 2.89100003242493 | 3.24000000953674 | 3.67899990081787 | 4.04099988937378 | 4.37799978256226 | 4.55399990081787 | 3.32999992370605 | 2.10999989509583 | 2.59599995613098 | 3.14299988746643 | 3.67600011825562 | 4.24300003051758 | 4.26200008392334 | 4.21000003814697 | 4.27400016784668 | 2.46099996566772 | 2.45099997520447 | 2.45300006866455 | 2.45900011062622 | 2.46900010108948 | 2.4539999961853 | 2.45199990272522 | 3.41199994087219 | 3.6949999332428 |
1077 | Uganda | UGA | Unemployment, female (% of female labor force) (national estimate) | SL.UEM.TOTL.FE.NE.ZS | .. | .. | .. | .. | .. | 4.19999980926514 | 4.48999977111816 | .. | 2.09999990463257 | .. | .. | .. | .. | .. | .. | 4.28999996185303 | 2.44000005722046 | .. | .. | .. | 4.1399998664856 | .. | .. | .. | .. |
1078 | Uganda | UGA | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS | 1.94599997997284 | 2.10800004005432 | 2.24000000953674 | 2.4449999332428 | 2.58699989318848 | 2.71000003814697 | 2.73900008201599 | 2.22199988365173 | 1.70799994468689 | 2.00300002098084 | 2.34299993515015 | 2.65899991989136 | 2.99699997901917 | 2.94799995422363 | 2.85199999809265 | 2.85899996757507 | 1.38199996948242 | 1.38100004196167 | 1.38800001144409 | 1.39699995517731 | 1.4099999666214 | 1.40499997138977 | 1.40900003910065 | 2.15300011634827 | 2.20700001716614 |
1079 | Uganda | UGA | Unemployment, male (% of male labor force) (national estimate) | SL.UEM.TOTL.MA.NE.ZS | .. | .. | .. | .. | .. | 2.59999990463257 | 2.70000004768372 | .. | 1.70000004768372 | .. | .. | .. | .. | .. | .. | 2.86999988555908 | 1.37000000476837 | .. | .. | .. | 3.15000009536743 | .. | .. | .. | .. |
1080 | Uganda | UGA | Unemployment, total (% of total labor force) (modeled ILO estimate) | SL.UEM.TOTL.ZS | 2.20900011062622 | 2.47399997711182 | 2.71000003814697 | 3.02600002288818 | 3.2739999294281 | 3.5 | 3.59999990463257 | 2.74900007247925 | 1.89999997615814 | 2.28699994087219 | 2.72699999809265 | 3.1489999294281 | 3.59999990463257 | 3.58599996566772 | 3.51300001144409 | 3.54999995231628 | 1.9099999666214 | 1.90600001811981 | 1.91100001335144 | 1.91999995708466 | 1.932000041008 | 1.92299997806549 | 1.92499995231628 | 2.76799988746643 | 2.93600010871887 |
1081 | Uganda | UGA | Unemployment, total (% of total labor force) (national estimate) | SL.UEM.TOTL.NE.ZS | .. | .. | .. | .. | .. | 3.5 | 3.59999990463257 | .. | 1.89999997615814 | .. | .. | .. | 3.59999990463257 | .. | .. | 3.54999995231628 | 1.9099999666214 | .. | .. | .. | 3.64000010490417 | .. | .. | .. | .. |
1082 | Uganda | UGA | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS | 3.95000004768372 | 4.46999979019165 | 4.95100021362305 | 5.51999998092651 | 6.01200008392334 | 6.48000001907349 | 6.66900014877319 | 4.84299993515015 | 3.04800009727478 | 3.74900007247925 | 4.50500011444092 | 5.2480001449585 | 6.02199983596802 | 6.01900005340576 | 5.95800018310547 | 5.99300003051758 | 3.32500004768372 | 3.36100006103516 | 3.40700006484985 | 3.45700001716614 | 3.51200008392334 | 3.54800009727478 | 3.59400010108948 | 4.76999998092651 | 5.28700017929077 |
1083 | Uganda | UGA | Unemployment, youth female (% of female labor force ages 15-24) (national estimate) | SL.UEM.1524.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.03000020980835 | 3.21000003814697 | .. | .. | .. | 5.92999982833862 | .. | .. | .. | .. |
1084 | Uganda | UGA | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS | 3.625 | 3.87199997901917 | 4.07999992370605 | 4.36999988555908 | 4.59100008010864 | 4.78900003433228 | 4.77899980545044 | 3.84599995613098 | 2.92899990081787 | 3.43600010871887 | 3.98000001907349 | 4.49100017547607 | 5.01800012588501 | 4.90000009536743 | 4.74300003051758 | 4.69099998474121 | 2.10199999809265 | 2.13299989700317 | 2.17000007629395 | 2.21099996566772 | 2.25600004196167 | 2.28500008583069 | 2.32299995422363 | 3.28999996185303 | 3.43199992179871 |
1085 | Uganda | UGA | Unemployment, youth male (% of male labor force ages 15-24) (national estimate) | SL.UEM.1524.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.76000022888184 | 1.98000001907349 | .. | .. | .. | 5.59000015258789 | .. | .. | .. | .. |
1086 | Uganda | UGA | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.ZS | 3.78200006484985 | 4.16099977493286 | 4.50099992752075 | 4.92600011825562 | 5.27799987792969 | 5.60699987411499 | 5.69299983978271 | 4.32800006866455 | 2.98699998855591 | 3.58699989318848 | 4.2350001335144 | 4.8600001335144 | 5.50799989700317 | 5.44700002670288 | 5.33599996566772 | 5.3270001411438 | 2.70099997520447 | 2.73499989509583 | 2.77699995040894 | 2.82200002670288 | 2.87100005149841 | 2.90400004386902 | 2.94600009918213 | 4.00400018692017 | 4.33099985122681 |
1087 | Uganda | UGA | Unemployment, youth total (% of total labor force ages 15-24) (national estimate) | SL.UEM.1524.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.36999988555908 | 2.59999990463257 | .. | .. | .. | 5.76000022888184 | .. | .. | .. | .. |
1088 | Uganda | UGA | Vulnerable employment, female (% of female employment) (modeled ILO estimate) | SL.EMP.VULN.FE.ZS | 94.16999816894531 | 94.0200004577637 | 93.7399978637695 | 93.70999908447271 | 93.5200004577636 | 93.08000183105469 | 92.9099998474121 | 92.0200004577637 | 91.3599967956543 | 90.40999984741211 | 89.01000022888181 | 87.7799987792968 | 86.9999980926514 | 85.939998626709 | 84.8600006103516 | 83.3099994659423 | 82.7200012207031 | 82.30000114440921 | 81.9200000762939 | 81.1599998474122 | 81.109998703003 | 80.47000122070321 | 79.7999992370606 | .. | .. |
1089 | Uganda | UGA | Vulnerable employment, male (% of male employment) (modeled ILO estimate) | SL.EMP.VULN.MA.ZS | 81.0900030136108 | 80.7799978256225 | 80.27999687194821 | 79.96000289916991 | 79.47000312805179 | 78.6999979019165 | 78.41000175476071 | 77.6599969863892 | 76.8899965286255 | 75.9900016784668 | 74.8100004196167 | 73.899998664856 | 73.73999881744379 | 72.6099996566772 | 70.829999923706 | 69.57999897003181 | 69.0199985504151 | 68.5699987411499 | 68.0400018692017 | 67.6500005722045 | 67.5299978256225 | 67.01999855041507 | 66.65000152587888 | .. | .. |
1090 | Uganda | UGA | Vulnerable employment, total (% of total employment) (modeled ILO estimate) | SL.EMP.VULN.ZS | 87.1900005340576 | 86.980001449585 | 86.5799999237061 | 86.4200000762939 | 86.05999946594241 | 85.44000244140629 | 85.2099990844726 | 84.4499988555908 | 83.76000022888181 | 82.8500003814698 | 81.59000015258789 | 80.5400009155273 | 80.1000003814697 | 79.0200004577637 | 77.5900001525879 | 76.21000099182129 | 75.65999984741211 | 75.2400016784668 | 74.810001373291 | 74.2499980926514 | 74.1899995803833 | 73.6200008392334 | 73.109998703003 | .. | .. |
1091 | Uganda | UGA | Wage and salaried workers, female (% of female employment) (modeled ILO estimate) | SL.EMP.WORK.FE.ZS | 5.67999982833862 | 5.82999992370605 | 6.1100001335144 | 6.13000011444092 | 6.32000017166138 | 6.75 | 6.90999984741211 | 7.71000003814697 | 8.28999996185303 | 9.10999965667725 | 10.3299999237061 | 11.3299999237061 | 11.6999998092651 | 12.3900003433228 | 13.1899995803833 | 14.0900001525879 | 14.4899997711182 | 14.7200002670288 | 15.0299997329712 | 15.6199998855591 | 15.6300001144409 | 16.2399997711182 | 16.8199996948242 | .. | .. |
1092 | Uganda | UGA | Wage and salaried workers, male (% of male employment) (modeled ILO estimate) | SL.EMP.WORK.MA.ZS | 18.5699996948242 | 18.8700008392334 | 19.3700008392334 | 19.6900005340576 | 20.1700000762939 | 20.9400005340576 | 21.1900005340576 | 21.7999992370605 | 22.4200000762939 | 23.1200008392334 | 24.0200004577637 | 24.5400009155273 | 24 | 24.6000003814697 | 26.1299991607666 | 26.4599990844727 | 26.7000007629395 | 26.8899993896484 | 27.3600006103516 | 27.4799995422363 | 27.5300006866455 | 28.0400009155273 | 28.3400001525879 | .. | .. |
1093 | Uganda | UGA | Wage and salaried workers, total (% of total employment) (modeled ILO estimate) | SL.EMP.WORK.ZS | 12.5500001907349 | 12.7700004577637 | 13.1599998474121 | 13.3299999237061 | 13.6800003051758 | 14.289999961853 | 14.4899997711182 | 15.1400003433228 | 15.710000038147 | 16.4500007629395 | 17.4799995422363 | 18.2199993133545 | 18.1100006103516 | 18.7299995422363 | 19.8999996185303 | 20.4899997711182 | 20.7800006866455 | 20.9699993133545 | 21.3500003814697 | 21.6900005340576 | 21.7000007629395 | 22.25 | 22.6900005340576 | .. | .. |
1094 | Uganda | UGA | Women Business and the Law Index Score (scale 1-100) | SG.LAW.INDX | 46.875 | 46.875 | 46.875 | 46.875 | 46.875 | 46.875 | 46.875 | 46.875 | 46.875 | 65 | 67.5 | 67.5 | 67.5 | 70 | 70 | 70 | 70 | 70 | 70 | 70 | 70 | 70 | 73.125 | 73.125 | 73.125 |
1095 | Uganda | UGA | Women making their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women age 15-49) | SG.DMK.SRCR.FN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 48 | .. | .. | .. | .. | 49 | .. | .. | .. | .. | 62 | .. | .. | .. | .. | .. |
1096 | Uganda | UGA | Women participating in the three decisions (own health care, major household purchases, and visiting family) (% of women age 15-49) | SG.DMK.ALLD.FN.ZS | .. | .. | .. | .. | 28.5 | .. | .. | .. | .. | 38.8 | .. | .. | .. | .. | 37.5 | .. | .. | .. | .. | 51.1 | .. | .. | .. | .. | .. |
1097 | Uganda | UGA | Women who believe a husband is justified in beating his wife (any of five reasons) (%) | SG.VAW.REAS.ZS | .. | .. | .. | .. | 76.5 | .. | .. | .. | .. | 70.2 | .. | .. | .. | .. | 58.3 | .. | .. | .. | .. | 49 | .. | .. | .. | .. | .. |
1098 | Uganda | UGA | Women who believe a husband is justified in beating his wife when she argues with him (%) | SG.VAW.ARGU.ZS | .. | .. | .. | .. | 36.9 | .. | .. | .. | .. | 39.9 | .. | .. | .. | .. | 28.5 | .. | .. | .. | .. | 26.1 | .. | .. | .. | .. | .. |
1099 | Uganda | UGA | Women who believe a husband is justified in beating his wife when she burns the food (%) | SG.VAW.BURN.ZS | .. | .. | .. | .. | 22.2 | .. | .. | .. | .. | 23.4 | .. | .. | .. | .. | 17.1 | .. | .. | .. | .. | 13.6 | .. | .. | .. | .. | .. |
1100 | Uganda | UGA | Women who believe a husband is justified in beating his wife when she goes out without telling him (%) | SG.VAW.GOES.ZS | .. | .. | .. | .. | 56.3 | .. | .. | .. | .. | 52.2 | .. | .. | .. | .. | 37.7 | .. | .. | .. | .. | 30 | .. | .. | .. | .. | .. |
1101 | Uganda | UGA | Women who believe a husband is justified in beating his wife when she neglects the children (%) | SG.VAW.NEGL.ZS | .. | .. | .. | .. | 67.3 | .. | .. | .. | .. | 56 | .. | .. | .. | .. | 45 | .. | .. | .. | .. | 38.5 | .. | .. | .. | .. | .. |
1102 | Uganda | UGA | Women who believe a husband is justified in beating his wife when she refuses sex with him (%) | SG.VAW.REFU.ZS | .. | .. | .. | .. | 24.2 | .. | .. | .. | .. | 30.5 | .. | .. | .. | .. | 21.9 | .. | .. | .. | .. | 18.1 | .. | .. | .. | .. | .. |
1103 | Djibouti | DJI | Adequacy of social insurance programs (% of total welfare of beneficiary households) | per_si_allsi.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34.8538524109419 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1104 | Djibouti | DJI | Adequacy of social protection and labor programs (% of total welfare of beneficiary households) | per_allsp.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 28.9534337810507 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1105 | Djibouti | DJI | Adequacy of social safety net programs (% of total welfare of beneficiary households) | per_sa_allsa.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.9092579029868 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1106 | Djibouti | DJI | Adequacy of unemployment benefits and ALMP (% of total welfare of beneficiary households) | per_lm_alllm.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1107 | Djibouti | DJI | Adjusted net national income (annual % growth) | NY.ADJ.NNTY.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 15.696445844737838 | 10.346297193338998 | 3.1483408978399012 | 1.8886486333806687 | 14.462001974219675 | 12.040383577632412 | 0.8031142260813908 | .. |
1108 | Djibouti | DJI | Adjusted net national income (constant 2015 US$) | NY.ADJ.NNTY.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1633941569.3294394 | 1890412322.8938944 | 2086000000 | 2151674391.1289406 | 2192311960.1117992 | 2509364159.064222 | 2811501229.1751842 | 2834080795.5131435 | .. |
1109 | Djibouti | DJI | Adjusted net national income (current US$) | NY.ADJ.NNTY.CD | 494100000 | 501300000 | 527200000 | 545700000 | 562600000 | 582100000 | 615700000 | 656000000 | 692400000 | 743000000 | 789900000 | 913800000 | 902800000 | 902100000 | 1013000000 | 1113000000 | 1579000000 | 1862000000 | 2086000000 | 2151000000 | 2204000000 | 2537000000 | 2844000000 | 2922000000 | .. |
1110 | Djibouti | DJI | Adjusted net national income per capita (annual % growth) | NY.ADJ.NNTY.PC.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 13.712486749155772 | 8.500226162129579 | 1.4698657800297212 | 0.2716614260149868 | 12.692652135636322 | 10.356251088959368 | -0.6706692126117986 | .. |
1111 | Djibouti | DJI | Adjusted net national income per capita (constant 2015 US$) | NY.ADJ.NNTY.PC.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1849.8233540392341 | 2103.4801363446536 | 2282.2807052094204 | 2315.827168299515 | 2322.11837740896 | 2616.856785231162 | 2887.8650445481717 | 2868.497022792609 | .. |
1112 | Djibouti | DJI | Adjusted net national income per capita (current US$) | NY.ADJ.NNTY.PC.CD | 747.6643999164722 | 736.7021081172434 | 753.1719080593109 | 760.4758792436212 | 767.510801220705 | 779.3056267713773 | 810.5165743201705 | 850.1825430048509 | 884.0111944109656 | 935.1158008140416 | 980.6867165928369 | 1119.3577351196345 | 1090.5752458263873 | 1073.6806023370793 | 1186.6398179158014 | 1282.0571891961629 | 1787.6227221678803 | 2071.8654689459413 | 2282.2807052094204 | 2315.1013273893386 | 2334.498464145747 | 2645.676451602475 | 2921.2465217753042 | 2957.4838917330126 | .. |
1113 | Djibouti | DJI | Adjusted net savings, excluding particulate emission damage (% of GNI) | NY.ADJ.SVNX.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.736952 | 16.478598 | 19.797382 | 13.885657 | 8.389561 | 13.948401 | 22.234417 | 30.289314 | .. |
1114 | Djibouti | DJI | Adjusted net savings, excluding particulate emission damage (current US$) | NY.ADJ.SVNX.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 236500000 | 361100000 | 475800000 | 350400000 | 220200000 | 400400000 | 718300000 | 995300000 | .. |
1115 | Djibouti | DJI | Adjusted net savings, including particulate emission damage (% of GNI) | NY.ADJ.SVNG.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.633464 | 14.339843 | 17.601845 | 11.601024 | 6.0292437 | 11.715457 | 20.150395 | 28.139598 | .. |
1116 | Djibouti | DJI | Adjusted net savings, including particulate emission damage (current US$) | NY.ADJ.SVNG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 194100000 | 314200000 | 423000000 | 292800000 | 158300000 | 336300000 | 651000000 | 924600000 | .. |
1117 | Djibouti | DJI | Adjusted savings: carbon dioxide damage (% of GNI) | NY.ADJ.DCO2.GN.ZS | 1.1261619 | 1.1454346 | 1.1371586 | 1.2252731 | 1.2653675 | 1.3314849 | 1.3503075 | 1.2812699 | 1.371312 | 1.3367227 | 1.3996354 | 1.2258716 | 1.1871377 | 1.302805 | 1.1457719 | 1.154499 | 0.90015065 | 0.70790322 | 0.78352627 | 0.69604549 | 0.67000039 | 0.66877888 | 0.59483844 | 0.5455845 | .. |
1118 | Djibouti | DJI | Adjusted savings: carbon dioxide damage (current US$) | NY.ADJ.DCO2.CD | 5798192.9 | 6011899.5 | 6236913.6 | 6947539.6 | 7400322.1 | 8074333 | 8681930.2 | 8822847.8 | 10002681 | 10585713 | 12202087 | 12648726 | 12711760 | 14929760 | 14297957 | 15946704 | 18137899 | 15510353 | 18830253 | 17565093 | 17586034 | 19198159 | 19217873 | 17926928 | .. |
1119 | Djibouti | DJI | Adjusted savings: consumption of fixed capital (% of GNI) | NY.ADJ.DKAP.GN.ZS | 3.3767211 | 3.558261 | 3.4895845 | 3.3912377 | 3.3989145 | 3.5737272 | 3.644336 | 4.175323 | 4.5657994 | 5.5795599 | 8.8910412 | 10.676276 | 14.963193 | 20.45438 | 17.95756 | 18.513923 | 21.094409 | 14.200256 | 12.521426 | 14.262378 | 15.433712 | 11.352036 | 11.627217 | 10.770969 | .. |
1120 | Djibouti | DJI | Adjusted savings: consumption of fixed capital (current US$) | NY.ADJ.DKAP.CD | 17385494 | 18675800 | 19139140 | 19228984 | 19878068 | 21671642 | 23431604 | 28751349 | 33304046 | 44185395 | 77512513 | 110200000 | 160200000 | 234400000 | 224100000 | 255700000 | 425000000 | 311100000 | 300900000 | 359900000 | 405100000 | 325900000 | 375600000 | 353900000 | .. |
1121 | Djibouti | DJI | Adjusted savings: education expenditure (% of GNI) | NY.ADJ.AEDU.GN.ZS | 6.3610052 | 6.8878394 | 7.4146736 | 9.2653951 | 7.5134123 | 8.0426727 | 8.4487687 | 8.727835 | 7.9085149 | 7.7664767 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | 7.8028827 | .. |
1122 | Djibouti | DJI | Adjusted savings: education expenditure (current US$) | NY.ADJ.AEDU.CD | 32750474 | 36151342 | 40666870 | 52536611 | 43941124 | 48772028 | 54322159 | 60100029 | 57686623 | 61503927 | 68025897 | 80511304 | 83552545 | 89418724 | 97371279 | 107800000 | 157200000 | 171000000 | 187500000 | 196900000 | 204800000 | 224000000 | 252100000 | 256400000 | .. |
1123 | Djibouti | DJI | Adjusted savings: energy depletion (% of GNI) | NY.ADJ.DNGY.GN.ZS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
1124 | Djibouti | DJI | Adjusted savings: energy depletion (current US$) | NY.ADJ.DNGY.CD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
1125 | Djibouti | DJI | Adjusted savings: gross savings (% of GNI) | NY.ADJ.ICTR.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 26.458463 | 24.38139 | 25.967893 | 21.541248 | 17.291786 | 18.447149 | 26.995092 | 34.111256 | .. |
1126 | Djibouti | DJI | Adjusted savings: mineral depletion (% of GNI) | NY.ADJ.DMIN.GN.ZS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
1127 | Djibouti | DJI | Adjusted savings: mineral depletion (current US$) | NY.ADJ.DMIN.CD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
1128 | Djibouti | DJI | Adjusted savings: natural resources depletion (% of GNI) | NY.ADJ.DRES.GN.ZS | 0.66088558 | 0.92823458 | 0.38225649 | 0.37144018 | 0.40714183 | 0.44282097 | 0.6027917 | 0.55440221 | 0.51416438 | 0.59845121 | 0.50897244 | 0.76538134 | 0.72816443 | 0.82546015 | 0.88223796 | 0.87589421 | 0.52983457 | 0.79751551 | 0.66844192 | 0.50005003 | 0.60139588 | 0.28081644 | 0.34150325 | 0.30827144 | .. |
1129 | Djibouti | DJI | Adjusted savings: net forest depletion (% of GNI) | NY.ADJ.DFOR.GN.ZS | 0.66088558 | 0.92823458 | 0.38225649 | 0.37144018 | 0.40714183 | 0.44282097 | 0.6027917 | 0.55440221 | 0.51416438 | 0.59845121 | 0.50897244 | 0.76538134 | 0.72816443 | 0.82546015 | 0.88223796 | 0.87589421 | 0.52983457 | 0.79751551 | 0.66844192 | 0.50005003 | 0.60139588 | 0.28081644 | 0.34150325 | 0.30827144 | .. |
1130 | Djibouti | DJI | Adjusted savings: net forest depletion (current US$) | NY.ADJ.DFOR.CD | 3402656.6 | 4871908.8 | 2096542 | 2106138.8 | 2381111.1 | 2685335.7 | 3875706.3 | 3817623.6 | 3750439.4 | 4739227.4 | 4437245.5 | 7897318.5 | 7797117.3 | 9459528.7 | 11009346 | 12098430 | 10676086 | 17473783 | 16064465 | 12619039 | 15785316 | 8061197.3 | 11033191 | 10129246 | .. |
1131 | Djibouti | DJI | Adjusted savings: net national savings (% of GNI) | NY.ADJ.NNAT.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.3640546 | 10.181134 | 13.446467 | 7.2788695 | 1.8580746 | 7.0951133 | 15.367876 | 23.340287 | .. |
1132 | Djibouti | DJI | Adjusted savings: net national savings (current US$) | NY.ADJ.NNAT.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 108100000 | 223100000 | 323200000 | 183700000 | 48770363 | 203700000 | 496500000 | 766900000 | .. |
1133 | Djibouti | DJI | Adjusted savings: particulate emission damage (% of GNI) | NY.ADJ.DPEM.GN.ZS | 4.6041495 | 4.5906358 | 4.3331956 | 4.1744439 | 3.9561516 | 3.7115875 | 3.4484926 | 3.2948575 | 3.1816066 | 3.0536096 | 2.962053 | 2.6676824 | 2.6981007 | 2.7264796 | 2.6831179 | 2.6430124 | 2.103488 | 2.1387554 | 2.1955364 | 2.2846331 | 2.3603173 | 2.2329436 | 2.084022 | 2.1497162 | .. |
1134 | Djibouti | DJI | Adjusted savings: particulate emission damage (current US$) | NY.ADJ.DPEM.CD | 23705071 | 24094297 | 23766050 | 23669917 | 23136990 | 22507648 | 22172410 | 22688448 | 23207409 | 24182005 | 25823316 | 27525544 | 28891013 | 31244649 | 33482321 | 36507035 | 42384964 | 46860717 | 52764671 | 57653981 | 61953129 | 64099521 | 67329997 | 70635818 | .. |
1135 | Djibouti | DJI | Agriculture, forestry, and fishing, value added (annual % growth) | NV.AGR.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -1.82111572153066 | 1.3302183611176446 | -4.364272483382592 | 35.13680869543242 | 14.992165591566462 | 12.868802673177399 | 11.48969287797614 | .. |
1136 | Djibouti | DJI | Agriculture, forestry, and fishing, value added (constant 2015 US$) | NV.AGR.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 25807431.27982465 | 25337448.09146454 | 25674491.478215855 | 24553986.71138367 | 33181474.049264453 | 38156095.58445284 | 43066328.23300503 | 48014517.08079844 | .. |
1137 | Djibouti | DJI | Agriculture, forestry, and fishing, value added per worker (constant 2015 US$) | NV.AGR.EMPL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 285.66108147133684 | 283.4402965416095 | 290.844030602869 | 281.93363913514526 | 384.7048885114221 | 451.17686327355193 | 462.11351692874246 | .. | .. |
1138 | Djibouti | DJI | Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%) | SI.SPR.PC40.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1139 | Djibouti | DJI | Annualized average growth rate in per capita real survey mean consumption or income, total population (%) | SI.SPR.PCAP.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1140 | Djibouti | DJI | Average working hours of children, study and work, ages 7-14 (hours per week) | SL.TLF.0714.SW.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1141 | Djibouti | DJI | Average working hours of children, study and work, female, ages 7-14 (hours per week) | SL.TLF.0714.SW.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1142 | Djibouti | DJI | Average working hours of children, study and work, male, ages 7-14 (hours per week) | SL.TLF.0714.SW.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1143 | Djibouti | DJI | Average working hours of children, working only, ages 7-14 (hours per week) | SL.TLF.0714.WK.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1144 | Djibouti | DJI | Average working hours of children, working only, female, ages 7-14 (hours per week) | SL.TLF.0714.WK.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1145 | Djibouti | DJI | Average working hours of children, working only, male, ages 7-14 (hours per week) | SL.TLF.0714.WK.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1146 | Djibouti | DJI | Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits) | per_si_allsi.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.47806485127851 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1147 | Djibouti | DJI | Benefit incidence of social protection and labor programs to poorest quintile (% of total SPL benefits) | per_allsp.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.2847267061281 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1148 | Djibouti | DJI | Benefit incidence of social safety net programs to poorest quintile (% of total safety net benefits) | per_sa_allsa.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 53.8215017451067 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1149 | Djibouti | DJI | Benefit incidence of unemployment benefits and ALMP to poorest quintile (% of total U/ALMP benefits) | per_lm_alllm.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1150 | Djibouti | DJI | Child employment in agriculture (% of economically active children ages 7-14) | SL.AGR.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1151 | Djibouti | DJI | Child employment in agriculture, female (% of female economically active children ages 7-14) | SL.AGR.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1152 | Djibouti | DJI | Child employment in agriculture, male (% of male economically active children ages 7-14) | SL.AGR.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1153 | Djibouti | DJI | Child employment in manufacturing (% of economically active children ages 7-14) | SL.MNF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1154 | Djibouti | DJI | Child employment in manufacturing, female (% of female economically active children ages 7-14) | SL.MNF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1155 | Djibouti | DJI | Child employment in manufacturing, male (% of male economically active children ages 7-14) | SL.MNF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1156 | Djibouti | DJI | Child employment in services (% of economically active children ages 7-14) | SL.SRV.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1157 | Djibouti | DJI | Child employment in services, female (% of female economically active children ages 7-14) | SL.SRV.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1158 | Djibouti | DJI | Child employment in services, male (% of male economically active children ages 7-14) | SL.SRV.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1159 | Djibouti | DJI | Children in employment, female (% of female children ages 7-14) | SL.TLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1160 | Djibouti | DJI | Children in employment, male (% of male children ages 7-14) | SL.TLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1161 | Djibouti | DJI | Children in employment, self-employed (% of children in employment, ages 7-14) | SL.SLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1162 | Djibouti | DJI | Children in employment, self-employed, female (% of female children in employment, ages 7-14) | SL.SLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1163 | Djibouti | DJI | Children in employment, self-employed, male (% of male children in employment, ages 7-14) | SL.SLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1164 | Djibouti | DJI | Children in employment, study and work (% of children in employment, ages 7-14) | SL.TLF.0714.SW.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1165 | Djibouti | DJI | Children in employment, study and work, female (% of female children in employment, ages 7-14) | SL.TLF.0714.SW.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1166 | Djibouti | DJI | Children in employment, study and work, male (% of male children in employment, ages 7-14) | SL.TLF.0714.SW.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1167 | Djibouti | DJI | Children in employment, total (% of children ages 7-14) | SL.TLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1168 | Djibouti | DJI | Children in employment, unpaid family workers (% of children in employment, ages 7-14) | SL.FAM.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1169 | Djibouti | DJI | Children in employment, unpaid family workers, female (% of female children in employment, ages 7-14) | SL.FAM.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1170 | Djibouti | DJI | Children in employment, unpaid family workers, male (% of male children in employment, ages 7-14) | SL.FAM.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1171 | Djibouti | DJI | Children in employment, wage workers (% of children in employment, ages 7-14) | SL.WAG.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1172 | Djibouti | DJI | Children in employment, wage workers, female (% of female children in employment, ages 7-14) | SL.WAG.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1173 | Djibouti | DJI | Children in employment, wage workers, male (% of male children in employment, ages 7-14) | SL.WAG.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1174 | Djibouti | DJI | Children in employment, work only (% of children in employment, ages 7-14) | SL.TLF.0714.WK.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1175 | Djibouti | DJI | Children in employment, work only, female (% of female children in employment, ages 7-14) | SL.TLF.0714.WK.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1176 | Djibouti | DJI | Children in employment, work only, male (% of male children in employment, ages 7-14) | SL.TLF.0714.WK.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1177 | Djibouti | DJI | Community health workers (per 1,000 people) | SH.MED.CMHW.P3 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1178 | Djibouti | DJI | Contributing family workers, female (% of female employment) (modeled ILO estimate) | SL.FAM.WORK.FE.ZS | 9.27999973297119 | 9.22999954223633 | 8.89000034332275 | 8.5 | 8.03999996185303 | 7.6100001335144 | 7.28999996185303 | 6.90999984741211 | 6.57000017166138 | 6.1399998664856 | 5.63000011444092 | 5.05000019073486 | 5.1399998664856 | 5.01999998092651 | 5.07999992370605 | 4.86999988555908 | 4.61999988555908 | 4.32000017166138 | 3.97000002861023 | 3.72000002861023 | 3.35999989509583 | 3.15000009536743 | 2.85999989509583 | .. | .. |
1179 | Djibouti | DJI | Contributing family workers, male (% of male employment) (modeled ILO estimate) | SL.FAM.WORK.MA.ZS | 5.28000020980835 | 5.3600001335144 | 5.17999982833862 | 5 | 4.78000020980835 | 4.53000020980835 | 4.34999990463257 | 4.13000011444092 | 3.95000004768372 | 3.67000007629395 | 3.32999992370605 | 2.94000005722046 | 3.02999997138977 | 2.99000000953674 | 3.02999997138977 | 2.91000008583069 | 2.78999996185303 | 2.59999990463257 | 2.35999989509583 | 2.19000005722046 | 1.97000002861023 | 1.82000005245209 | 1.62999999523163 | .. | .. |
1180 | Djibouti | DJI | Contributing family workers, total (% of total employment) (modeled ILO estimate) | SL.FAM.WORK.ZS | 6.75 | 6.78999996185303 | 6.55000019073486 | 6.30999994277954 | 6.01000022888184 | 5.69999980926514 | 5.48000001907349 | 5.19999980926514 | 4.96000003814697 | 4.63000011444092 | 4.21999979019165 | 3.75999999046326 | 3.84999990463257 | 3.76999998092651 | 3.8199999332428 | 3.67000007629395 | 3.50999999046326 | 3.26999998092651 | 3 | 2.78999996185303 | 2.51999998092651 | 2.34999990463257 | 2.11999988555908 | .. | .. |
1181 | Djibouti | DJI | Coverage of social insurance programs (% of population) | per_si_allsi.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.50192378981733 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1182 | Djibouti | DJI | Coverage of social insurance programs in 2nd quintile (% of population) | per_si_allsi.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.64577221745292 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1183 | Djibouti | DJI | Coverage of social insurance programs in 3rd quintile (% of population) | per_si_allsi.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 10.4667005378496 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1184 | Djibouti | DJI | Coverage of social insurance programs in 4th quintile (% of population) | per_si_allsi.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.4743027882944 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1185 | Djibouti | DJI | Coverage of social insurance programs in poorest quintile (% of population) | per_si_allsi.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.33148698049873 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1186 | Djibouti | DJI | Coverage of social insurance programs in richest quintile (% of population) | per_si_allsi.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.58643402720634 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1187 | Djibouti | DJI | Coverage of social protection and labor programs (% of population) | per_allsp.cov_pop_tot | .. | .. | .. | .. | .. | 2.94569267772138 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.9419414778464 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1188 | Djibouti | DJI | Coverage of social safety net programs (% of population) | per_sa_allsa.cov_pop_tot | .. | .. | .. | .. | .. | 2.8197486912029 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.52545220283742 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1189 | Djibouti | DJI | Coverage of social safety net programs in 2nd quintile (% of population) | per_sa_allsa.cov_q2_tot | .. | .. | .. | .. | .. | 2.46028638996766 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.37726794510168 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1190 | Djibouti | DJI | Coverage of social safety net programs in 3rd quintile (% of population) | per_sa_allsa.cov_q3_tot | .. | .. | .. | .. | .. | 2.95510706309743 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.83395055870151 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1191 | Djibouti | DJI | Coverage of social safety net programs in 4th quintile (% of population) | per_sa_allsa.cov_q4_tot | .. | .. | .. | .. | .. | 3.88785838990846 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.04507433519359 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1192 | Djibouti | DJI | Coverage of social safety net programs in poorest quintile (% of population) | per_sa_allsa.cov_q1_tot | .. | .. | .. | .. | .. | 2.36822416371687 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 30.8282557262149 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1193 | Djibouti | DJI | Coverage of social safety net programs in richest quintile (% of population) | per_sa_allsa.cov_q5_tot | .. | .. | .. | .. | .. | 2.42782812725454 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.57089569280909 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1194 | Djibouti | DJI | Coverage of unemployment benefits and ALMP (% of population) | per_lm_alllm.cov_pop_tot | .. | .. | .. | .. | .. | 0.125943986518477 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.32677046139511 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1195 | Djibouti | DJI | Coverage of unemployment benefits and ALMP in 2nd quintile (% of population) | per_lm_alllm.cov_q2_tot | .. | .. | .. | .. | .. | 0.267632399134343 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.28831197746183 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1196 | Djibouti | DJI | Coverage of unemployment benefits and ALMP in 3rd quintile (% of population) | per_lm_alllm.cov_q3_tot | .. | .. | .. | .. | .. | 0.135157409503489 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.24286396144475 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1197 | Djibouti | DJI | Coverage of unemployment benefits and ALMP in 4th quintile (% of population) | per_lm_alllm.cov_q4_tot | .. | .. | .. | .. | .. | 0.0472224407812826 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.14130124753209 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1198 | Djibouti | DJI | Coverage of unemployment benefits and ALMP in poorest quintile (% of population) | per_lm_alllm.cov_q1_tot | .. | .. | .. | .. | .. | 0.0136270353993481 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.19500224253495 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1199 | Djibouti | DJI | Coverage of unemployment benefits and ALMP in richest quintile (% of population) | per_lm_alllm.cov_q5_tot | .. | .. | .. | .. | .. | 0.1659480660055 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.76244935008948 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1200 | Djibouti | DJI | Current health expenditure (% of GDP) | SH.XPD.CHEX.GD.ZS | .. | .. | .. | 2.93908072 | 2.8072207 | 3.58787632 | 3.97685766 | 3.32442927 | 3.22467232 | 3.48426819 | 3.41498637 | 3.19098687 | 3.21451879 | 3.06150365 | 3.3765645 | 3.299927 | 2.92013574 | 2.96522927 | 3.07556486 | 2.7274003 | 2.46476841 | 2.26254249 | 1.79826784 | .. | .. |
1201 | Djibouti | DJI | Current health expenditure per capita (current US$) | SH.XPD.CHEX.PC.CD | .. | .. | .. | 31.95798492 | 31.04225731 | 40.19449615 | 46.11334229 | 40.28805161 | 40.95962524 | 47.32995605 | 50.44793701 | 53.96245575 | 55.32074356 | 56.2014122 | 68.77837372 | 72.22033691 | 67.53491211 | 73.12316895 | 82.28987885 | 76.8683548 | 72.23477173 | 71.08630371 | 61.80943298 | .. | .. |
1202 | Djibouti | DJI | Current health expenditure per capita, PPP (current international $) | SH.XPD.CHEX.PP.CD | .. | .. | .. | 70.82596588 | 68.89014435 | 90.61211395 | 103.79589844 | 90.15970612 | 91.60031128 | 105.36799622 | 109.86113739 | 109.2483902 | 111.12482452 | 109.8675766 | 130.63053894 | 130.61026001 | 119.84156799 | 127.26846313 | 141.57090759 | 128.72476196 | 121.08282471 | 121.57725525 | 104.1417923 | .. | .. |
1203 | Djibouti | DJI | Domestic general government health expenditure (% of current health expenditure) | SH.XPD.GHED.CH.ZS | .. | .. | .. | 48.00641632 | 44.59395599 | 35.86056137 | 37.82312775 | 43.28553009 | 43.34220123 | 49.54573059 | 50.82165146 | 57.3996048 | 59.26670837 | 60.67915726 | 63.49311447 | 57.27902222 | 61.89267731 | 59.48296738 | 55.04614258 | 48.48154068 | 46.43397141 | 49.40739822 | 53.66573334 | .. | .. |
1204 | Djibouti | DJI | Domestic general government health expenditure (% of GDP) | SH.XPD.GHED.GD.ZS | .. | .. | .. | 1.4109472 | 1.25185072 | 1.28663254 | 1.50417197 | 1.43899679 | 1.39764392 | 1.7263062 | 1.73555219 | 1.8316139 | 1.90513957 | 1.85769463 | 2.14388585 | 1.89016593 | 1.80735016 | 1.76380634 | 1.69297981 | 1.32228565 | 1.14448988 | 1.11786342 | 0.96505356 | .. | .. |
1205 | Djibouti | DJI | Domestic general government health expenditure (% of general government expenditure) | SH.XPD.GHED.GE.ZS | .. | .. | .. | 6.07547617 | 5.96840477 | 5.49563599 | 5.81530714 | 5.38615036 | 5.32781839 | 7.23246336 | 6.52659225 | 6.34888029 | 6.13991737 | 6.97048664 | 8.47449207 | 7.13329411 | 6.73504782 | 6.07299089 | 4.06950951 | 4.06950951 | 4.06950951 | 4.31139421 | 4.28400278 | .. | .. |
1206 | Djibouti | DJI | Domestic general government health expenditure per capita (current US$) | SH.XPD.GHED.PC.CD | .. | .. | .. | 15.3418831 | 13.84297028 | 14.41397308 | 17.44150759 | 17.43889722 | 17.75280199 | 23.4499744 | 25.63847374 | 30.97423629 | 32.78678409 | 34.10254198 | 43.66953435 | 41.36710264 | 41.79916365 | 43.49582708 | 45.2974055 | 37.26695846 | 33.54147372 | 35.12189169 | 33.17048432 | .. | .. |
1207 | Djibouti | DJI | Domestic general government health expenditure per capita, PPP (current international $) | SH.XPD.GHED.PP.CD | .. | .. | .. | 34.00100634 | 30.72084145 | 32.4940142 | 39.25885364 | 39.02610504 | 39.70158928 | 52.20534557 | 55.8332416 | 62.70814763 | 65.86002473 | 66.66671389 | 82.94140352 | 74.81227802 | 74.17314554 | 75.70305789 | 77.92932335 | 62.40774082 | 56.22356234 | 60.06815927 | 55.8884566 | .. | .. |
1208 | Djibouti | DJI | Domestic private health expenditure (% of current health expenditure) | SH.XPD.PVTD.CH.ZS | .. | .. | .. | 51.99358368 | 55.40604401 | 43.33620834 | 37.42380905 | 41.85393906 | 42.25835037 | 38.17026138 | 36.29995728 | 32.11385727 | 30.64589882 | 29.5377636 | 25.22384834 | 24.23509026 | 25.01658249 | 23.93575096 | 21.76084518 | 24.55328941 | 27.70902824 | 30.8210144 | 25.57739258 | .. | .. |
1209 | Djibouti | DJI | Domestic private health expenditure per capita (current US$) | SH.XPD.PVTD.PC.CD | .. | .. | .. | 16.616103 | 17.1992863 | 17.41877171 | 17.25736932 | 16.86213724 | 17.30886212 | 18.06596988 | 18.31258079 | 17.32942738 | 16.95353746 | 16.60064131 | 17.34855246 | 17.50266525 | 16.8949278 | 17.50257911 | 17.90697349 | 18.87370874 | 20.01555327 | 21.90951819 | 15.80924087 | .. | .. |
1210 | Djibouti | DJI | Domestic private health expenditure per capita, PPP (current international $) | SH.XPD.PVTD.PP.CD | .. | .. | .. | 36.82495948 | 38.16930448 | 39.26785572 | 38.8443793 | 37.73538721 | 38.70878159 | 40.21924224 | 39.87954812 | 35.08387682 | 34.05519715 | 32.45242554 | 32.95004885 | 31.65351632 | 29.98026347 | 30.46266385 | 30.80702552 | 31.60616192 | 33.55087247 | 37.47134236 | 26.63675525 | .. | .. |
1211 | Djibouti | DJI | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 0.449999988079071 | 0.469999998807907 | 0.469999998807907 | 0.469999998807907 | 0.490000009536743 | 0.479999989271164 | 0.479999989271164 | 0.479999989271164 | 0.5 | 0.490000009536743 | 0.479999989271164 | 0.469999998807907 | 0.469999998807907 | 0.490000009536743 | 0.5 | 0.490000009536743 | 0.540000021457672 | 0.540000021457672 | 0.529999971389771 | 0.519999980926514 | 0.509999990463257 | 0.519999980926514 | 0.519999980926514 | .. | .. |
1212 | Djibouti | DJI | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 1.01999998092651 | 1.0900000333786 | 1.07000005245209 | 1.08000004291534 | 1.12999999523163 | 1.11000001430511 | 1.10000002384186 | 1.0900000333786 | 1.12999999523163 | 1.10000002384186 | 1.08000004291534 | 1.02999997138977 | 1.01999998092651 | 1.08000004291534 | 1.0900000333786 | 1.05999994277954 | 1.19000005722046 | 1.16999995708466 | 1.13999998569489 | 1.08000004291534 | 1.05999994277954 | 1.05999994277954 | 1.04999995231628 | .. | .. |
1213 | Djibouti | DJI | Employers, total (% of total employment) (modeled ILO estimate) | SL.EMP.MPYR.ZS | 0.810000002384186 | 0.860000014305115 | 0.839999973773956 | 0.850000023841858 | 0.889999985694885 | 0.870000004768372 | 0.860000014305115 | 0.860000014305115 | 0.879999995231628 | 0.860000014305115 | 0.850000023841858 | 0.810000002384186 | 0.810000002384186 | 0.850000023841858 | 0.860000014305115 | 0.839999973773956 | 0.930000007152557 | 0.930000007152557 | 0.899999976158142 | 0.860000014305115 | 0.850000023841858 | 0.850000023841858 | 0.839999973773956 | .. | .. |
1214 | Djibouti | DJI | Employment in agriculture (% of total employment) (modeled ILO estimate) | SL.AGR.EMPL.ZS | 40.8699989318848 | 40.7299995422363 | 40.3899993896484 | 40.0800018310547 | 39.5999984741211 | 38.9700012207031 | 38.310001373291 | 37.6500015258789 | 36.939998626709 | 36.0999984741211 | 35.2299995422363 | 34.2999992370605 | 33.6399993896484 | 32.8199996948242 | 31.8299999237061 | 30.9899997711182 | 30.1499996185303 | 29.1900005340576 | 28.2099990844727 | 27.2900009155273 | 26.4500007629395 | 25.4699993133545 | 24.5499992370605 | .. | .. |
1215 | Djibouti | DJI | Employment in agriculture, female (% of female employment) (modeled ILO estimate) | SL.AGR.EMPL.FE.ZS | 42.7400016784668 | 42.2299995422363 | 41.6100006103516 | 40.9000015258789 | 40.0499992370605 | 39.1399993896484 | 38.2200012207031 | 37.2900009155273 | 36.310001373291 | 35.2999992370605 | 34.25 | 33.2000007629395 | 32.2299995422363 | 31.2199993133545 | 30.1399993896484 | 29.1499996185303 | 28.1599998474121 | 27.1100006103516 | 26.0799999237061 | 25.0699996948242 | 24.1100006103516 | 23.1100006103516 | 22.1399993896484 | .. | .. |
1216 | Djibouti | DJI | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 39.7799987792969 | 39.8499984741211 | 39.6699981689453 | 39.5900001525879 | 39.3300018310547 | 38.8699989318848 | 38.3699989318848 | 37.8800010681152 | 37.3300018310547 | 36.5999984741211 | 35.8400001525879 | 35 | 34.5299987792969 | 33.8400001525879 | 32.8899993896484 | 32.1599998474121 | 31.4300003051758 | 30.5200004577637 | 29.5900001525879 | 28.7299995422363 | 27.9699993133545 | 27.0200004577637 | 26.1399993896484 | .. | .. |
1217 | Djibouti | DJI | Employment in industry (% of total employment) (modeled ILO estimate) | SL.IND.EMPL.ZS | 14.8100004196167 | 14.5699996948242 | 14.3299999237061 | 14.1099996566772 | 13.9099998474121 | 13.7299995422363 | 13.5799999237061 | 13.4399995803833 | 13.3400001525879 | 13.2700004577637 | 13.210000038147 | 13.1599998474121 | 13.1400003433228 | 13.1300001144409 | 13.1300001144409 | 13.1499996185303 | 13.1800003051758 | 13.25 | 13.3000001907349 | 13.3500003814697 | 13.3999996185303 | 13.4200000762939 | 13.4399995803833 | .. | .. |
1218 | Djibouti | DJI | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 9.1899995803833 | 9.07999992370605 | 8.9399995803833 | 8.85000038146973 | 8.75 | 8.60999965667725 | 8.47999954223633 | 8.35000038146973 | 8.22999954223633 | 8.10000038146973 | 7.96999979019165 | 7.82000017166138 | 7.76000022888184 | 7.65999984741211 | 7.53000020980835 | 7.44000005722046 | 7.34999990463257 | 7.28999996185303 | 7.19000005722046 | 7.09999990463257 | 7.03999996185303 | 6.90000009536743 | 6.80000019073486 | .. | .. |
1219 | Djibouti | DJI | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 18.1000003814697 | 17.7800006866455 | 17.5 | 17.2399997711182 | 17.0200004577637 | 16.8600006103516 | 16.7399997711182 | 16.6499996185303 | 16.5699996948242 | 16.5400009155273 | 16.5200004577637 | 16.5200004577637 | 16.5300006866455 | 16.5799999237061 | 16.6700000762939 | 16.7700004577637 | 16.9099998474121 | 17.0799999237061 | 17.25 | 17.4099998474121 | 17.5599994659424 | 17.7000007629395 | 17.8099994659424 | .. | .. |
1220 | Djibouti | DJI | Employment in services (% of total employment) (modeled ILO estimate) | SL.SRV.EMPL.ZS | 44.3199996948242 | 44.7099990844727 | 45.2799987792969 | 45.810001373291 | 46.4900016784668 | 47.2999992370605 | 48.1100006103516 | 48.9099998474121 | 49.7200012207031 | 50.6399993896484 | 51.5699996948242 | 52.5400009155273 | 53.2200012207031 | 54.0499992370605 | 55.0400009155273 | 55.8600006103516 | 56.6699981689453 | 57.560001373291 | 58.5 | 59.3600006103516 | 60.1500015258789 | 61.1100006103516 | 62 | .. | .. |
1221 | Djibouti | DJI | Employment in services, female (% of female employment) (modeled ILO estimate) | SL.SRV.EMPL.FE.ZS | 48.0800018310547 | 48.689998626709 | 49.4500007629395 | 50.25 | 51.2099990844727 | 52.2400016784668 | 53.2999992370605 | 54.3699989318848 | 55.4500007629395 | 56.5999984741211 | 57.7799987792969 | 58.9799995422363 | 60.0200004577637 | 61.1199989318848 | 62.3300018310547 | 63.4199981689453 | 64.4899978637695 | 65.5999984741211 | 66.7399978637695 | 67.8300018310547 | 68.8499984741211 | 69.9899978637695 | 71.0599975585938 | .. | .. |
1222 | Djibouti | DJI | Employment in services, male (% of male employment) (modeled ILO estimate) | SL.SRV.EMPL.MA.ZS | 42.1199989318848 | 42.3699989318848 | 42.8300018310547 | 43.1599998474121 | 43.6500015258789 | 44.2700004577637 | 44.8800010681152 | 45.4700012207031 | 46.0900001525879 | 46.8499984741211 | 47.6399993896484 | 48.4799995422363 | 48.939998626709 | 49.5900001525879 | 50.439998626709 | 51.060001373291 | 51.6599998474121 | 52.4000015258789 | 53.1599998474121 | 53.8699989318848 | 54.4700012207031 | 55.2799987792969 | 56.0499992370605 | .. | .. |
1223 | Djibouti | DJI | Employment to population ratio, 15+, female (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.FE.ZS | 9.22700023651123 | 9.26799964904785 | 9.33399963378906 | 9.42399978637695 | 9.49899959564209 | 9.60799980163574 | 9.72799968719482 | 9.83699989318848 | 9.92899990081787 | 10.0799999237061 | 10.2130002975464 | 10.3470001220703 | 10.4779996871948 | 10.6339998245239 | 10.7220001220703 | 10.7969999313354 | 10.8760004043579 | 10.9659996032715 | 11.0609998703003 | 11.1029996871948 | 11.1800003051758 | 11.2720003128052 | 11.3439998626709 | 10.4650001525879 | 10.4409999847412 |
1224 | Djibouti | DJI | Employment to population ratio, 15+, female (%) (national estimate) | SL.EMP.TOTL.SP.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.6700000762939 | .. | .. | .. | .. |
1225 | Djibouti | DJI | Employment to population ratio, 15+, male (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.MA.ZS | 41.2770004272461 | 41.2220001220703 | 41.125 | 40.8959999084473 | 40.8240013122559 | 40.6669998168945 | 40.4070014953613 | 40.0670013427734 | 39.6580009460449 | 38.9570007324219 | 38.193000793457 | 37.4339981079102 | 36.7239990234375 | 36.1679992675781 | 35.9099998474121 | 35.7319984436035 | 35.6339988708496 | 35.5530014038086 | 35.4370002746582 | 35.3709983825684 | 35.2480010986328 | 34.9379997253418 | 34.6279983520508 | 33.2970008850098 | 33.3059997558594 |
1226 | Djibouti | DJI | Employment to population ratio, 15+, male (%) (national estimate) | SL.EMP.TOTL.SP.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 36.6399993896484 | .. | .. | .. | .. |
1227 | Djibouti | DJI | Employment to population ratio, 15+, total (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.ZS | 25.2849998474121 | 25.2779998779297 | 25.2549991607666 | 25.1709995269775 | 25.1399993896484 | 25.0769996643066 | 24.9860000610352 | 24.8899993896484 | 24.798999786377 | 24.6359996795654 | 24.4699993133545 | 24.3110008239746 | 24.1439990997314 | 24.0200004577637 | 23.9810009002686 | 23.9400005340576 | 23.9200000762939 | 23.9080009460449 | 23.882999420166 | 23.882999420166 | 23.8600006103516 | 23.742000579834 | 23.6189994812012 | 22.5139999389648 | 22.5060005187988 |
1228 | Djibouti | DJI | Employment to population ratio, 15+, total (%) (national estimate) | SL.EMP.TOTL.SP.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 23.8600006103516 | .. | .. | .. | .. |
1229 | Djibouti | DJI | Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate) | SL.EMP.1524.SP.FE.ZS | 8.48799991607666 | 8.32400035858154 | 8.13199996948242 | 7.82600021362305 | 7.62400007247925 | 7.36100006103516 | 7.0460000038147 | 6.71700000762939 | 6.39400005340576 | 5.92000007629395 | 5.42999982833862 | 4.93300008773804 | 4.41300010681152 | 3.95099997520447 | 3.69899988174438 | 3.45499992370605 | 3.2409999370575 | 3.04299998283386 | 2.83599996566772 | 2.66799998283386 | 2.47499990463257 | 2.42700004577637 | 2.37599992752075 | 1.76999998092651 | 1.89499998092651 |
1230 | Djibouti | DJI | Employment to population ratio, ages 15-24, female (%) (national estimate) | SL.EMP.1524.SP.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.98000001907349 | .. | .. | .. | .. |
1231 | Djibouti | DJI | Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate) | SL.EMP.1524.SP.MA.ZS | 18.5659999847412 | 18.0790004730225 | 17.5049991607666 | 16.6070003509521 | 16.0310001373291 | 15.2880001068115 | 14.4169998168945 | 13.5380001068115 | 12.7019996643066 | 11.4259996414185 | 10.1850004196167 | 9.00599956512451 | 7.8439998626709 | 6.87599992752075 | 6.39400005340576 | 5.93900012969971 | 5.55000019073486 | 5.19700002670288 | 4.83300018310547 | 4.55999994277954 | 4.22499990463257 | 4.07000017166138 | 3.9210000038147 | 3.02600002288818 | 3.30999994277954 |
1232 | Djibouti | DJI | Employment to population ratio, ages 15-24, male (%) (national estimate) | SL.EMP.1524.SP.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.01000022888184 | .. | .. | .. | .. |
1233 | Djibouti | DJI | Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) | SL.EMP.1524.SP.ZS | 13.5570001602173 | 13.2329998016357 | 12.8489999771118 | 12.2440004348755 | 11.8479995727539 | 11.3369998931885 | 10.7390003204346 | 10.1409997940063 | 9.57699966430664 | 8.71599960327148 | 7.87099981307983 | 7.05299997329712 | 6.22300004959106 | 5.51300001144409 | 5.14900016784668 | 4.7960000038147 | 4.48999977111816 | 4.20900011062622 | 3.91799998283386 | 3.69600009918213 | 3.42600011825562 | 3.32100009918213 | 3.21700000762939 | 2.45499992370605 | 2.66700005531311 |
1234 | Djibouti | DJI | Employment to population ratio, ages 15-24, total (%) (national estimate) | SL.EMP.1524.SP.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.99000000953674 | .. | .. | .. | .. |
1235 | Djibouti | DJI | Exports of goods and services (annual % growth) | NE.EXP.GNFS.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.892568186058682 | 1.3390909147941414 | -25.13039495728256 | 52.52605574599252 | 9.860969304551375 | 9.21487315697658 | -29.704691173842463 | .. |
1236 | Djibouti | DJI | Exports of goods and services (constant 2015 US$) | NE.EXP.GNFS.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3254665297.6658177 | 3478995322.5354238 | 3525582232.8256087 | 2639589493.1727514 | 4026061741.822032 | 4423070454.365389 | 4830650786.378867 | 3395720888.598232 | .. |
1237 | Djibouti | DJI | External health expenditure (% of current health expenditure) | SH.XPD.EHEX.CH.ZS | .. | .. | .. | 0 | 0 | 20.80323029 | 24.7530632 | 14.86052895 | 14.39944839 | 12.28400421 | 12.87839222 | 10.48653603 | 10.08739281 | 9.78307915 | 11.28303623 | 18.48588943 | 13.09074306 | 16.58128166 | 23.19301224 | 26.96517181 | 25.85700226 | 19.77158546 | 20.75687408 | .. | .. |
1238 | Djibouti | DJI | External health expenditure per capita (current US$) | SH.XPD.EHEX.PC.CD | .. | .. | .. | 0 | 0 | 8.36175363 | 11.41446368 | 5.98701737 | 5.89795975 | 5.8140142 | 6.4968837 | 5.65879255 | 5.58042065 | 5.49822847 | 7.76028924 | 13.35057176 | 8.84082198 | 12.12475824 | 19.0855017 | 20.72768289 | 18.67774527 | 14.05488918 | 12.82970493 | .. | .. |
1239 | Djibouti | DJI | External health expenditure per capita, PPP (current international $) | SH.XPD.EHEX.PP.CD | .. | .. | .. | 0 | 0 | 18.85024619 | 25.692662 | 13.3982078 | 13.18993902 | 12.94340946 | 14.1483491 | 11.45637281 | 11.20959717 | 10.74843115 | 14.73909194 | 24.144468 | 15.68815063 | 21.10274333 | 32.83455679 | 34.71085153 | 31.30838509 | 24.03775199 | 21.61657937 | .. | .. |
1240 | Djibouti | DJI | Female share of employment in senior and middle management (%) | SL.EMP.SMGT.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1241 | Djibouti | DJI | Final consumption expenditure (annual % growth) | NE.CON.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.464302836088478 | 9.072814795832713 | 14.651109165245856 | 8.711069302860025 | 0.7794015066011895 | 3.7222394810202672 | 8.194237050143926 | .. |
1242 | Djibouti | DJI | Final consumption expenditure (constant 2015 US$) | NE.CON.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1654223713.1289177 | 1810784454.925826 | 1975073574.872975 | 2264443760.4215384 | 2461701025.7161484 | 2480887560.598597 | 2573232136.8589187 | 2784088878.003622 | .. |
1243 | Djibouti | DJI | GDP (constant 2015 US$) | NY.GDP.MKTP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2105985489.123518 | 2254700565.115364 | 2424391785.4389744 | 2597091693.865469 | 2738843335.3025575 | 2869607134.048346 | 3028730597.3367143 | 3065136606.435847 | 3197233617.0244007 |
1244 | Djibouti | DJI | GDP growth (annual %) | NY.GDP.MKTP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.061543242339212 | 7.526108918810166 | 7.123432337287198 | 5.458091517211997 | 4.774416888337399 | 5.545130599946702 | 1.2020220329647486 | 4.30966144579628 |
1245 | Djibouti | DJI | GDP per capita (constant 2015 US$) | NY.GDP.PCAP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2384.235283668802 | 2508.827198536747 | 2652.5132280803396 | 2795.22567541598 | 2901.009782123247 | 2992.531344068654 | 3110.994628292657 | 3102.3587061927474 | 3190.2246933730603 |
1246 | Djibouti | DJI | GDP per capita growth (annual %) | NY.GDP.PCAP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.225655191052539 | 5.727219061854754 | 5.380272785252927 | 3.7844567484349767 | 3.154817419416716 | 3.9586313593273985 | -0.277593603710244 | 2.8322317146924405 |
1247 | Djibouti | DJI | GDP per capita, PPP (constant 2017 international $) | NY.GDP.PCAP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4031.2233463990647 | 4241.881178463089 | 4484.823005897256 | 4726.118717550307 | 4904.976636295689 | 5059.719693635865 | 5260.015344122198 | 5245.413877972738 | 5393.976153391561 |
1248 | Djibouti | DJI | GDP per capita, PPP (current international $) | NY.GDP.PCAP.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4103.941203662569 | 4289.034249936545 | 4563.377343226545 | 4695.100996049126 | 4904.976636295689 | 5180.596948273089 | 5482.012135571669 | 5532.682123082326 | 5925.79529621207 |
1249 | Djibouti | DJI | GDP per person employed (constant 2017 PPP $) | SL.GDP.PCAP.EM.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 24529.75287426312 | 25694.622138852752 | 27041.72086779088 | 28404.37306019153 | 29360.074828984558 | 30260.52369559356 | 31457.437286165372 | 32774.158760141036 | 33568.22354073871 |
1250 | Djibouti | DJI | GDP, PPP (constant 2017 international $) | NY.GDP.MKTP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3560763456.9809084 | 3812208308.2530274 | 4099119257.74408 | 4391117244.494189 | 4630788442.32676 | 4851881587.780385 | 5120924758.377575 | 5182479402.264821 | 5405826719.000562 |
1251 | Djibouti | DJI | GDP, PPP (current international $) | NY.GDP.MKTP.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3624994849.430332 | 3854585103.657723 | 4170917764.9543757 | 4362298152.146175 | 4630788442.32676 | 4967793567.428875 | 5337051288.670748 | 5466301002.969584 | 5938814268.477848 |
1252 | Djibouti | DJI | General government final consumption expenditure (annual % growth) | NE.CON.GOVT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.863059732840455 | 4.852308378578172 | 25.041320618748756 | 3.495778098885012 | 1.8032812585591813 | -3.8906932525250397 | 1.625003414025585 | .. |
1253 | Djibouti | DJI | General government final consumption expenditure (constant 2015 US$) | NE.CON.GOVT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 419052863.27950317 | 460384297.4969388 | 482723563.33804107 | 603603918.5357686 | 624704572.1239538 | 635969752.5944273 | 611226120.3421358 | 621158565.6651117 | .. |
1254 | Djibouti | DJI | Gini index | SI.POV.GINI | .. | .. | .. | .. | .. | 40 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 45.1 | 44.1 | .. | .. | .. | 41.6 | .. | .. | .. | .. |
1255 | Djibouti | DJI | GNI (constant 2015 US$) | NY.GNP.MKTP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2077204890.583858 | 2230683815.886609 | 2397387660.996731 | 2517275031.1541142 | 2613210502.790188 | 2729392378.7423973 | 2936182677.885242 | 2969770287.9328895 | .. |
1256 | Djibouti | DJI | GNI growth (annual %) | NY.GNP.MKTP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.388723471549866 | 7.473217132920439 | 5.000750279474602 | 3.8110842259492443 | 4.445944015155277 | 7.576422531014984 | 1.1439209930847625 | .. |
1257 | Djibouti | DJI | GNI per capita (constant 2015 US$) | NY.GNP.PCAP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2351.6520969005383 | 2482.1035286101132 | 2622.968169511017 | 2709.319742458823 | 2767.9382510223363 | 2846.3102655191265 | 3015.932994046822 | 3005.834287716917 | .. |
1258 | Djibouti | DJI | GNI per capita growth (annual %) | NY.GNP.PCAP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.547224943753747 | 5.6752121447481585 | 3.2921319424132918 | 2.1635876949065675 | 2.83142206903797 | 5.959389971730957 | -0.3348451822318168 | .. |
1259 | Djibouti | DJI | GNI per capita, Atlas method (current US$) | NY.GNP.PCAP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2540 | 2640 | 2730 | 2910 | 3110 | 3120 | 3300 |
1260 | Djibouti | DJI | GNI per capita, PPP (constant 2017 international $) | NY.GNP.PCAP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3976.2163743629526 | 4196.786040899236 | 4434.962551981444 | 4580.967370789293 | 4680.080617131376 | 4812.593452573602 | 5099.394664166453 | 5082.319586810507 | .. |
1261 | Djibouti | DJI | GNI per capita, PPP (current international $) | NY.GNP.PCAP.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4050 | 4240 | 4510 | 4550 | 4680 | 4930 | 5320 | 5360 | 5740 |
1262 | Djibouti | DJI | GNI, Atlas method (current US$) | NY.GNP.ATLS.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2325113306.4557157 | 2455248777.391414 | 2581255192.7612205 | 2789282789.9440904 | 3031712133.2074413 | 3081144942.481589 | 3311894454.7920976 |
1263 | Djibouti | DJI | GNI, PPP (constant 2017 international $) | NY.GNP.MKTP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3512176018.6092987 | 3771680992.4584293 | 4053546902.5859365 | 4256254660.645636 | 4418464110.633732 | 4614906551.322236 | 4964551371.0619 | 5021341916.407954 | .. |
1264 | Djibouti | DJI | GNI, PPP (current international $) | NY.GNP.MKTP.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3575606060.0196753 | 3813420038.5353227 | 4124459934.565877 | 4228354172.7359476 | 4418464110.633732 | 4725369385.990628 | 5174904158.211224 | 5296929188.23756 | 5753838564.209508 |
1265 | Djibouti | DJI | Gross capital formation (annual % growth) | NE.GDI.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -95.69886071106112 | -274.82584782433923 | -644.031969823646 | -8.223592943301199 | -91.7128307881405 | 182.28357936113503 | -53.862541974364156 | .. |
1266 | Djibouti | DJI | Gross capital formation (constant 2015 US$) | NE.GDI.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1272220558.521179 | 54719978.28451212 | -95664665.96519263 | 520446366.67564857 | 477646975.9920425 | 39583413.13579054 | 111737475.43301524 | 51552830.82681257 | .. |
1267 | Djibouti | DJI | Gross fixed capital formation (annual % growth) | NE.GDI.FTOT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 17.92590548669841 | 19.76395678212957 | -4.1101497097727275 | -0.6843088749788961 | 14.889586146250792 | 7.286120245357779 | 0.9678759169680973 | .. |
1268 | Djibouti | DJI | Gross fixed capital formation (constant 2015 US$) | NE.GDI.FTOT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 520738738.4382655 | 614085872.5233346 | 735453538.9740098 | 705225297.4763563 | 700399378.1771293 | 804685946.9586178 | 863316332.6515186 | 871672163.5225048 | .. |
1269 | Djibouti | DJI | Gross national expenditure (constant 2015 US$) | NE.DAB.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2926444271.650097 | 1865504433.210338 | 1879408908.9077826 | 2784890127.097187 | 2939348001.708191 | 2520470973.7343874 | 2684969612.291934 | 2835641708.830435 | .. |
1270 | Djibouti | DJI | Gross value added at basic prices (GVA) (constant 2015 US$) | NY.GDP.FCST.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1963712475.320733 | 2102512166.6155105 | 2248396827.0491385 | 2419652716.188731 | 2548816961.499913 | 2669989705.3811746 | 2829495579.709706 | 2886325578.312405 | .. |
1271 | Djibouti | DJI | Hospital beds (per 1,000 people) | SH.MED.BEDS.ZS | .. | .. | .. | 1.75 | 1.75 | 1.75 | 1.61 | 1.61 | 1.61 | 1.61 | .. | .. | .. | 1.42 | 1.42 | 1.42 | 1.42 | 1.4 | 1.4 | 1.4 | 1.4 | .. | .. | .. | .. |
1272 | Djibouti | DJI | Households and NPISHs Final consumption expenditure (annual % growth) | NE.CON.PRVT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.32992629641862 | 10.502012989799582 | 11.31254229701608 | 10.593520388745532 | 0.4335520616808566 | 6.32883140363252 | 10.227296820627018 | .. |
1273 | Djibouti | DJI | Households and NPISHs Final consumption expenditure (constant 2015 US$) | NE.CON.PRVT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1235567107.6962838 | 1350844608.1871383 | 1492710484.4109588 | 1661573989.331942 | 1837593168.6659138 | 1845560091.7339714 | 1962362478.39254 | 2163059113.754358 | .. |
1274 | Djibouti | DJI | Households and NPISHs Final consumption expenditure per capita (constant 2015 US$) | NE.CON.PRVT.PC.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1398.8242982310896 | 1503.1091748550214 | 1633.1752188048354 | 1788.351859645992 | 1946.409347315887 | 2008.2309916933382 | 2076.9465286674827 | 1944.2516715851102 | .. |
1275 | Djibouti | DJI | Households and NPISHs Final consumption expenditure per capita growth (annual %) | NE.CON.PRVT.PC.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.455180522372046 | 8.653133526535697 | 9.501530457626913 | 8.83816497393208 | 3.1761892462499617 | 3.421694877649699 | -6.388939496073888 | .. |
1276 | Djibouti | DJI | Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $) | NE.CON.PRVT.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1965845976.319057 | 2149257957.0107365 | 2374973306.840305 | 2643643166.7194557 | 2923698044.5915594 | 2936373797.741209 | 3122211944.780691 | 3441529827.742484 | .. |
1277 | Djibouti | DJI | Households and NPISHs Final consumption expenditure, PPP (current international $) | NE.CON.PRVT.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2060762625.1352239 | 2292283592.3185754 | 2562101570.776766 | 2703772769.992443 | 2923698044.5915594 | 3325160721.3718715 | 3440491942.8895006 | 2980656495.375561 | .. |
1278 | Djibouti | DJI | Imports of goods and services (annual % growth) | NE.IMP.GNFS.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | -22.62267733897157 | -3.2323524662395187 | -6.709414142849582 | 50.35729027297296 | -2.880606886682841 | 10.051553003707099 | -29.539182288317917 | .. |
1279 | Djibouti | DJI | Imports of goods and services (constant 2015 US$) | NE.IMP.GNFS.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3980702498.32747 | 3080161016.3064666 | 2980599355.731736 | 2780618601.0165877 | 4180862781.31479 | 4060428560.113476 | 4468564689.010943 | 3148587219.8525944 | .. |
1280 | Djibouti | DJI | Income share held by fourth 20% | SI.DST.04TH.20 | .. | .. | .. | .. | .. | 21.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 21.2 | 20.9 | .. | .. | .. | 21.5 | .. | .. | .. | .. |
1281 | Djibouti | DJI | Income share held by highest 10% | SI.DST.10TH.10 | .. | .. | .. | .. | .. | 30.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34.4 | 34.1 | .. | .. | .. | 32.3 | .. | .. | .. | .. |
1282 | Djibouti | DJI | Income share held by highest 20% | SI.DST.05TH.20 | .. | .. | .. | .. | .. | 46.5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 50.3 | 50 | .. | .. | .. | 47.6 | .. | .. | .. | .. |
1283 | Djibouti | DJI | Income share held by lowest 10% | SI.DST.FRST.10 | .. | .. | .. | .. | .. | 2.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.3 | 1.7 | .. | .. | .. | 1.9 | .. | .. | .. | .. |
1284 | Djibouti | DJI | Income share held by lowest 20% | SI.DST.FRST.20 | .. | .. | .. | .. | .. | 6 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.3 | 4.9 | .. | .. | .. | 5.4 | .. | .. | .. | .. |
1285 | Djibouti | DJI | Income share held by second 20% | SI.DST.02ND.20 | .. | .. | .. | .. | .. | 10.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.8 | 9.7 | .. | .. | .. | 10.4 | .. | .. | .. | .. |
1286 | Djibouti | DJI | Income share held by third 20% | SI.DST.03RD.20 | .. | .. | .. | .. | .. | 15.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.4 | 14.6 | .. | .. | .. | 15.1 | .. | .. | .. | .. |
1287 | Djibouti | DJI | Industry (including construction), value added (annual % growth) | NV.IND.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.42289471139901 | 8.567577121256448 | 6.114837744190282 | 14.10174120421334 | 19.057981942840314 | 13.410270480478957 | -4.4329812062661915 | .. |
1288 | Djibouti | DJI | Industry (including construction), value added (constant 2015 US$) | NV.IND.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 236878603.18931758 | 254461852.49789327 | 276263067.9548281 | 293156106.30738795 | 334496221.74320436 | 398244451.28250736 | 451650109.37299085 | 431628544.9064055 | .. |
1289 | Djibouti | DJI | Industry (including construction), value added per worker (constant 2015 US$) | NV.IND.EMPL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5543.361962206469 | 5769.383062187684 | 6106.921024124329 | 6330.468350497537 | 7042.614128229066 | 10010.227959837603 | 10720.362870042944 | .. | .. |
1290 | Djibouti | DJI | International migrant stock (% of population) | SM.POP.TOTL.ZS | .. | .. | .. | 13.9098098156283 | .. | .. | .. | .. | 11.8307155905787 | .. | .. | .. | .. | 12.2261381171446 | .. | .. | .. | .. | 12.6541204084874 | .. | .. | .. | .. | .. | .. |
1291 | Djibouti | DJI | International migrant stock, total | SM.POP.TOTL | .. | .. | .. | 100507 | .. | .. | .. | .. | 92091 | .. | .. | .. | .. | 101575 | .. | .. | .. | .. | 112351 | .. | .. | .. | .. | .. | .. |
1292 | Djibouti | DJI | Labor force participation rate for ages 15-24, female (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.FE.ZS | 18.4080009460449 | 18.2390003204346 | 18.0259990692139 | 17.6749992370605 | 17.4589996337891 | 17.1509990692139 | 16.7630004882813 | 16.3449993133545 | 15.918999671936 | 15.2670001983643 | 14.6079998016357 | 13.9519996643066 | 13.2930002212524 | 12.7030000686646 | 12.4079999923706 | 12.16100025177 | 11.956000328064 | 11.7639999389648 | 11.5559997558594 | 11.4289999008179 | 11.2410001754761 | 11.0389995574951 | 10.8509998321533 | 10.1169996261597 | 10.6230001449585 |
1293 | Djibouti | DJI | Labor force participation rate for ages 15-24, female (%) (national estimate) | SL.TLF.ACTI.1524.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.7200002670288 | .. | .. | .. | .. |
1294 | Djibouti | DJI | Labor force participation rate for ages 15-24, male (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.MA.ZS | 39.7270011901855 | 39.0279998779297 | 38.1590003967285 | 36.8079986572266 | 35.9539985656738 | 34.7890014648438 | 33.3959999084473 | 31.9650001525879 | 30.5690002441406 | 28.4220008850098 | 26.3390007019043 | 24.3519992828369 | 22.4400005340576 | 20.8040008544922 | 20.0240001678467 | 19.3700008392334 | 18.8290004730225 | 18.3339996337891 | 17.8080005645752 | 17.5009994506836 | 17.0289993286133 | 16.5400009155273 | 16.0939998626709 | 15.3360004425049 | 15.4809999465942 |
1295 | Djibouti | DJI | Labor force participation rate for ages 15-24, male (%) (national estimate) | SL.TLF.ACTI.1524.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 17.8899993896484 | .. | .. | .. | .. |
1296 | Djibouti | DJI | Labor force participation rate for ages 15-24, total (%) (modeled ILO estimate) | SL.TLF.ACTI.1524.ZS | 29.1299991607666 | 28.7000007629395 | 28.1580009460449 | 27.2999992370605 | 26.7520008087158 | 25.9969997406006 | 25.0979995727539 | 24.1860008239746 | 23.3099994659424 | 21.94700050354 | 20.6310005187988 | 19.3640003204346 | 18.1189994812012 | 17.0289993286133 | 16.5049991607666 | 16.05299949646 | 15.673999786377 | 15.3210000991821 | 14.9440002441406 | 14.7270002365112 | 14.3870000839233 | 14.0299997329712 | 13.7049999237061 | 12.9630002975464 | 13.2749996185303 |
1297 | Djibouti | DJI | Labor force participation rate for ages 15-24, total (%) (national estimate) | SL.TLF.ACTI.1524.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.7799997329712 | .. | .. | .. | .. |
1298 | Djibouti | DJI | Labor force participation rate, female (% of female population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.FE.ZS | 14.7880001068115 | 14.8459997177124 | 14.9350004196167 | 15.0749998092651 | 15.1820001602173 | 15.335000038147 | 15.5109996795654 | 15.6719999313354 | 15.8070001602173 | 16.0249996185303 | 16.2229995727539 | 16.4220008850098 | 16.6319999694824 | 16.8500003814697 | 16.9669990539551 | 17.0809993743896 | 17.1909999847412 | 17.3059997558594 | 17.4330005645752 | 17.4950008392334 | 17.6030006408691 | 17.7320003509521 | 17.8479995727539 | 17.1420001983643 | 17.2180004119873 |
1299 | Djibouti | DJI | Labor force participation rate, female (% of female population ages 15+) (national estimate) | SL.TLF.CACT.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 18.2099990844727 | .. | .. | .. | .. |
1300 | Djibouti | DJI | Labor force participation rate, female (% of female population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.FE.ZS | 48.52 | 48.64 | 48.77 | 48.96 | 49.05 | 49.17 | 49.31 | 49.45 | 49.61 | 50.02 | 50.52 | 51.11 | 51.8 | 52.47 | 52.78 | 53.04 | 53.25 | 53.44 | 53.64 | 53.73 | 53.89 | 54.06 | 54.24 | .. | .. |
1301 | Djibouti | DJI | Labor force participation rate, male (% of male population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.MA.ZS | 56.0540008544922 | 55.8530006408691 | 55.5769996643066 | 55.1520004272461 | 54.9179992675781 | 54.5559997558594 | 54.064998626709 | 53.4749984741211 | 52.7980003356934 | 51.7159996032715 | 50.5730018615723 | 49.4389991760254 | 48.4020004272461 | 47.5229988098145 | 47.0460014343262 | 46.7039985656738 | 46.4490013122559 | 46.2029991149902 | 45.9179992675781 | 45.7200012207031 | 45.4420013427734 | 45.125 | 44.8300018310547 | 44.2360000610352 | 44.1469993591309 |
1302 | Djibouti | DJI | Labor force participation rate, male (% of male population ages 15+) (national estimate) | SL.TLF.CACT.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 47.0099983215332 | .. | .. | .. | .. |
1303 | Djibouti | DJI | Labor force participation rate, male (% of male population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.MA.ZS | 81.03 | 81.02 | 80.8 | 80.34 | 79.94 | 79.25 | 78.4 | 77.58 | 76.86 | 76.07 | 75.41 | 74.83 | 74.39 | 73.98 | 73.68 | 73.49 | 73.35 | 73.16 | 72.92 | 72.82 | 72.63 | 72.33 | 72.08 | .. | .. |
1304 | Djibouti | DJI | Labor force participation rate, total (% of total population ages 15+) (modeled ILO estimate) | SL.TLF.CACT.ZS | 35.4640007019043 | 35.3919982910156 | 35.2879981994629 | 35.1279983520508 | 35.0229988098145 | 34.8699989318848 | 34.685001373291 | 34.4959983825684 | 34.310001373291 | 34.0149993896484 | 33.726001739502 | 33.443000793457 | 33.173999786377 | 32.9300003051758 | 32.7999992370605 | 32.6949996948242 | 32.6059989929199 | 32.515998840332 | 32.4169998168945 | 32.359001159668 | 32.2700004577637 | 32.1660003662109 | 32.0730018615723 | 31.4400005340576 | 31.4260005950928 |
1305 | Djibouti | DJI | Labor force participation rate, total (% of total population ages 15+) (national estimate) | SL.TLF.CACT.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 32.2700004577637 | .. | .. | .. | .. |
1306 | Djibouti | DJI | Labor force participation rate, total (% of total population ages 15-64) (modeled ILO estimate) | SL.TLF.ACTI.ZS | 64.88 | 64.93 | 64.88 | 64.73 | 64.54 | 64.22 | 63.84 | 63.52 | 63.3 | 63.21 | 63.26 | 63.4 | 63.62 | 63.81 | 63.84 | 63.88 | 63.9 | 63.88 | 63.84 | 63.84 | 63.82 | 63.75 | 63.7 | .. | .. |
1307 | Djibouti | DJI | Labor force with advanced education (% of total working-age population with advanced education) | SL.TLF.ADVN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 70.7799987792969 | .. | .. | .. | .. |
1308 | Djibouti | DJI | Labor force with advanced education, female (% of female working-age population with advanced education) | SL.TLF.ADVN.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 57.2700004577637 | .. | .. | .. | .. |
1309 | Djibouti | DJI | Labor force with advanced education, male (% of male working-age population with advanced education) | SL.TLF.ADVN.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 77.4700012207031 | .. | .. | .. | .. |
1310 | Djibouti | DJI | Labor force with basic education (% of total working-age population with basic education) | SL.TLF.BASC.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 28.6299991607666 | .. | .. | .. | .. |
1311 | Djibouti | DJI | Labor force with basic education, female (% of female working-age population with basic education) | SL.TLF.BASC.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 15.8199996948242 | .. | .. | .. | .. |
1312 | Djibouti | DJI | Labor force with basic education, male (% of male working-age population with basic education) | SL.TLF.BASC.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 37.7099990844727 | .. | .. | .. | .. |
1313 | Djibouti | DJI | Labor force with intermediate education (% of total working-age population with intermediate education) | SL.TLF.INTM.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 42.439998626709 | .. | .. | .. | .. |
1314 | Djibouti | DJI | Labor force with intermediate education, female (% of female working-age population with intermediate education) | SL.TLF.INTM.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29.7600002288818 | .. | .. | .. | .. |
1315 | Djibouti | DJI | Labor force with intermediate education, male (% of male working-age population with intermediate education) | SL.TLF.INTM.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 50.5400009155273 | .. | .. | .. | .. |
1316 | Djibouti | DJI | Labor force, female (% of total labor force) | SL.TLF.TOTL.FE.ZS | 20.805939277535643 | 20.930199277306716 | 21.127765881513206 | 21.44196581598704 | 21.704415090628995 | 22.074257045588347 | 22.478739369684842 | 22.809496717992012 | 23.026654687032043 | 23.365234991985588 | 23.59135393608685 | 23.788977682268932 | 24.03029456702098 | 24.34411160955949 | 24.497498002607124 | 24.705967241503714 | 24.944913883722812 | 25.208018435463487 | 25.48967193195626 | 25.59236502002798 | 25.809355047394035 | 26.07778959337467 | 26.310408627639028 | 25.751071017761234 | 25.880302046552167 |
1317 | Djibouti | DJI | Labor force, total | SL.TLF.TOTL.IN | 135370 | 139755 | 144303 | 148783 | 152545 | 156268 | 159920 | 163467 | 166950 | 170942 | 174831 | 178692 | 182607 | 186579 | 190248 | 194026 | 197872 | 201785 | 205750 | 209457 | 213318 | 217227 | 221057 | 220818 | 224866 |
1318 | Djibouti | DJI | Manufacturing, value added (annual % growth) | NV.IND.MANF.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 52.76410184273456 | 4.3069106813996285 | 7.608687371225869 | 14.793265822408046 | 13.149713518645825 | 13.852006270239897 | 18.690837007389234 | .. |
1319 | Djibouti | DJI | Manufacturing, value added (constant 2015 US$) | NV.IND.MANF.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 41621176.21912395 | 63582216.02752652 | 66320645.281086646 | 71366775.84310418 | 81924252.70245668 | 92697057.23512119 | 105537459.41565804 | 125263293.93677825 | .. |
1320 | Djibouti | DJI | Multidimensional poverty headcount ratio (% of total population) | SI.POV.MDIM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1321 | Djibouti | DJI | Multidimensional poverty headcount ratio, children (% of population ages 0-17) | SI.POV.MDIM.17 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1322 | Djibouti | DJI | Multidimensional poverty headcount ratio, female (% of female population) | SI.POV.MDIM.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1323 | Djibouti | DJI | Multidimensional poverty headcount ratio, household (% of total households) | SI.POV.MDIM.HH | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1324 | Djibouti | DJI | Multidimensional poverty headcount ratio, male (% of male population) | SI.POV.MDIM.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1325 | Djibouti | DJI | Multidimensional poverty index (scale 0-1) | SI.POV.MDIM.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1326 | Djibouti | DJI | Multidimensional poverty index, children (population ages 0-17) (scale 0-1) | SI.POV.MDIM.17.XQ | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1327 | Djibouti | DJI | Multidimensional poverty intensity (average share of deprivations experienced by the poor) | SI.POV.MDIM.IT | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1328 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Australia (current US$) | DC.DAC.AUSL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 189999.99761581398 | 170000.00178813902 | 200000.00298023198 | 59999.9986588955 | 29999.999329447703 | 9999.99977648258 | 29999.999329447703 | 0 | 29999.999329447703 | 29999.999329447703 | .. |
1329 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Austria (current US$) | DC.DAC.AUTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0 | 9999.99977648258 | 9999.99977648258 | 0 | 59999.9986588955 | .. |
1330 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Belgium (current US$) | DC.DAC.BELL.CD | 90000.0035762787 | 79999.9982118607 | 29999.999329447703 | .. | .. | 39999.9991059303 | 29999.999329447703 | 9999.99977648258 | 19999.9995529652 | 19999.9995529652 | .. | .. | .. | .. | 119999.997317791 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1331 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Canada (current US$) | DC.DAC.CANL.CD | 100000.00149011599 | 79999.9982118607 | 239999.994635582 | 100000.00149011599 | 119999.997317791 | 100000.00149011599 | 360000.01430511504 | 379999.99523162795 | 1149999.97615814 | 1029999.97138977 | 750000 | 270000.010728836 | 389999.98569488496 | 150000.005960464 | 2859999.89509583 | 2519999.98092651 | 15359999.6566772 | 1559999.9427795399 | 779999.971389771 | 850000.023841858 | 1440000.0572204601 | 1240000.0095367401 | 1179999.94754791 | 1039999.96185303 | .. |
1332 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Czech Republic (current US$) | DC.DAC.CZEL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 19999.9995529652 | 29999.999329447703 | 19999.9995529652 | .. | .. | .. | .. | .. | .. |
1333 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Denmark (current US$) | DC.DAC.DNKL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | .. | 9999.99977648258 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 19999.9995529652 | .. |
1334 | Djibouti | DJI | Net bilateral aid flows from DAC donors, European Union institutions (current US$) | DC.DAC.CECL.CD | 3269999.98092651 | 8819999.69482422 | 5900000.09536743 | 1809999.9427795399 | 6570000.17166138 | 1850000.02384186 | 7650000.09536743 | 5599999.90463257 | 3190000.05722046 | 1629999.99523163 | 5650000.09536743 | 11500000 | 10270000.4577637 | 9979999.54223633 | 12340000.1525879 | 17610000.6103516 | 31329999.9237061 | 31639999.3896484 | 9479999.54223633 | 13170000.076293899 | 14689999.5803833 | 32450000.7629395 | 37630001.0681152 | 31409999.8474121 | .. |
1335 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Finland (current US$) | DC.DAC.FINL.CD | .. | .. | .. | .. | .. | .. | .. | 29999.999329447703 | 59999.9986588955 | 9999.99977648258 | .. | .. | .. | .. | .. | .. | 9999.99977648258 | 9999.99977648258 | 9999.99977648258 | .. | .. | 9999.99977648258 | 9999.99977648258 | 9999.99977648258 | .. |
1336 | Djibouti | DJI | Net bilateral aid flows from DAC donors, France (current US$) | DC.DAC.FRAL.CD | 46130001.0681152 | 39779998.779296905 | 41439998.626709 | 20620000.8392334 | 21870000.8392334 | 26299999.237060502 | 22809999.4659424 | 24510000.2288818 | 35119998.9318848 | 71610000.6103516 | 56700000.762939505 | 51229999.5422363 | 41970001.220703095 | 46220001.220703095 | 43959999.0844727 | 40439998.626709 | 42400001.5258789 | 40799999.237060495 | 56290000.9155273 | 49060001.373291 | 41290000.9155273 | 44529998.779296905 | 36360000.6103516 | 37319999.6948242 | .. |
1337 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Germany (current US$) | DC.DAC.DEUL.CD | 1639999.98569489 | 1899999.97615814 | 449999.988079071 | 300000.011920929 | 90000.0035762787 | 29999.999329447703 | 579999.983310699 | 289999.99165535 | 389999.98569488496 | 140000.000596046 | 280000.001192093 | 200000.00298023198 | 1120000.00476837 | 230000.004172325 | 6800000.19073486 | 2660000.08583069 | 1820000.05245209 | 1100000.02384186 | 1429999.94754791 | 1139999.98569489 | 540000.021457672 | 360000.01430511504 | 889999.985694885 | 430000.00715255697 | .. |
1338 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Greece (current US$) | DC.DAC.GRCL.CD | .. | 19999.9995529652 | .. | .. | .. | .. | .. | .. | 59999.9986588955 | 79999.9982118607 | .. | 90000.0035762787 | 529999.971389771 | 9999.99977648258 | 19999.9995529652 | 19999.9995529652 | .. | 9999.99977648258 | 0 | .. | .. | .. | .. | .. | .. |
1339 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Hungary (current US$) | DC.DAC.HUNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1340 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Iceland (current US$) | DC.DAC.ISLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 59999.9986588955 | .. | .. | .. |
1341 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Ireland (current US$) | DC.DAC.IRLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | 379999.99523162795 | .. | .. | .. | .. | .. | .. | 59999.9986588955 | 180000.00715255702 | 109999.999403954 | 39999.9991059303 | .. | .. | .. | .. | .. |
1342 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Italy (current US$) | DC.DAC.ITAL.CD | 1710000.03814697 | 1629999.99523163 | 1870000.00476837 | 5119999.88555908 | 1049999.95231628 | 1340000.0333786 | 1039999.96185303 | 860000.014305115 | 1240000.0095367401 | 800000.011920929 | 850000.023841858 | 250000 | 12020000.4577637 | 439999.997615814 | 469999.998807907 | 4659999.84741211 | 170000.00178813902 | 209999.993443489 | 4260000.228881841 | 870000.004768372 | 150000.005960464 | 629999.995231628 | 920000.016689301 | 280000.001192093 | .. |
1343 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Japan (current US$) | DC.DAC.JPNL.CD | 11430000.3051758 | 16950000.762939498 | 9979999.54223633 | 13920000.076293899 | 2990000.00953674 | 5440000.05722046 | 8060000.419616699 | 7159999.84741211 | 6380000.11444092 | 4590000.15258789 | 3670000.07629395 | 3740000.00953674 | 28819999.6948242 | 37979999.5422363 | 16569999.6948242 | 24840000.1525879 | 6230000.01907349 | 26459999.084472697 | 17840000.1525879 | 9130000.11444092 | 16920000.0762939 | 9380000.11444092 | 44330001.8310547 | 13920000.076293899 | .. |
1344 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Korea, Rep. (current US$) | DC.DAC.KORL.CD | 39999.9991059303 | .. | .. | 50000.0007450581 | .. | 39999.9991059303 | 39999.9991059303 | 90000.0035762787 | 100000.00149011599 | 529999.971389771 | 569999.992847443 | 250000 | .. | 270000.010728836 | 389999.98569488496 | 1159999.9666214 | 310000.002384186 | .. | 79999.9982118607 | .. | 189999.99761581398 | .. | 140000.000596046 | 300000.011920929 | .. |
1345 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Luxembourg (current US$) | DC.DAC.LUXL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 310000.002384186 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 230000.004172325 | .. | .. | .. | .. |
1346 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Netherlands (current US$) | DC.DAC.NLDL.CD | .. | .. | .. | 209999.993443489 | 889999.985694885 | 529999.971389771 | .. | .. | 759999.990463257 | .. | 1429999.94754791 | .. | .. | .. | .. | .. | .. | 1330000.04291534 | .. | .. | .. | .. | .. | .. | .. |
1347 | Djibouti | DJI | Net bilateral aid flows from DAC donors, New Zealand (current US$) | DC.DAC.NZLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | 460000.00834465 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1348 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Norway (current US$) | DC.DAC.NORL.CD | .. | 50000.0007450581 | .. | 280000.001192093 | 9999.99977648258 | 79999.9982118607 | .. | 29999.999329447703 | 109999.999403954 | 469999.998807907 | .. | .. | 800000.011920929 | 330000.013113022 | .. | .. | .. | 479999.989271164 | 250000 | .. | .. | .. | .. | 479999.989271164 | .. |
1349 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Poland (current US$) | DC.DAC.POLL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9999.99977648258 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1350 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Portugal (current US$) | DC.DAC.PRTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1351 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Slovak Republic (current US$) | DC.DAC.SVKL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1352 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Slovenia (current US$) | DC.DAC.SVNL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1353 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Spain (current US$) | DC.DAC.ESPL.CD | 1059999.9427795399 | 1429999.94754791 | .. | .. | .. | .. | .. | .. | .. | .. | 1490000.0095367401 | 560000.002384186 | 2670000.07629395 | -300000.011920929 | 750000 | 9999.99977648258 | .. | .. | .. | .. | .. | .. | 159999.99642372102 | 0 | .. |
1354 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Sweden (current US$) | DC.DAC.SWEL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 39999.9991059303 | 129999.995231628 | 200000.00298023198 | 70000.0002980232 | .. | 70000.0002980232 | 70000.0002980232 | 2190000.05722046 | 800000.011920929 | 1460000.03814697 | 930000.007152557 | 1370000.00476837 | 600000.023841858 | 720000.028610229 | .. |
1355 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Switzerland (current US$) | DC.DAC.CHEL.CD | .. | 389999.98569488496 | .. | 419999.986886978 | 129999.995231628 | 109999.999403954 | .. | .. | .. | 140000.000596046 | 29999.999329447703 | 860000.014305115 | 460000.00834465 | 159999.99642372102 | 699999.988079071 | 340000.00357627904 | 270000.010728836 | 9999.99977648258 | 140000.000596046 | 219999.998807907 | .. | .. | .. | .. | .. |
1356 | Djibouti | DJI | Net bilateral aid flows from DAC donors, Total (current US$) | DC.DAC.TOTL.CD | 65470001.32501124 | 71149999.1379679 | 61299998.236820124 | 43970000.72523948 | 34660000.951960675 | 38749999.20465048 | 44689999.82438984 | 45110000.07949766 | 56919999.245554246 | 91630000.51490963 | 81680000.9459258 | 77629999.54260883 | 107950001.70171262 | 107610000.28252593 | 100499999.4039536 | 103329999.54186386 | 107580000.73768198 | 114219997.38365406 | 97200000.86165962 | 82700001.61416824 | 88080000.32231198 | 99729999.56458814 | 147910002.61157754 | 107610000.48369162 | .. |
1357 | Djibouti | DJI | Net bilateral aid flows from DAC donors, United Kingdom (current US$) | DC.DAC.GBRL.CD | .. | .. | .. | .. | .. | 19999.9995529652 | .. | .. | .. | .. | .. | .. | 2349999.90463257 | 9999.99977648258 | 19999.9995529652 | 109999.999403954 | 100000.00149011599 | .. | 29999.999329447703 | .. | 50000.0007450581 | 70000.0002980232 | 779999.971389771 | 1470000.02861023 | .. |
1358 | Djibouti | DJI | Net bilateral aid flows from DAC donors, United States (current US$) | DC.DAC.USAL.CD | .. | 19999.9995529652 | 1389999.98569489 | 1139999.98569489 | 939999.997615814 | 2869999.8855590797 | 4119999.88555908 | 6150000.09536743 | 7570000.17166138 | 10199999.8092651 | 10210000.038146999 | 8539999.96185303 | 6349999.90463257 | 12039999.961853001 | 15310000.4196167 | 8720000.26702881 | 9229999.54223633 | 8149999.61853027 | 5650000.09536743 | 6750000 | 11609999.6566772 | 9619999.88555908 | 24879999.1607666 | 20120000.8392334 | .. |
1359 | Djibouti | DJI | Net migration | SM.POP.NETM | 9988 | .. | .. | .. | .. | -8997 | .. | .. | .. | .. | -12221 | .. | .. | .. | .. | 6002 | .. | .. | .. | .. | 4501 | .. | .. | .. | .. |
1360 | Djibouti | DJI | Net ODA provided to the least developed countries (% of GNI) | DC.ODA.TLDC.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1361 | Djibouti | DJI | Net ODA provided, to the least developed countries (current US$) | DC.ODA.TLDC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1362 | Djibouti | DJI | Net ODA provided, total (% of GNI) | DC.ODA.TOTL.GN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1363 | Djibouti | DJI | Net ODA provided, total (constant 2020 US$) | DC.ODA.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1364 | Djibouti | DJI | Net ODA provided, total (current US$) | DC.ODA.TOTL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1365 | Djibouti | DJI | Net ODA received (% of central government expense) | DT.ODA.ODAT.XP.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1366 | Djibouti | DJI | Net ODA received (% of GNI) | DT.ODA.ODAT.GN.ZS | 16.635487662762262 | 15.428950362032712 | 13.701884119696622 | 12.74029873619471 | 10.156697548510571 | 12.219340899391382 | 12.32737144597061 | 9.342119363139814 | 10.168294000480682 | 14.569737453371252 | 12.923766115854777 | 13.64779785707494 | 15.486686296211772 | 11.521240192403843 | 11.251004308526188 | 10.744490085071563 | 7.40700386098094 | 7.581374857324501 | 7.23245565206421 | 7.3406806202151955 | 5.410264748135436 | 6.466659146664753 | 8.76391124704871 | 8.309471870622927 | .. |
1367 | Djibouti | DJI | Net ODA received (% of gross capital formation) | DT.ODA.ODAT.GI.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 12.846163748844905 | 262.75703601739417 | -181.24769228038235 | 32.436657071590716 | 23.86283368125028 | 220.70892989934953 | 372.45376689324246 | 879.7372349202092 | .. |
1368 | Djibouti | DJI | Net ODA received (% of imports of goods, services and primary income) | DT.ODA.ODAT.MP.ZS | 32.629105316457824 | 28.336543693708478 | 27.986533299486 | 25.159842949649192 | 21.913992633177763 | 27.670299894562778 | 25.11888234183281 | 18.415927989911374 | 19.923770019019265 | 26.41433529804802 | 19.02284275862425 | 19.653425884771117 | 27.937429501490087 | 25.96837403777802 | 19.990728352703172 | 19.989521748000097 | 3.75116743623378 | 5.21688159984818 | 5.689930015936577 | 6.245685926154012 | 3.18752101806308 | 4.0813191964515525 | 5.316620250449112 | 7.140055081708219 | .. |
1369 | Djibouti | DJI | Net ODA received per capita (current US$) | DT.ODA.ODAT.PC.ZS | 129.6042440673774 | 119.00686053938644 | 107.36128611514859 | 100.6721200146737 | 81.0347365155322 | 99.20382366368844 | 104.33903753787062 | 83.37232400645244 | 94.69541980183199 | 145.2135377248343 | 139.88349229373796 | 172.497225276831 | 200.32132810400205 | 157.14227759219537 | 164.46616307275755 | 170.95248171036454 | 168.96940549940223 | 184.83220961932196 | 189.70500962764473 | 199.49049054480327 | 151.0539144268107 | 186.8867539039808 | 269.60928942663656 | 259.2505021735158 | .. |
1370 | Djibouti | DJI | Net official aid received (constant 2020 US$) | DT.ODA.OATL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1371 | Djibouti | DJI | Net official aid received (current US$) | DT.ODA.OATL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1372 | Djibouti | DJI | Net official development assistance and official aid received (constant 2020 US$) | DT.ODA.ALLD.KD | 112809997.558594 | 106519996.64306599 | 101819999.69482401 | 101510002.13623 | 91839996.3378906 | 106809997.558594 | 98089996.3378906 | 72849998.4741211 | 82769996.6430664 | 125120002.746582 | 112269996.64306599 | 132880004.882813 | 156729995.727539 | 123330001.831055 | 129679992.675781 | 138699996.94824198 | 139199996.94824198 | 156130004.882813 | 184559997.55859402 | 196660003.66210902 | 148139999.38964802 | 179210006.71386698 | 276600006.10351604 | .. | .. |
1373 | Djibouti | DJI | Net official development assistance and official aid received (current US$) | DT.ODA.ALLD.CD | 85650001.5258789 | 80980003.3569336 | 75150001.5258789 | 72239997.8637695 | 59400001.5258789 | 74099998.4741211 | 79260002.1362305 | 64330001.8310547 | 74169998.1689453 | 115379997.253418 | 112669998.168945 | 140820007.32421902 | 165830001.831055 | 132029998.779297 | 140399993.89648402 | 148410003.66210902 | 149250000 | 166110000.61035198 | 173389999.38964802 | 185350006.10351598 | 142610000.61035198 | 179210006.71386698 | 262480010.986328 | 256140014.648438 | .. |
1374 | Djibouti | DJI | Net official development assistance received (constant 2020 US$) | DT.ODA.ODAT.KD | 114029998.77929701 | 107949996.94824201 | 102879997.253418 | 102790000.915527 | 92699996.9482422 | 107959999.084473 | 99300003.0517578 | 73819999.6948242 | 83800003.0517578 | 126300003.05175799 | 113330001.831055 | 134130004.882813 | 158770004.272461 | 125720001.22070299 | 130649993.896484 | 140479995.727539 | 140270004.272461 | 158259994.506836 | 186479995.727539 | 198529998.779297 | 149770004.272461 | 179050003.05175802 | 269769989.013672 | 256140014.648438 | .. |
1375 | Djibouti | DJI | Net official development assistance received (current US$) | DT.ODA.ODAT.CD | 85650001.5258789 | 80980003.3569336 | 75150001.5258789 | 72239997.8637695 | 59400001.5258789 | 74099998.4741211 | 79260002.1362305 | 64330001.8310547 | 74169998.1689453 | 115379997.253418 | 112669998.168945 | 140820007.32421902 | 165830001.831055 | 132029998.779297 | 140399993.89648402 | 148410003.66210902 | 149250000 | 166110000.61035198 | 173389999.38964802 | 185350006.10351598 | 142610000.61035198 | 179210006.71386698 | 262480010.986328 | 256140014.648438 | .. |
1376 | Djibouti | DJI | Net official flows from UN agencies, FAO (current US$) | DT.NFL.FAOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 565468.907356262 | .. | .. | .. | .. | 333539.992570877 | 455219.924449921 | .. | .. |
1377 | Djibouti | DJI | Net official flows from UN agencies, IAEA (current US$) | DT.NFL.IAEA.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 66453.9411664009 | 52553.2625615597 | 30208.0009132624 | 21022.0906883478 | 456906.43787384 | .. |
1378 | Djibouti | DJI | Net official flows from UN agencies, IFAD (current US$) | DT.NFL.IFAD.CD | .. | -59999.9986588955 | -59999.9986588955 | -59999.9986588955 | -439999.997615814 | -70000.0002980232 | -90000.0035762787 | -39999.9991059303 | -70000.0002980232 | 270000.010728836 | 3349999.90463257 | 810000.002384186 | 759999.990463257 | 720000.028610229 | 2220000.02861023 | 1370000.00476837 | 1570000.05245209 | 699999.988079071 | 1024587.9888534499 | 862338.185310364 | 1646230.10158539 | 2343462.94403076 | 5968274.11651611 | 2227121.35314941 | .. |
1379 | Djibouti | DJI | Net official flows from UN agencies, ILO (current US$) | DT.NFL.ILOG.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 74182.2198033333 | 94565.8683776855 | 65600.0003218651 | 121009.99802351 | 106229.998171329 | 83559.9973797798 | 64274.400472641006 | 512889.98126983596 | 209739.923477173 | .. |
1380 | Djibouti | DJI | Net official flows from UN agencies, UNAIDS (current US$) | DT.NFL.UNAI.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0 | .. | 90000.0035762787 | 289999.99165535 | 460000.00834465 | 348254.79984283395 | 328277.558088303 | 418246.001005173 | 425772.994756699 | 384002.506732941 | 319200.00910759 | 23496.10067904 | 203547.760844231 | .. | .. |
1381 | Djibouti | DJI | Net official flows from UN agencies, UNDP (current US$) | DT.NFL.UNDP.CD | 860000.014305115 | 680000.007152557 | 1179999.94754791 | 589999.973773956 | 419999.986886978 | 589999.973773956 | 250000 | 750000 | 670000.016689301 | 740000.009536743 | 670000.016689301 | 990000.009536743 | 1220000.02861023 | 1149999.97615814 | 1080000.04291534 | 779020.5478668209 | 896438.002586365 | 1073540.32993317 | 767215.430736542 | 833440.899848938 | 599463.522434235 | 522726.17816925 | 837339.997291565 | 741629.242897034 | .. |
1382 | Djibouti | DJI | Net official flows from UN agencies, UNECE (current US$) | DT.NFL.UNEC.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1383 | Djibouti | DJI | Net official flows from UN agencies, UNEP (current US$) | DT.NFL.UNEP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1384 | Djibouti | DJI | Net official flows from UN agencies, UNFPA (current US$) | DT.NFL.UNFP.CD | 360000.01430511504 | 389999.98569488496 | 439999.997615814 | 280000.001192093 | 540000.021457672 | 509999.99046325695 | 349999.99403953605 | 300000.011920929 | 439999.997615814 | 660000.026226044 | 750000 | 670000.016689301 | 970000.028610229 | 740000.009536743 | 790000.021457672 | 720888.97228241 | 696478.009223938 | 808049.440383911 | 1033236.50360107 | 729075.312614441 | 546247.601509094 | 514919.996261597 | 855044.603347778 | 792699.992656708 | .. |
1385 | Djibouti | DJI | Net official flows from UN agencies, UNHCR (current US$) | DT.NFL.UNCR.CD | 2700000.04768372 | 2259999.99046326 | 2140000.10490417 | 2250000 | 2130000.1144409203 | 2990000.00953674 | 2799999.95231628 | 3410000.08583069 | 1039999.96185303 | 439999.997615814 | 870000.004768372 | 1120000.00476837 | 1759999.9904632599 | 1059999.9427795399 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1386 | Djibouti | DJI | Net official flows from UN agencies, UNICEF (current US$) | DT.NFL.UNCF.CD | 1080000.04291534 | 1090000.0333786 | 519999.980926514 | 670000.016689301 | 779999.971389771 | 689999.997615814 | 560000.002384186 | 860000.014305115 | 790000.021457672 | 839999.973773956 | 2829999.92370605 | 1129999.99523163 | 2019999.9809265102 | 910000.026226044 | 930000.007152557 | 798043.727874756 | 933179.259300232 | 1048220.9920883201 | 1250639.0810012799 | 1086004.73403931 | 1253000.02098083 | 1101587.41474152 | 1371999.97901917 | 1215999.96089935 | .. |
1387 | Djibouti | DJI | Net official flows from UN agencies, UNIDIR (current US$) | DT.NFL.UNID.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1388 | Djibouti | DJI | Net official flows from UN agencies, UNPBF (current US$) | DT.NFL.UNPB.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1389 | Djibouti | DJI | Net official flows from UN agencies, UNRWA (current US$) | DT.NFL.UNRW.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1390 | Djibouti | DJI | Net official flows from UN agencies, UNTA (current US$) | DT.NFL.UNTA.CD | 1250000 | 670000.016689301 | 1370000.00476837 | 1220000.02861023 | 839999.973773956 | 1230000.01907349 | 1590000.0333786 | 1360000.01430511 | 1840000.0333786 | 990000.009536743 | 1379999.99523163 | 90000.0035762787 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1391 | Djibouti | DJI | Net official flows from UN agencies, UNWTO (current US$) | DT.NFL.UNWT.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1392 | Djibouti | DJI | Net official flows from UN agencies, WFP (current US$) | DT.NFL.WFPG.CD | 1240000.0095367401 | 230000.004172325 | 1889999.98569489 | 879999.995231628 | 1289999.96185303 | 2589999.91416931 | 839999.973773956 | 1509999.9904632599 | 1799999.95231628 | 1090000.0333786 | 2240000.00953674 | 1990000.0095367401 | 3390000.10490417 | 1139999.98569489 | 1649999.97615814 | 605929.493904114 | 692461.013793945 | 3079449.89204407 | 786575.973033905 | 977348.029613495 | 1442080.0209045399 | 1514081.0012817401 | 1642889.97650146 | 1058404.20722961 | .. |
1393 | Djibouti | DJI | Net official flows from UN agencies, WHO (current US$) | DT.NFL.WHOL.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 540000.021457672 | 520730.257034302 | 654904.067516327 | 425490.915775299 | 1254032.49263763 | 703453.302383423 | 842999.994754791 | 1054545.2833175699 | 752847.373485565 | 501041.71037673997 | .. |
1394 | Djibouti | DJI | Number of surgical procedures (per 100,000 population) | SH.SGR.PROC.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1395 | Djibouti | DJI | Nurses and midwives (per 1,000 people) | SH.MED.NUMW.P3 | .. | .. | 0.7043 | .. | .. | 0.7364 | .. | 0.3836 | 0.5746 | .. | .. | .. | .. | .. | .. | .. | .. | 0.7288 | .. | .. | .. | .. | .. | .. | .. |
1396 | Djibouti | DJI | Out-of-pocket expenditure (% of current health expenditure) | SH.XPD.OOPC.CH.ZS | .. | .. | .. | 51.33246613 | 54.73034286 | 42.81143951 | 36.94394684 | 41.30123901 | 41.67882919 | 37.76251602 | 35.84453583 | 31.6133194 | 30.16868782 | 29.03930855 | 24.22880554 | 22.94796562 | 24.05808449 | 22.65952682 | 20.54255676 | 23.17866516 | 26.1577282 | 29.10498428 | 24.15331268 | .. | .. |
1397 | Djibouti | DJI | Out-of-pocket expenditure per capita (current US$) | SH.XPD.OOPC.PC.CD | .. | .. | .. | 16.40482232 | 16.98953325 | 17.20784459 | 17.03608829 | 16.63946468 | 17.07149276 | 17.87298332 | 18.082828 | 17.05932375 | 16.68954296 | 16.32050183 | 16.66417907 | 16.5730992 | 16.24760584 | 16.56936268 | 16.9044445 | 17.817057 | 18.89497479 | 20.68965615 | 14.92902559 | .. | .. |
1398 | Djibouti | DJI | Out-of-pocket expenditure per capita, PPP (current international $) | SH.XPD.OOPC.PP.CD | .. | .. | .. | 36.35671475 | 37.7038126 | 38.79235401 | 38.34630084 | 37.23707344 | 38.17793915 | 39.78960722 | 39.37921246 | 34.537045 | 33.52490164 | 31.90478371 | 31.65022071 | 29.97239898 | 28.83158245 | 28.83843133 | 29.08228202 | 29.83667897 | 31.67251392 | 35.38504052 | 25.15369358 | .. | .. |
1399 | Djibouti | DJI | Part time employment, female (% of total female employment) | SL.TLF.PART.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1400 | Djibouti | DJI | Part time employment, male (% of total male employment) | SL.TLF.PART.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1401 | Djibouti | DJI | Part time employment, total (% of total employment) | SL.TLF.PART.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1402 | Djibouti | DJI | Physicians (per 1,000 people) | SH.MED.PHYS.ZS | .. | .. | 0.1329 | .. | .. | .. | .. | 0.1672 | 0.1788 | 0.2328 | .. | .. | .. | .. | .. | .. | .. | 0.2237 | .. | .. | .. | .. | .. | .. | .. |
1403 | Djibouti | DJI | Poverty gap at $1.90 a day (2011 PPP) (%) | SI.POV.GAPS | .. | .. | .. | .. | .. | 5.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.8 | 7.4 | .. | .. | .. | 5.6 | .. | .. | .. | .. |
1404 | Djibouti | DJI | Poverty gap at $3.20 a day (2011 PPP) (%) | SI.POV.LMIC.GP | .. | .. | .. | .. | .. | 17.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 16.1 | 17.9 | .. | .. | .. | 14.7 | .. | .. | .. | .. |
1405 | Djibouti | DJI | Poverty gap at $5.50 a day (2011 PPP) (%) | SI.POV.UMIC.GP | .. | .. | .. | .. | .. | 36.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 32.3 | 36 | .. | .. | .. | 32.2 | .. | .. | .. | .. |
1406 | Djibouti | DJI | Poverty headcount ratio at $1.90 a day (2011 PPP) (% of population) | SI.POV.DDAY | .. | .. | .. | .. | .. | 20.2 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 18.2 | 22.3 | .. | .. | .. | 17 | .. | .. | .. | .. |
1407 | Djibouti | DJI | Poverty headcount ratio at $3.20 a day (2011 PPP) (% of population) | SI.POV.LMIC | .. | .. | .. | .. | .. | 47.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 38 | 44.2 | .. | .. | .. | 39.8 | .. | .. | .. | .. |
1408 | Djibouti | DJI | Poverty headcount ratio at $5.50 a day (2011 PPP) (% of population) | SI.POV.UMIC | .. | .. | .. | .. | .. | 76.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 68.1 | 74.5 | .. | .. | .. | 70.2 | .. | .. | .. | .. |
1409 | Djibouti | DJI | Poverty headcount ratio at national poverty lines (% of population) | SI.POV.NAHC | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 21.1 | .. | .. | .. | .. |
1410 | Djibouti | DJI | PPP conversion factor, GDP (LCU per international $) | PA.NUS.PPP | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 93.5718231201172 | 98.2695922851563 | 100.152282714844 | 102.110855102539 | 103.302284240723 | 106.126457214355 | 106.022705078125 | 104.228207970402 | 102.857201066307 | 103.423347194543 | 100.881356683089 |
1411 | Djibouti | DJI | PPP conversion factor, private consumption (LCU per international $) | PA.NUS.PRVT.PP | .. | .. | .. | 87.6610583592553 | 86.7407501775386 | 85.9309343656756 | 85.6888393894415 | 86.0602333546755 | 85.8206957379447 | 86.0347470121696 | 87.8024947636095 | 94.6680602852009 | 96.5976691341348 | 98.7931033317955 | 100.624099731445 | 100.602394104004 | 102.84056854248 | 104.175155639648 | 103.542343139648 | 105.117561340332 | 104.736534118652 | 102.390539444221 | 103.906143637053 | 104.464323977986 | .. |
1412 | Djibouti | DJI | Price level ratio of PPP conversion factor (GDP) to market exchange rate | PA.NUS.PPPC.RF | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.5265096590730257 | 0.5529430527914895 | 0.5635365697629656 | 0.574557059112536 | 0.581260989082455 | 0.5971520372626477 | 0.5965682450477152 | 0.5864709740008327 | 0.5787565963859476 | 0.5819421857548798 | 0.5676389210227772 |
1413 | Djibouti | DJI | Proportion of people living below 50 percent of median income (%) | SI.DST.50MD | .. | .. | .. | .. | .. | 15.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. | 18.9 | 18.9 | .. | .. | .. | 17.1 | .. | .. | .. | .. |
1414 | Djibouti | DJI | Proportion of seats held by women in national parliaments (%) | SG.GEN.PARL.ZS | .. | 0 | 0 | 0 | 0 | 0 | 10.7692307692308 | 10.7692307692308 | 10.7692307692308 | 10.7692307692308 | 13.8461538461538 | 13.8461538461538 | 13.8461538461538 | 13.8461538461538 | 13.8461538461538 | 13.8461538461538 | 12.7272727272727 | 12.7272727272727 | 12.7272727272727 | 12.7272727272727 | 10.7692307692308 | 26.1538461538462 | 26.1538461538462 | 26.1538461538462 | 26.1538461538462 |
1415 | Djibouti | DJI | Proportion of time spent on unpaid domestic and care work, female (% of 24 hour day) | SG.TIM.UWRK.FE | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1416 | Djibouti | DJI | Proportion of time spent on unpaid domestic and care work, male (% of 24 hour day) | SG.TIM.UWRK.MA | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1417 | Djibouti | DJI | Proportion of women subjected to physical and/or sexual violence in the last 12 months (% of ever-partnered women ages 15-49) | SG.VAW.1549.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1418 | Djibouti | DJI | Ratio of female to male labor force participation rate (%) (modeled ILO estimate) | SL.TLF.CACT.FM.ZS | 26.381703145862744 | 26.58048725648805 | 26.872628083247275 | 27.33355035625829 | 27.644852985713715 | 28.108732507463575 | 28.689540504127027 | 29.30715358303333 | 29.938634152269554 | 30.986541382672172 | 32.078379719596754 | 33.21669361982831 | 34.36221607097056 | 35.45651748304617 | 36.06469952104252 | 36.572884333170734 | 37.01048353908361 | 37.456442411429094 | 37.965505559133405 | 38.265530122757845 | 38.737291758098344 | 39.29529163645895 | 39.81262289485388 | 38.75124372617868 | 39.00151915630957 |
1419 | Djibouti | DJI | Ratio of female to male labor force participation rate (%) (national estimate) | SL.TLF.CACT.FM.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 38.736438491067766 | .. | .. | .. | .. |
1420 | Djibouti | DJI | Refugee population by country or territory of asylum | SM.POP.REFG | 23589 | 23577 | 23266 | 23238 | 23172 | 21702 | 27034 | 18033 | 10455 | 9257 | 6653 | 9228 | 12106 | 15102 | 20336 | 19136 | 20010 | 20525 | 19369 | 17683 | 17553 | 18293 | 19639 | 21193 | 23232 |
1421 | Djibouti | DJI | Refugee population by country or territory of origin | SM.POP.REFG.OR | 8143 | 3222 | 1879 | 1911 | 451 | 470 | 520 | 492 | 498 | 479 | 645 | 638 | 613 | 556 | 595 | 626 | 747 | 870 | 1059 | 1437 | 1761 | 2124 | 2351 | 2419 | 2607 |
1422 | Djibouti | DJI | Self-employed, female (% of female employment) (modeled ILO estimate) | SL.EMP.SELF.FE.ZS | 48.7999992370605 | 49.2799987792969 | 49.3400001525879 | 49.439998626709 | 49.6300010681152 | 49.4900016784668 | 49.2599983215332 | 49.0299987792969 | 48.9099998474121 | 48.5400009155273 | 48.1500015258789 | 47.6599998474121 | 47.1599998474121 | 46.9300003051758 | 46.4300003051758 | 45.7999992370605 | 45.6599998474121 | 45.1199989318848 | 44.4700012207031 | 43.7200012207031 | 43.1500015258789 | 42.5099983215332 | 41.8899993896484 | .. | .. |
1423 | Djibouti | DJI | Self-employed, male (% of male employment) (modeled ILO estimate) | SL.EMP.SELF.MA.ZS | 35.2200012207031 | 35.9700012207031 | 36.5099983215332 | 37.1300010681152 | 37.5400009155273 | 37.7400016784668 | 37.810001373291 | 37.8300018310547 | 37.7299995422363 | 37.439998626709 | 37.060001373291 | 36.5900001525879 | 36.4599990844727 | 36.0200004577637 | 35.2799987792969 | 34.7900009155273 | 34.0900001525879 | 33.3800010681152 | 32.5999984741211 | 31.9099998474121 | 31.3199996948242 | 30.3999996185303 | 29.5599994659424 | .. | .. |
1424 | Djibouti | DJI | Self-employed, total (% of total employment) (modeled ILO estimate) | SL.EMP.SELF.ZS | 40.2299995422363 | 40.8899993896484 | 41.2599983215332 | 41.7299995422363 | 42.0900001525879 | 42.2000007629395 | 42.2099990844727 | 42.1599998474121 | 42.060001373291 | 41.75 | 41.3600006103516 | 40.8699989318848 | 40.5900001525879 | 40.2400016784668 | 39.5900001525879 | 39.060001373291 | 38.6100006103516 | 37.9799995422363 | 37.2700004577637 | 36.560001373291 | 36 | 35.2000007629395 | 34.4500007629395 | .. | .. |
1425 | Djibouti | DJI | Services, value added (annual % growth) | NV.SRV.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.14990727349192 | 6.783790782067726 | 7.987871695270272 | 3.7561312053076676 | 2.3730657380260993 | 4.511327159320857 | 3.1040161548427676 | .. |
1426 | Djibouti | DJI | Services, value added (constant 2015 US$) | NV.SRV.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1701171845.2408128 | 1822804054.7382822 | 1946459268.1787746 | 2101939937.1215916 | 2180891559.01664 | 2232645549.387167 | 2333367494.4280386 | 2405795598.4069347 | .. |
1427 | Djibouti | DJI | Services, value added per worker (constant 2015 US$) | NV.SRV.EMPL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9209.87934454154 | 9512.591072061434 | 9800.634997237685 | 10171.410528864633 | 10185.257955956016 | 10113.483428664662 | 10439.528788311374 | .. | .. |
1428 | Djibouti | DJI | Share of youth not in education, employment or training, female (% of female youth population) | SL.UEM.NEET.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 24.0499992370605 | .. | .. | .. | .. |
1429 | Djibouti | DJI | Share of youth not in education, employment or training, male (% of male youth population) | SL.UEM.NEET.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.5100002288818 | .. | .. | .. | .. |
1430 | Djibouti | DJI | Share of youth not in education, employment or training, total (% of youth population) | SL.UEM.NEET.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 19.3199996948242 | .. | .. | .. | .. |
1431 | Djibouti | DJI | Specialist surgical workforce (per 100,000 population) | SH.MED.SAOP.P5 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.42 | .. | .. | .. | .. | .. | .. | .. | .. |
1432 | Djibouti | DJI | Survey mean consumption or income per capita, bottom 40% of population (2011 PPP $ per day) | SI.SPR.PC40 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1433 | Djibouti | DJI | Survey mean consumption or income per capita, total population (2011 PPP $ per day) | SI.SPR.PCAP | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1434 | Djibouti | DJI | Unemployment with advanced education (% of total labor force with advanced education) | SL.UEM.ADVN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 16.2900009155273 | .. | .. | .. | .. |
1435 | Djibouti | DJI | Unemployment with advanced education, female (% of female labor force with advanced education) | SL.UEM.ADVN.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 22.1299991607666 | .. | .. | .. | .. |
1436 | Djibouti | DJI | Unemployment with advanced education, male (% of male labor force with advanced education) | SL.UEM.ADVN.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.1499996185303 | .. | .. | .. | .. |
1437 | Djibouti | DJI | Unemployment with basic education (% of total labor force with basic education) | SL.UEM.BASC.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34.8300018310547 | .. | .. | .. | .. |
1438 | Djibouti | DJI | Unemployment with basic education, female (% of female labor force with basic education) | SL.UEM.BASC.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 53.3199996948242 | .. | .. | .. | .. |
1439 | Djibouti | DJI | Unemployment with basic education, male (% of male labor force with basic education) | SL.UEM.BASC.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 29.3299999237061 | .. | .. | .. | .. |
1440 | Djibouti | DJI | Unemployment with intermediate education (% of total labor force with intermediate education) | SL.UEM.INTM.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 27.4699993133545 | .. | .. | .. | .. |
1441 | Djibouti | DJI | Unemployment with intermediate education, female (% of female labor force with intermediate education) | SL.UEM.INTM.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 31.2000007629395 | .. | .. | .. | .. |
1442 | Djibouti | DJI | Unemployment with intermediate education, male (% of male labor force with intermediate education) | SL.UEM.INTM.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 26.0699996948242 | .. | .. | .. | .. |
1443 | Djibouti | DJI | Unemployment, female (% of female labor force) (modeled ILO estimate) | SL.UEM.TOTL.FE.ZS | 37.6069984436035 | 37.5709991455078 | 37.5009994506836 | 37.4879989624023 | 37.4309997558594 | 37.3499984741211 | 37.2840003967285 | 37.2319984436035 | 37.1860008239746 | 37.0960006713867 | 37.0460014343262 | 36.9900016784668 | 37 | 36.8940010070801 | 36.806999206543 | 36.7919998168945 | 36.7309989929199 | 36.6349983215332 | 36.5550003051758 | 36.5330009460449 | 36.4889984130859 | 36.4339981079102 | 36.4420013427734 | 38.9480018615723 | 39.3580017089844 |
1444 | Djibouti | DJI | Unemployment, female (% of female labor force) (national estimate) | SL.UEM.TOTL.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 35.9000015258789 | .. | .. | .. | .. |
1445 | Djibouti | DJI | Unemployment, male (% of male labor force) (modeled ILO estimate) | SL.UEM.TOTL.MA.ZS | 26.3619995117188 | 26.1949996948242 | 26.0020008087158 | 25.8490009307861 | 25.6620006561279 | 25.4570007324219 | 25.261999130249 | 25.0739994049072 | 24.8880004882813 | 24.6709995269775 | 24.4790000915527 | 24.2819995880127 | 24.1270008087158 | 23.8929996490479 | 23.6690006256104 | 23.492000579834 | 23.2830009460449 | 23.0499992370605 | 22.826000213623 | 22.6359996795654 | 22.431999206543 | 22.5750007629395 | 22.7560005187988 | 24.7280006408691 | 24.5550003051758 |
1446 | Djibouti | DJI | Unemployment, male (% of male labor force) (national estimate) | SL.UEM.TOTL.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 22.0699996948242 | .. | .. | .. | .. |
1447 | Djibouti | DJI | Unemployment, total (% of total labor force) (modeled ILO estimate) | SL.UEM.TOTL.ZS | 28.7019996643066 | 28.576000213623 | 28.431999206543 | 28.3449993133545 | 28.2169990539551 | 28.0830001831055 | 27.9640007019043 | 27.8470001220703 | 27.7199993133545 | 27.5739994049072 | 27.4440002441406 | 27.3050003051758 | 27.2210006713867 | 27.0580005645752 | 26.8880004882813 | 26.7779998779297 | 26.6380004882813 | 26.4750003814697 | 26.3250007629395 | 26.193000793457 | 26.0599994659424 | 26.1889991760254 | 26.3570003509521 | 28.3899993896484 | 28.3859996795654 |
1448 | Djibouti | DJI | Unemployment, total (% of total labor force) (national estimate) | SL.UEM.TOTL.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 26.0599994659424 | .. | .. | .. | .. |
1449 | Djibouti | DJI | Unemployment, youth female (% of female labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.FE.ZS | 53.890998840332 | 54.3600006103516 | 54.8870010375977 | 55.7220001220703 | 56.3339996337891 | 57.0779991149902 | 57.9669990539551 | 58.9029998779297 | 59.8349990844727 | 61.2270011901855 | 62.8310012817383 | 64.6389999389648 | 66.802001953125 | 68.8949966430664 | 70.1900024414063 | 71.5920028686523 | 72.8889999389648 | 74.1360015869141 | 75.4629974365234 | 76.6589965820313 | 77.9850006103516 | 78.0139999389648 | 78.1070022583008 | 82.5070037841797 | 82.1579971313477 |
1450 | Djibouti | DJI | Unemployment, youth female (% of female labor force ages 15-24) (national estimate) | SL.UEM.1524.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 74.5999984741211 | .. | .. | .. | .. |
1451 | Djibouti | DJI | Unemployment, youth male (% of male labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.MA.ZS | 53.2649993896484 | 53.6780014038086 | 54.1269989013672 | 54.8819999694824 | 55.4109992980957 | 56.0540008544922 | 56.8320007324219 | 57.6469993591309 | 58.4469985961914 | 59.7980003356934 | 61.3300018310547 | 63.015998840332 | 65.0429992675781 | 66.9499969482422 | 68.0660018920898 | 69.3359985351563 | 70.5230026245117 | 71.6539993286133 | 72.8629989624023 | 73.943000793457 | 75.1910018920898 | 75.3919982910156 | 75.6389999389648 | 80.2649993896484 | 78.6210021972656 |
1452 | Djibouti | DJI | Unemployment, youth male (% of male labor force ages 15-24) (national estimate) | SL.UEM.1524.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 72.0100021362305 | .. | .. | .. | .. |
1453 | Djibouti | DJI | Unemployment, youth total (% of total labor force ages 15-24) (modeled ILO estimate) | SL.UEM.1524.ZS | 53.4620018005371 | 53.8930015563965 | 54.3689994812012 | 55.1520004272461 | 55.7109985351563 | 56.390998840332 | 57.2099990844727 | 58.0699996948242 | 58.9160003662109 | 60.2869987487793 | 61.8470001220703 | 63.5769996643066 | 65.6529998779297 | 67.6259994506836 | 68.8040008544922 | 70.1220016479492 | 71.3519973754883 | 72.5279998779297 | 73.7839965820313 | 74.9059982299805 | 76.1869964599609 | 76.3330001831055 | 76.5289993286133 | 81.0609970092773 | 79.9069976806641 |
1454 | Djibouti | DJI | Unemployment, youth total (% of total labor force ages 15-24) (national estimate) | SL.UEM.1524.NE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 73.0400009155273 | .. | .. | .. | .. |
1455 | Djibouti | DJI | Vulnerable employment, female (% of female employment) (modeled ILO estimate) | SL.EMP.VULN.FE.ZS | 48.34999942779539 | 48.81000137329103 | 48.88000202178955 | 48.9799995422363 | 49.13999843597413 | 48.9999995231628 | 48.780001640319824 | 48.54999923706051 | 48.410000324249275 | 48.0599980354309 | 47.67000102996822 | 47.18999958038326 | 46.6899991035461 | 46.45000028610231 | 45.92999839782715 | 45.30999851226808 | 45.129998207092285 | 44.57999849319458 | 43.940001249313326 | 43.210001707077026 | 42.639998674392736 | 41.99999856948853 | 41.369998216629035 | .. | .. |
1456 | Djibouti | DJI | Vulnerable employment, male (% of male employment) (modeled ILO estimate) | SL.EMP.VULN.MA.ZS | 34.20000028610225 | 34.8800005912781 | 35.45000028610232 | 36.049999237060504 | 36.419999599456744 | 36.62999868392945 | 36.71999883651737 | 36.740000724792516 | 36.60000157356262 | 36.33999824523925 | 35.98999977111815 | 35.55999898910526 | 35.43999981880187 | 34.94000077247624 | 34.189999818801866 | 33.72999978065489 | 32.910000801086426 | 32.21000051498417 | 31.46000027656553 | 30.81999921798706 | 30.26000094413753 | 29.34000051021579 | 28.50999915599823 | .. | .. |
1457 | Djibouti | DJI | Vulnerable employment, total (% of total employment) (modeled ILO estimate) | SL.EMP.VULN.ZS | 39.4199981689453 | 40.030001640319824 | 40.41999912261966 | 40.87999963760374 | 41.210000991821346 | 41.319998741149945 | 41.349998950958295 | 41.299998283386245 | 41.16999912261967 | 40.88999843597412 | 40.51000070571895 | 40.059999227523754 | 39.78999853134157 | 39.38999891281131 | 38.7299997806549 | 38.21999931335445 | 37.679998159408555 | 37.04999876022342 | 36.3800010681152 | 35.69999980926513 | 35.15999937057491 | 34.35999822616577 | 33.60999965667728 | .. | .. |
1458 | Djibouti | DJI | Wage and salaried workers, female (% of female employment) (modeled ILO estimate) | SL.EMP.WORK.FE.ZS | 51.2000007629395 | 50.7200012207031 | 50.6599998474121 | 50.560001373291 | 50.3699989318848 | 50.5099983215332 | 50.7400016784668 | 50.9700012207031 | 51.0900001525879 | 51.4599990844727 | 51.8499984741211 | 52.3400001525879 | 52.8499984741211 | 53.0699996948242 | 53.5699996948242 | 54.2000007629395 | 54.3400001525879 | 54.8800010681152 | 55.5299987792969 | 56.2799987792969 | 56.8499984741211 | 57.4900016784668 | 58.1100006103516 | .. | .. |
1459 | Djibouti | DJI | Wage and salaried workers, male (% of male employment) (modeled ILO estimate) | SL.EMP.WORK.MA.ZS | 64.7799987792969 | 64.0299987792969 | 63.4900016784668 | 62.8699989318848 | 62.4599990844727 | 62.2599983215332 | 62.189998626709 | 62.1699981689453 | 62.2700004577637 | 62.560001373291 | 62.939998626709 | 63.4099998474121 | 63.5499992370605 | 63.9799995422363 | 64.7200012207031 | 65.2099990844727 | 65.9100036621094 | 66.620002746582 | 67.4000015258789 | 68.0999984741211 | 68.6800003051758 | 69.5999984741211 | 70.4400024414063 | .. | .. |
1460 | Djibouti | DJI | Wage and salaried workers, total (% of total employment) (modeled ILO estimate) | SL.EMP.WORK.ZS | 59.7700004577637 | 59.1100006103516 | 58.7400016784668 | 58.2700004577637 | 57.9099998474121 | 57.7999992370605 | 57.7999992370605 | 57.8400001525879 | 57.939998626709 | 58.25 | 58.6399993896484 | 59.1300010681152 | 59.4099998474121 | 59.7599983215332 | 60.4099998474121 | 60.939998626709 | 61.3899993896484 | 62.0299987792969 | 62.7299995422363 | 63.4500007629395 | 64 | 64.8000030517578 | 65.5500030517578 | .. | .. |
1461 | Djibouti | DJI | Women Business and the Law Index Score (scale 1-100) | SG.LAW.INDX | 53.125 | 53.125 | 53.125 | 53.125 | 53.125 | 53.125 | 53.125 | 53.125 | 56.25 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 59.375 | 61.875 | 68.125 | 68.125 | 68.125 |
1462 | Djibouti | DJI | Women making their own informed decisions regarding sexual relations, contraceptive use and reproductive health care (% of women age 15-49) | SG.DMK.SRCR.FN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1463 | Djibouti | DJI | Women participating in the three decisions (own health care, major household purchases, and visiting family) (% of women age 15-49) | SG.DMK.ALLD.FN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1464 | Djibouti | DJI | Women who believe a husband is justified in beating his wife (any of five reasons) (%) | SG.VAW.REAS.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1465 | Djibouti | DJI | Women who believe a husband is justified in beating his wife when she argues with him (%) | SG.VAW.ARGU.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1466 | Djibouti | DJI | Women who believe a husband is justified in beating his wife when she burns the food (%) | SG.VAW.BURN.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1467 | Djibouti | DJI | Women who believe a husband is justified in beating his wife when she goes out without telling him (%) | SG.VAW.GOES.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1468 | Djibouti | DJI | Women who believe a husband is justified in beating his wife when she neglects the children (%) | SG.VAW.NEGL.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1469 | Djibouti | DJI | Women who believe a husband is justified in beating his wife when she refuses sex with him (%) | SG.VAW.REFU.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1470 | Vietnam | VNM | Adequacy of social insurance programs (% of total welfare of beneficiary households) | per_si_allsi.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 31.0870754804204 | .. | .. | .. | 24.9349129142272 | .. | 28.2748117217932 | .. | 28.9393345877702 | .. | .. | .. | .. | .. | .. | .. |
1471 | Vietnam | VNM | Adequacy of social protection and labor programs (% of total welfare of beneficiary households) | per_allsp.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 26.3287820455898 | .. | .. | .. | 16.7464200492624 | .. | 19.8804252505164 | .. | 22.5241930656147 | .. | .. | .. | .. | .. | .. | .. |
1472 | Vietnam | VNM | Adequacy of social safety net programs (% of total welfare of beneficiary households) | per_sa_allsa.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.118541137866 | .. | .. | .. | 9.01395156709938 | .. | 2.4891827895112 | .. | 2.88902076181073 | .. | .. | .. | .. | .. | .. | .. |
1473 | Vietnam | VNM | Adequacy of unemployment benefits and ALMP (% of total welfare of beneficiary households) | per_lm_alllm.adq_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1474 | Vietnam | VNM | Adjusted net national income (annual % growth) | NY.ADJ.NNTY.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1475 | Vietnam | VNM | Adjusted net national income (constant 2015 US$) | NY.ADJ.NNTY.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 152600000000 | .. | .. | .. | .. | .. | .. |
1476 | Vietnam | VNM | Adjusted net national income (current US$) | NY.ADJ.NNTY.CD | 24810000000 | 25060000000 | 25890000000 | 27090000000 | 28310000000 | 30030000000 | 33170000000 | 36000000000 | 44580000000 | 50560000000 | 59670000000 | 75270000000 | 80180000000 | 89430000000 | 103200000000 | 120600000000 | 134200000000 | 146700000000 | 152600000000 | 161600000000 | 175600000000 | 193600000000 | 207200000000 | 217600000000 | .. |
1477 | Vietnam | VNM | Adjusted net national income per capita (annual % growth) | NY.ADJ.NNTY.PC.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1478 | Vietnam | VNM | Adjusted net national income per capita (constant 2015 US$) | NY.ADJ.NNTY.PC.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1646.5775217221449 | .. | .. | .. | .. | .. | .. |
1479 | Vietnam | VNM | Adjusted net national income per capita (current US$) | NY.ADJ.NNTY.PC.CD | 321.65132705740297 | 320.8061394870215 | 327.57278021267075 | 339.0046385820741 | 350.62080069356284 | 368.31077177406553 | 403.0295868916358 | 433.4069133868428 | 531.7736421157663 | 597.5120171590892 | 698.5517186058074 | 872.7621945993238 | 920.6330069552687 | 1016.6236669603163 | 1161.2286807641028 | 1342.9556065423362 | 1478.7456265850167 | 1599.5403093425912 | 1646.5775217221449 | 1725.7502060941943 | 1856.2241696391006 | 2026.250006031129 | 2147.9936971727802 | 2235.495867039692 | .. |
1480 | Vietnam | VNM | Adjusted net savings, excluding particulate emission damage (% of GNI) | NY.ADJ.SVNX.GN.ZS | 16.149762 | 18.041787 | 19.352106 | 19.785437 | 19.216325 | 19.433833 | 16.663024 | 14.036679 | 12.165551 | 11.82293 | 12.058476 | 7.4421341 | 8.4692818 | 12.883938 | 10.956617 | 13.944955 | 14.316089 | 14.091716 | 9.7541791 | 8.5795742 | 8.8437331 | 9.5012419 | 8.5900761 | 9.2955386 | .. |
1481 | Vietnam | VNM | Adjusted net savings, excluding particulate emission damage (current US$) | NY.ADJ.SVNX.CD | 4266000000 | 4798000000 | 5450000000 | 6079000000 | 6197000000 | 6704000000 | 6486000000 | 6257000000 | 6883000000 | 7678000000 | 9073000000 | 7158000000 | 8554000000 | 14430000000 | 14240000000 | 20920000000 | 23480000000 | 24940000000 | 17660000000 | 16390000000 | 18310000000 | 21760000000 | 21050000000 | 23800000000 | .. |
1482 | Vietnam | VNM | Adjusted net savings, including particulate emission damage (% of GNI) | NY.ADJ.SVNG.GN.ZS | 15.645229 | 17.551246 | 18.887039 | 19.357489 | 18.815456 | 19.050507 | 16.29118 | 13.668565 | 11.808874 | 11.47628 | 11.72 | 7.0988664 | 8.1047679 | 12.514049 | 10.578015 | 13.566422 | 13.938012 | 13.729972 | 9.3858625 | 8.2185929 | 8.4962067 | 9.1722106 | 8.2635527 | 8.9686326 | .. |
1483 | Vietnam | VNM | Adjusted net savings, including particulate emission damage (current US$) | NY.ADJ.SVNG.CD | 4132000000 | 4667000000 | 5319000000 | 5948000000 | 6068000000 | 6571000000 | 6341000000 | 6093000000 | 6681000000 | 7453000000 | 8819000000 | 6828000000 | 8186000000 | 14020000000 | 13750000000 | 20350000000 | 22860000000 | 24300000000 | 16990000000 | 15700000000 | 17590000000 | 21000000000 | 20250000000 | 22960000000 | .. |
1484 | Vietnam | VNM | Adjusted savings: carbon dioxide damage (% of GNI) | NY.ADJ.DCO2.GN.ZS | 2.5175122 | 2.8982264 | 2.8579925 | 3.0745277 | 3.3770182 | 3.8786585 | 3.8332104 | 4.1791809 | 3.7844102 | 3.6298321 | 3.6360133 | 3.2911036 | 3.6039455 | 3.8308779 | 3.4145537 | 3.0698969 | 3.0341086 | 3.2110356 | 4.0303754 | 4.2016213 | 4.0151975 | 4.4117612 | 4.6458016 | 4.835873 | .. |
1485 | Vietnam | VNM | Adjusted savings: carbon dioxide damage (current US$) | NY.ADJ.DCO2.CD | 665000000 | 770700000 | 804900000 | 944700000 | 1089000000 | 1338000000 | 1492000000 | 1863000000 | 2141000000 | 2357000000 | 2736000000 | 3165000000 | 3640000000 | 4291000000 | 4439000000 | 4605000000 | 4976000000 | 5684000000 | 7295000000 | 8025000000 | 8311000000 | 10100000000 | 11380000000 | 12380000000 | .. |
1486 | Vietnam | VNM | Adjusted savings: consumption of fixed capital (% of GNI) | NY.ADJ.DKAP.GN.ZS | 3.698863 | 4.360243 | 5.390147 | 6.3234902 | 7.6630715 | 9.0197527 | 10.761321 | 12.69311 | 14.130882 | 15.388256 | 15.524368 | 16.31332 | 17.903829 | 16.882495 | 16.664769 | 15.939896 | 15.368305 | 14.715188 | 14.396217 | 14.498919 | 14.178682 | 14.241073 | 14.625994 | 14.537728 | .. |
1487 | Vietnam | VNM | Adjusted savings: consumption of fixed capital (current US$) | NY.ADJ.DKAP.CD | 977000000 | 1160000000 | 1518000000 | 1943000000 | 2471000000 | 3111000000 | 4189000000 | 5658000000 | 7995000000 | 9994000000 | 11680000000 | 15690000000 | 18080000000 | 18910000000 | 21660000000 | 23910000000 | 25200000000 | 26050000000 | 26060000000 | 27690000000 | 29350000000 | 32610000000 | 35830000000 | 37220000000 | .. |
1488 | Vietnam | VNM | Adjusted savings: education expenditure (% of GNI) | NY.ADJ.AEDU.GN.ZS | 2.6 | 2.8134768 | 2.9044295 | 2.9953822 | 3.0863349 | 3.1772876 | 3.2682402 | 3.3591929 | 3.4501456 | 3.5410983 | 3.632051 | 3.7230037 | 3.8139564 | 5.36 | 3.8720162 | 4.5866422 | 4.6030501 | 4.6030501 | 4.6030501 | 4.6030501 | 4.6030501 | 4.6030501 | 4.6030501 | 4.6030501 | .. |
1489 | Vietnam | VNM | Adjusted savings: education expenditure (current US$) | NY.ADJ.AEDU.CD | 686800000 | 748200000 | 818000000 | 920400000 | 995300000 | 1096000000 | 1272000000 | 1497000000 | 1952000000 | 2300000000 | 2733000000 | 3581000000 | 3852000000 | 6003000000 | 5034000000 | 6880000000 | 7549000000 | 8147000000 | 8332000000 | 8792000000 | 9528000000 | 10540000000 | 11280000000 | 11780000000 | .. |
1490 | Vietnam | VNM | Adjusted savings: energy depletion (% of GNI) | NY.ADJ.DNGY.GN.ZS | 2.3676429 | 1.3881996 | 2.6609134 | 5.4987826 | 4.5412352 | 3.8867733 | 3.993455 | 6.5321389 | 7.0209978 | 6.5905459 | 4.9266895 | 4.9238113 | 2.3318009 | 3.0171982 | 3.5846693 | 3.3883781 | 2.6302764 | 2.2741765 | 1.2106826 | 0.8231446 | 0.89484211 | 1.1303801 | 0.77403616 | 0.43654839 | .. |
1491 | Vietnam | VNM | Adjusted savings: energy depletion (current US$) | NY.ADJ.DNGY.CD | 625400000 | 369200000 | 749400000 | 1690000000 | 1464000000 | 1341000000 | 1554000000 | 2912000000 | 3972000000 | 4280000000 | 3707000000 | 4736000000 | 2355000000 | 3379000000 | 4660000000 | 5083000000 | 4314000000 | 4025000000 | 2191000000 | 1572000000 | 1852000000 | 2589000000 | 1896000000 | 1118000000 | .. |
1492 | Vietnam | VNM | Adjusted savings: gross savings (% of GNI) | NY.ADJ.ICTR.GN.ZS | 22.150266 | 23.886082 | 27.367414 | 31.701954 | 31.726413 | 33.064972 | 32.00212 | 34.105333 | 33.693572 | 34.062673 | 32.75887 | 28.756065 | 28.740736 | 31.641251 | 31.183439 | 32.121047 | 30.963386 | 29.751973 | 24.86601 | 23.571947 | 23.454784 | 24.712583 | 24.03339 | 24.575122 | .. |
1493 | Vietnam | VNM | Adjusted savings: mineral depletion (% of GNI) | NY.ADJ.DMIN.GN.ZS | 0.01648542 | 0.01110234 | 0.01068516 | 0.01509842 | 0.01509812 | 0.02324221 | 0.01934932 | 0.02341732 | 0.04187685 | 0.17220668 | 0.24537452 | 0.50870009 | 0.37335918 | 0.24909602 | 0.36243366 | 0.27230816 | 0.19590006 | 0.12352794 | 0.09129627 | 0.08818805 | 0.10071711 | 0.07361622 | 0.01263381 | 0.02842407 | .. |
1494 | Vietnam | VNM | Adjusted savings: mineral depletion (current US$) | NY.ADJ.DMIN.CD | 4354421.3 | 2952445 | 3009344.2 | 4639131.7 | 4868819 | 8017243.9 | 7531440.7 | 10438686 | 23691930 | 111800000 | 184600000 | 489300000 | 377100000 | 279000000 | 471200000 | 408500000 | 321300000 | 218600000 | 165200000 | 168400000 | 208500000 | 168600000 | 30952823 | 72765611 | .. |
1495 | Vietnam | VNM | Adjusted savings: natural resources depletion (% of GNI) | NY.ADJ.DRES.GN.ZS | 2.38412832 | 1.3993019400000002 | 2.67159856 | 5.51388102 | 4.55633332 | 3.91001551 | 4.01280432 | 6.55555622 | 7.06287465 | 6.762752580000001 | 5.1720640200000005 | 5.43251139 | 2.70516008 | 3.2662942200000002 | 3.9471029599999996 | 3.6606862600000003 | 2.82617646 | 2.39770444 | 1.30197887 | 0.91133265 | 0.9955592200000001 | 1.20399632 | 0.7866699699999999 | 0.46497246000000003 | .. |
1496 | Vietnam | VNM | Adjusted savings: net forest depletion (% of GNI) | NY.ADJ.DFOR.GN.ZS | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
1497 | Vietnam | VNM | Adjusted savings: net forest depletion (current US$) | NY.ADJ.DFOR.CD | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | .. |
1498 | Vietnam | VNM | Adjusted savings: net national savings (% of GNI) | NY.ADJ.NNAT.GN.ZS | 18.451403 | 19.525839 | 21.977267 | 25.378464 | 24.063342 | 24.045219 | 21.240798 | 21.412223 | 19.56269 | 18.674417 | 17.234503 | 12.442745 | 10.964431 | 14.62111 | 14.446257 | 16.088896 | 15.573324 | 15.097406 | 10.483483 | 9.0894781 | 9.2514397 | 10.513949 | 9.4194976 | 9.9933339 | .. |
1499 | Vietnam | VNM | Adjusted savings: net national savings (current US$) | NY.ADJ.NNAT.CD | 4874000000 | 5193000000 | 6190000000 | 7798000000 | 7760000000 | 8294000000 | 8268000000 | 9545000000 | 11070000000 | 12130000000 | 12970000000 | 11970000000 | 11070000000 | 16380000000 | 18780000000 | 24130000000 | 25540000000 | 26720000000 | 18980000000 | 17360000000 | 19150000000 | 24080000000 | 23080000000 | 25580000000 | .. |
1500 | Vietnam | VNM | Adjusted savings: particulate emission damage (% of GNI) | NY.ADJ.DPEM.GN.ZS | 0.50453345 | 0.49054119 | 0.46506617 | 0.427948 | 0.4008694 | 0.38332627 | 0.37184406 | 0.36811403 | 0.35667647 | 0.34665006 | 0.3384763 | 0.34326769 | 0.36451396 | 0.36988877 | 0.37860207 | 0.378533 | 0.3780771 | 0.36174421 | 0.36831664 | 0.36098128 | 0.34752642 | 0.32903129 | 0.32652344 | 0.32690602 | .. |
1501 | Vietnam | VNM | Adjusted savings: particulate emission damage (current US$) | NY.ADJ.DPEM.CD | 133300000 | 130400000 | 131000000 | 131500000 | 129300000 | 132200000 | 144700000 | 164100000 | 201800000 | 225100000 | 254700000 | 330200000 | 368200000 | 414300000 | 492200000 | 567800000 | 620000000 | 640300000 | 666700000 | 689500000 | 719400000 | 753500000 | 800000000 | 836900000 | .. |
1502 | Vietnam | VNM | Agriculture, forestry, and fishing, value added (annual % growth) | NV.AGR.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1503 | Vietnam | VNM | Agriculture, forestry, and fishing, value added (constant 2015 US$) | NV.AGR.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1504 | Vietnam | VNM | Agriculture, forestry, and fishing, value added per worker (constant 2015 US$) | NV.AGR.EMPL.KD | 710.9304788851892 | 719.5827541991346 | 736.7239149744294 | 750.2784569337318 | 773.821170196589 | 808.4603558970374 | 855.7723058490952 | 902.6652236048357 | 973.1935151629041 | 1052.3408203648032 | 1125.1575317333768 | 1168.1544698980797 | 1194.2235301565383 | 1140.3773656552655 | 1176.6226202949313 | 1215.9912855612572 | 1236.0747310291338 | 1273.9676447590614 | 1366.7415389201349 | 1449.721243474592 | 1538.9148277958654 | 1629.005102443523 | 1734.9376309227696 | .. | .. |
1505 | Vietnam | VNM | Annualized average growth rate in per capita real survey mean consumption or income, bottom 40% of population (%) | SI.SPR.PC40.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.75 | .. | .. | .. |
1506 | Vietnam | VNM | Annualized average growth rate in per capita real survey mean consumption or income, total population (%) | SI.SPR.PCAP.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.46 | .. | .. | .. |
1507 | Vietnam | VNM | Average working hours of children, study and work, ages 7-14 (hours per week) | SL.TLF.0714.SW.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1508 | Vietnam | VNM | Average working hours of children, study and work, female, ages 7-14 (hours per week) | SL.TLF.0714.SW.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1509 | Vietnam | VNM | Average working hours of children, study and work, male, ages 7-14 (hours per week) | SL.TLF.0714.SW.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.8 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1510 | Vietnam | VNM | Average working hours of children, working only, ages 7-14 (hours per week) | SL.TLF.0714.WK.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 34.2 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1511 | Vietnam | VNM | Average working hours of children, working only, female, ages 7-14 (hours per week) | SL.TLF.0714.WK.FE.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 32.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1512 | Vietnam | VNM | Average working hours of children, working only, male, ages 7-14 (hours per week) | SL.TLF.0714.WK.MA.TM | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 35.3 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1513 | Vietnam | VNM | Benefit incidence of social insurance programs to poorest quintile (% of total social insurance benefits) | per_si_allsi.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 1.90616723709744 | .. | .. | .. | 1.07852598112075 | .. | 1.95383206025073 | .. | 1.6220909516921 | .. | .. | .. | .. | .. | .. | .. |
1514 | Vietnam | VNM | Benefit incidence of social protection and labor programs to poorest quintile (% of total SPL benefits) | per_allsp.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 4.67684279411817 | .. | .. | .. | 3.05921178480699 | .. | 3.80939896722388 | .. | 3.67648029252563 | .. | .. | .. | .. | .. | .. | .. |
1515 | Vietnam | VNM | Benefit incidence of social safety net programs to poorest quintile (% of total safety net benefits) | per_sa_allsa.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.5393713498041 | .. | .. | .. | 6.50028696440252 | .. | 43.6501556076413 | .. | 63.7974577317895 | .. | .. | .. | .. | .. | .. | .. |
1516 | Vietnam | VNM | Benefit incidence of unemployment benefits and ALMP to poorest quintile (% of total U/ALMP benefits) | per_lm_alllm.ben_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1517 | Vietnam | VNM | Child employment in agriculture (% of economically active children ages 7-14) | SL.AGR.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 77.14 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1518 | Vietnam | VNM | Child employment in agriculture, female (% of female economically active children ages 7-14) | SL.AGR.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 72.73 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1519 | Vietnam | VNM | Child employment in agriculture, male (% of male economically active children ages 7-14) | SL.AGR.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 80.66 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1520 | Vietnam | VNM | Child employment in manufacturing (% of economically active children ages 7-14) | SL.MNF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1521 | Vietnam | VNM | Child employment in manufacturing, female (% of female economically active children ages 7-14) | SL.MNF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.41 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1522 | Vietnam | VNM | Child employment in manufacturing, male (% of male economically active children ages 7-14) | SL.MNF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 3.91 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1523 | Vietnam | VNM | Child employment in services (% of economically active children ages 7-14) | SL.SRV.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 16.18 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1524 | Vietnam | VNM | Child employment in services, female (% of female economically active children ages 7-14) | SL.SRV.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 18.39 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1525 | Vietnam | VNM | Child employment in services, male (% of male economically active children ages 7-14) | SL.SRV.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.42 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1526 | Vietnam | VNM | Children in employment, female (% of female children ages 7-14) | SL.TLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 21.6 | .. | .. | .. | .. | 13.5 | 10.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1527 | Vietnam | VNM | Children in employment, male (% of male children ages 7-14) | SL.TLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 21 | .. | .. | .. | .. | 12.5 | 11.7 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1528 | Vietnam | VNM | Children in employment, self-employed (% of children in employment, ages 7-14) | SL.SLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8.18 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1529 | Vietnam | VNM | Children in employment, self-employed, female (% of female children in employment, ages 7-14) | SL.SLF.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.03 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1530 | Vietnam | VNM | Children in employment, self-employed, male (% of male children in employment, ages 7-14) | SL.SLF.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1531 | Vietnam | VNM | Children in employment, study and work (% of children in employment, ages 7-14) | SL.TLF.0714.SW.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 88.1 | .. | .. | .. | .. | 84.1 | 81 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1532 | Vietnam | VNM | Children in employment, study and work, female (% of female children in employment, ages 7-14) | SL.TLF.0714.SW.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 83.4 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1533 | Vietnam | VNM | Children in employment, study and work, male (% of male children in employment, ages 7-14) | SL.TLF.0714.SW.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 79.1 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1534 | Vietnam | VNM | Children in employment, total (% of children ages 7-14) | SL.TLF.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 21.3 | .. | .. | .. | .. | 13 | 10.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1535 | Vietnam | VNM | Children in employment, unpaid family workers (% of children in employment, ages 7-14) | SL.FAM.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 87.37 | 84.29 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1536 | Vietnam | VNM | Children in employment, unpaid family workers, female (% of female children in employment, ages 7-14) | SL.FAM.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 85.52 | 86.71 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1537 | Vietnam | VNM | Children in employment, unpaid family workers, male (% of male children in employment, ages 7-14) | SL.FAM.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 89.2 | 82.35 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1538 | Vietnam | VNM | Children in employment, wage workers (% of children in employment, ages 7-14) | SL.WAG.0714.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.69 | 7.53 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1539 | Vietnam | VNM | Children in employment, wage workers, female (% of female children in employment, ages 7-14) | SL.WAG.0714.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.59 | 7.26 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1540 | Vietnam | VNM | Children in employment, wage workers, male (% of male children in employment, ages 7-14) | SL.WAG.0714.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.8 | 7.75 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1541 | Vietnam | VNM | Children in employment, work only (% of children in employment, ages 7-14) | SL.TLF.0714.WK.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | 11.9 | .. | .. | .. | .. | 15.9 | 19 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1542 | Vietnam | VNM | Children in employment, work only, female (% of female children in employment, ages 7-14) | SL.TLF.0714.WK.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 16.6 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1543 | Vietnam | VNM | Children in employment, work only, male (% of male children in employment, ages 7-14) | SL.TLF.0714.WK.MA.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.9 | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1544 | Vietnam | VNM | Community health workers (per 1,000 people) | SH.MED.CMHW.P3 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1545 | Vietnam | VNM | Contributing family workers, female (% of female employment) (modeled ILO estimate) | SL.FAM.WORK.FE.ZS | 56.7400016784668 | 53.9199981689453 | 55.1300010681152 | 54.2099990844727 | 54.1100006103516 | 53.3899993896484 | 51.0400009155273 | 47.5099983215332 | 42.0499992370605 | 36.7299995422363 | 31.6100006103516 | 26.8299999237061 | 22.3099994659424 | 26.3400001525879 | 24.9200000762939 | 23.1900005340576 | 22.6800003051758 | 26.6299991607666 | 23.3700008392334 | 22.1499996185303 | 21.4799995422363 | 20.4300003051758 | 19.0799999237061 | .. | .. |
1546 | Vietnam | VNM | Contributing family workers, male (% of male employment) (modeled ILO estimate) | SL.FAM.WORK.MA.ZS | 23.4300003051758 | 22.7099990844727 | 23.0599994659424 | 21.7000007629395 | 22.3899993896484 | 23.9899997711182 | 22.2700004577637 | 19.0200004577637 | 17.6399993896484 | 16.2399997711182 | 14.7799997329712 | 13.3299999237061 | 11.8500003814697 | 13.0900001525879 | 12.539999961853 | 12.1599998474121 | 12.0799999237061 | 16.6000003814697 | 11.5 | 10.460000038147 | 10.1899995803833 | 9.89999961853027 | 9.15999984741211 | .. | .. |
1547 | Vietnam | VNM | Contributing family workers, total (% of total employment) (modeled ILO estimate) | SL.FAM.WORK.ZS | 39.6199989318848 | 37.8400001525879 | 38.560001373291 | 37.439998626709 | 37.6300010681152 | 38.1599998474121 | 36.0999984741211 | 32.7099990844727 | 29.3799991607666 | 26.1000003814697 | 22.8799991607666 | 19.8199996948242 | 16.8700008392334 | 19.4099998474121 | 18.4699993133545 | 17.4599990844727 | 17.1700000762939 | 21.4200000762939 | 17.1700000762939 | 16.0499992370605 | 15.5900001525879 | 14.9300003051758 | 13.8999996185303 | .. | .. |
1548 | Vietnam | VNM | Coverage of social insurance programs (% of population) | per_si_allsi.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 17.1598824549761 | .. | .. | .. | 14.0923491492514 | .. | 14.4107161374148 | .. | 15.2492432666176 | .. | .. | .. | .. | .. | .. | .. |
1549 | Vietnam | VNM | Coverage of social insurance programs in 2nd quintile (% of population) | per_si_allsi.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 7.9550919273315 | .. | .. | .. | 5.59155317933305 | .. | 6.93270333447554 | .. | 7.01815430876617 | .. | .. | .. | .. | .. | .. | .. |
1550 | Vietnam | VNM | Coverage of social insurance programs in 3rd quintile (% of population) | per_si_allsi.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.1131812495988 | .. | .. | .. | 11.1851466859905 | .. | 11.6623936809786 | .. | 12.3346880877971 | .. | .. | .. | .. | .. | .. | .. |
1551 | Vietnam | VNM | Coverage of social insurance programs in 4th quintile (% of population) | per_si_allsi.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 22.1270761025657 | .. | .. | .. | 19.3957722321376 | .. | 20.4168682648085 | .. | 20.3496829964469 | .. | .. | .. | .. | .. | .. | .. |
1552 | Vietnam | VNM | Coverage of social insurance programs in poorest quintile (% of population) | per_si_allsi.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 5.51185442882699 | .. | .. | .. | 2.15203912074846 | .. | 2.82492845187023 | .. | 3.11494198837069 | .. | .. | .. | .. | .. | .. | .. |
1553 | Vietnam | VNM | Coverage of social insurance programs in richest quintile (% of population) | per_si_allsi.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 36.0866707678521 | .. | .. | .. | 32.1313702701249 | .. | 30.2094202279661 | .. | 33.4178396805731 | .. | .. | .. | .. | .. | .. | .. |
1554 | Vietnam | VNM | Coverage of social protection and labor programs (% of population) | per_allsp.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 37.4487034117681 | .. | .. | .. | 55.0599142905182 | .. | 40.4465516629976 | .. | 34.8579326536508 | .. | .. | .. | .. | .. | .. | .. |
1555 | Vietnam | VNM | Coverage of social safety net programs (% of population) | per_sa_allsa.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 22.5312115655317 | .. | .. | .. | 38.5410478848029 | .. | 23.3843714424791 | .. | 17.5068280169369 | .. | .. | .. | .. | .. | .. | .. |
1556 | Vietnam | VNM | Coverage of social safety net programs in 2nd quintile (% of population) | per_sa_allsa.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 23.9815388527973 | .. | .. | .. | 40.8296289306321 | .. | 26.0030758394187 | .. | 19.7374296064221 | .. | .. | .. | .. | .. | .. | .. |
1557 | Vietnam | VNM | Coverage of social safety net programs in 3rd quintile (% of population) | per_sa_allsa.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 17.3059202809682 | .. | .. | .. | 35.1523623024699 | .. | 15.2205744681066 | .. | 10.7925183097415 | .. | .. | .. | .. | .. | .. | .. |
1558 | Vietnam | VNM | Coverage of social safety net programs in 4th quintile (% of population) | per_sa_allsa.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 14.6865647591205 | .. | .. | .. | 31.4829136993085 | .. | 11.0585466772453 | .. | 5.35849043459861 | .. | .. | .. | .. | .. | .. | .. |
1559 | Vietnam | VNM | Coverage of social safety net programs in poorest quintile (% of population) | per_sa_allsa.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 47.205404748293 | .. | .. | .. | 58.2617207124027 | .. | 58.9311662342351 | .. | 48.3865774052822 | .. | .. | .. | .. | .. | .. | .. |
1560 | Vietnam | VNM | Coverage of social safety net programs in richest quintile (% of population) | per_sa_allsa.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 9.48374261087224 | .. | .. | .. | 26.9893615491785 | .. | 5.71483935824504 | .. | 3.26827187574559 | .. | .. | .. | .. | .. | .. | .. |
1561 | Vietnam | VNM | Coverage of unemployment benefits and ALMP (% of population) | per_lm_alllm.cov_pop_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.08825278751 | .. | .. | .. | 18.4187635134711 | .. | 14.1807390506436 | .. | 8.97639302634177 | .. | .. | .. | .. | .. | .. | .. |
1562 | Vietnam | VNM | Coverage of unemployment benefits and ALMP in 2nd quintile (% of population) | per_lm_alllm.cov_q2_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 6.61469130054842 | .. | .. | .. | 19.942072379211 | .. | 16.2411101712557 | .. | 9.1787862809188 | .. | .. | .. | .. | .. | .. | .. |
1563 | Vietnam | VNM | Coverage of unemployment benefits and ALMP in 3rd quintile (% of population) | per_lm_alllm.cov_q3_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.50894304838074 | .. | .. | .. | 16.1834321962503 | .. | 11.7885159489877 | .. | 6.0289782153829 | .. | .. | .. | .. | .. | .. | .. |
1564 | Vietnam | VNM | Coverage of unemployment benefits and ALMP in 4th quintile (% of population) | per_lm_alllm.cov_q4_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2.04637345328565 | .. | .. | .. | 12.2841323021365 | .. | 6.40880702804594 | .. | 3.94674784407433 | .. | .. | .. | .. | .. | .. | .. |
1565 | Vietnam | VNM | Coverage of unemployment benefits and ALMP in poorest quintile (% of population) | per_lm_alllm.cov_q1_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 18.896088747493 | .. | .. | .. | 40.3625024915716 | .. | 33.4595110357731 | .. | 24.4048442996947 | .. | .. | .. | .. | .. | .. | .. |
1566 | Vietnam | VNM | Coverage of unemployment benefits and ALMP in richest quintile (% of population) | per_lm_alllm.cov_q5_tot | .. | .. | .. | .. | .. | .. | .. | .. | .. | 0.378738904606037 | .. | .. | .. | 3.33436254167076 | .. | 3.01000379430127 | .. | 1.32689196096911 | .. | .. | .. | .. | .. | .. | .. |
1567 | Vietnam | VNM | Current health expenditure (% of GDP) | SH.XPD.CHEX.GD.ZS | .. | .. | .. | 3.81915784 | 4.51130724 | 3.59967494 | 3.66619444 | 3.7992034 | 4.01387453 | 4.24659586 | 4.30235815 | 4.05425787 | 4.16906261 | 4.69927359 | 4.6128521 | 5.00178242 | 5.07556248 | 4.6127553 | 4.56543732 | 4.51853609 | 4.71283436 | 5.03448868 | 5.24965572 | .. | .. |
1568 | Vietnam | VNM | Current health expenditure per capita (current US$) | SH.XPD.CHEX.PC.CD | .. | .. | .. | 18.91674423 | 23.18782616 | 19.65594101 | 22.37121964 | 28.7441864 | 35.03743744 | 42.29331589 | 49.50850296 | 59.16986084 | 64.43672943 | 78.63555908 | 89.58512878 | 108.93997192 | 119.52192688 | 117.41460419 | 117.86289215 | 124.0594101 | 140.16532898 | 163.1509552 | 180.71818542 | .. | .. |
1569 | Vietnam | VNM | Current health expenditure per capita, PPP (current international $) | SH.XPD.CHEX.PP.CD | .. | .. | .. | 96.36966705 | 122.26291656 | 104.34003448 | 114.63062286 | 141.61390686 | 150.88922119 | 174.31311035 | 192.45111084 | 193.48219299 | 209.23999023 | 251.39782715 | 265.6947937 | 316.587677 | 339.48956299 | 332.25540161 | 344.95898438 | 371.97747803 | 423.98468018 | 493.9914856 | 558.87298584 | .. | .. |
1570 | Vietnam | VNM | Domestic general government health expenditure (% of current health expenditure) | SH.XPD.GHED.CH.ZS | .. | .. | .. | 34.89794922 | 26.49161148 | 36.47419739 | 32.91641998 | 35.65555954 | 36.72709656 | 36.02748108 | 35.31490707 | 37.67632294 | 36.24856949 | 39.61755371 | 38.69340134 | 41.91252899 | 47.11077499 | 41.95794296 | 41.80939484 | 47.43162537 | 46.10822678 | 41.62815475 | 43.7980957 | .. | .. |
1571 | Vietnam | VNM | Domestic general government health expenditure (% of GDP) | SH.XPD.GHED.GD.ZS | .. | .. | .. | 1.33280778 | 1.19511807 | 1.31295264 | 1.20678008 | 1.35462737 | 1.47417974 | 1.52994156 | 1.51937377 | 1.52749527 | 1.51122534 | 1.86173725 | 1.78486931 | 2.09637356 | 2.39113688 | 1.93541718 | 1.90878153 | 2.14321518 | 2.17300439 | 2.09576464 | 2.29924917 | .. | .. |
1572 | Vietnam | VNM | Domestic general government health expenditure (% of general government expenditure) | SH.XPD.GHED.GE.ZS | .. | .. | .. | 7.49261236 | 6.22713661 | 6.64880705 | 5.43691063 | 6.96803188 | 7.14737988 | 7.45082951 | 6.81436205 | 7.14450169 | 6.0510025 | 7.84861135 | 8.40974712 | 8.93348789 | 9.77689266 | 8.50548553 | 7.89614296 | 9.64080048 | 10.09323883 | 10.21770763 | 10.06818295 | .. | .. |
1573 | Vietnam | VNM | Domestic general government health expenditure per capita (current US$) | SH.XPD.GHED.PC.CD | .. | .. | .. | 6.6015554 | 6.14282925 | 7.16934722 | 7.36380559 | 10.24890108 | 12.8682337 | 15.23721709 | 17.48388091 | 22.29302947 | 23.3573898 | 31.15348338 | 34.66353448 | 45.65949866 | 56.3077061 | 49.26475222 | 49.27776173 | 58.84340106 | 64.62774436 | 67.91673632 | 79.15112415 | .. | .. |
1574 | Vietnam | VNM | Domestic general government health expenditure per capita, PPP (current international $) | SH.XPD.GHED.PP.CD | .. | .. | .. | 33.631037 | 32.38941783 | 38.05718879 | 37.73229956 | 50.49323325 | 55.41723015 | 62.8006228 | 67.96392602 | 72.89697968 | 75.84649643 | 99.59766531 | 102.80635429 | 132.68990127 | 159.93616078 | 139.40753482 | 144.22526636 | 176.43498073 | 195.49182487 | 205.63954366 | 244.77572261 | .. | .. |
1575 | Vietnam | VNM | Domestic private health expenditure (% of current health expenditure) | SH.XPD.PVTD.CH.ZS | .. | .. | .. | 60.85498428 | 69.58628082 | 58.83494186 | 62.19817352 | 58.8431282 | 59.2638092 | 59.96383286 | 61.08750153 | 60.11936188 | 61.29605865 | 58.13803101 | 58.94776535 | 55.66624451 | 50.6530838 | 54.85071564 | 56.0296402 | 50.27044296 | 52.80683136 | 57.35515976 | 55.23139954 | .. | .. |
1576 | Vietnam | VNM | Domestic private health expenditure per capita (current US$) | SH.XPD.PVTD.PC.CD | .. | .. | .. | 11.51178156 | 16.13554664 | 11.56456145 | 13.91449165 | 16.91397839 | 20.76451866 | 25.36069528 | 30.24350685 | 35.57254339 | 39.49717403 | 45.71716244 | 52.80843189 | 60.64279008 | 60.54153991 | 64.40274986 | 66.03815805 | 62.36522353 | 74.01686304 | 93.57549448 | 99.8131897 | .. | .. |
1577 | Vietnam | VNM | Domestic private health expenditure per capita, PPP (current international $) | SH.XPD.PVTD.PP.CD | .. | .. | .. | 58.64574757 | 85.07821729 | 61.38839214 | 71.29815701 | 83.33005157 | 89.42269286 | 104.5248256 | 117.5635703 | 116.32025949 | 128.25586653 | 146.15773743 | 156.62114209 | 176.23246126 | 171.96192371 | 182.24446869 | 193.27929273 | 186.99474901 | 223.89287712 | 283.32960364 | 308.67338771 | .. | .. |
1578 | Vietnam | VNM | Employers, female (% of female employment) (modeled ILO estimate) | SL.EMP.MPYR.FE.ZS | 0.100000001490116 | 0.0199999995529652 | 0.0799999982118607 | 0.150000005960464 | 0.300000011920929 | 0.270000010728836 | 0.230000004172325 | 0.300000011920929 | 0.490000009536743 | 0.800000011920929 | 1.27999997138977 | 2.03999996185303 | 3.19000005722046 | 2.22000002861023 | 1.8400000333786 | 1.66999995708466 | 1.5 | 1.21000003814697 | 1.87000000476837 | 1.8400000333786 | 1.12000000476837 | 1.19000005722046 | 1.13999998569489 | .. | .. |
1579 | Vietnam | VNM | Employers, male (% of male employment) (modeled ILO estimate) | SL.EMP.MPYR.MA.ZS | 0.209999993443489 | 0.0700000002980232 | 0.159999996423721 | 0.270000010728836 | 0.310000002384186 | 0.5 | 0.449999988079071 | 0.699999988079071 | 1.0900000333786 | 1.71000003814697 | 2.65000009536743 | 4.1100001335144 | 6.26000022888184 | 4.55000019073486 | 3.85999989509583 | 3.64000010490417 | 3.40000009536743 | 2.90000009536743 | 3.83999991416931 | 3.75 | 2.88000011444092 | 3.00999999046326 | 2.79999995231628 | .. | .. |
1580 | Vietnam | VNM | Employers, total (% of total employment) (modeled ILO estimate) | SL.EMP.MPYR.ZS | 0.159999996423721 | 0.0399999991059303 | 0.119999997317791 | 0.209999993443489 | 0.310000002384186 | 0.389999985694885 | 0.349999994039536 | 0.509999990463257 | 0.800000011920929 | 1.26999998092651 | 1.99000000953674 | 3.10999989509583 | 4.78999996185303 | 3.44000005722046 | 2.89000010490417 | 2.70000004768372 | 2.49000000953674 | 2.08999991416931 | 2.90000009536743 | 2.82999992370605 | 2.02999997138977 | 2.14000010490417 | 2 | .. | .. |
1581 | Vietnam | VNM | Employment in agriculture (% of total employment) (modeled ILO estimate) | SL.AGR.EMPL.ZS | 65.2799987792969 | 64.7699966430664 | 64.9899978637695 | 65.25 | 63.9900016784668 | 62.0400009155273 | 59.6800003051758 | 57.9000015258789 | 54.8300018310547 | 51.6699981689453 | 49.2799987792969 | 48.6199989318848 | 47.5499992370605 | 48.7099990844727 | 48.310001373291 | 47.3699989318848 | 46.810001373291 | 46.3400001525879 | 44.0200004577637 | 41.8699989318848 | 40.1599998474121 | 38.7000007629395 | 37.2200012207031 | .. | .. |
1582 | Vietnam | VNM | Employment in agriculture, female (% of female employment) (modeled ILO estimate) | SL.AGR.EMPL.FE.ZS | 66.0199966430664 | 65.5999984741211 | 65.4499969482422 | 66.2799987792969 | 64.9599990844727 | 63.1300010681152 | 61.7099990844727 | 59.9900016784668 | 56.9599990844727 | 53.7799987792969 | 51.4799995422363 | 50.9599990844727 | 50.0200004577637 | 51.189998626709 | 50.9500007629395 | 49.5099983215332 | 48.7799987792969 | 48.1300010681152 | 45.4500007629395 | 43.4799995422363 | 41.4700012207031 | 39.9000015258789 | 38.2999992370605 | .. | .. |
1583 | Vietnam | VNM | Employment in agriculture, male (% of male employment) (modeled ILO estimate) | SL.AGR.EMPL.MA.ZS | 64.5800018310547 | 63.9799995422363 | 64.5599975585938 | 64.2900009155273 | 63.0900001525879 | 61.0299987792969 | 57.7900009155273 | 55.9599990844727 | 52.8600006103516 | 49.7000007629395 | 47.25 | 46.4500007629395 | 45.2700004577637 | 46.439998626709 | 45.8899993896484 | 45.3899993896484 | 44.9900016784668 | 44.6800003051758 | 42.7099990844727 | 40.3800010681152 | 38.9500007629395 | 37.5999984741211 | 36.2299995422363 | .. | .. |
1584 | Vietnam | VNM | Employment in industry (% of total employment) (modeled ILO estimate) | SL.IND.EMPL.ZS | 12.6800003051758 | 11.5799999237061 | 11.9899997711182 | 12.4399995803833 | 13.8999996185303 | 14.6999998092651 | 16.4099998474121 | 17.3500003814697 | 18.7399997711182 | 20.1900005340576 | 20.3899993896484 | 21 | 21.8500003814697 | 21.6800003051758 | 21.2800006866455 | 21.1900005340576 | 21.1800003051758 | 21.4500007629395 | 22.7399997711182 | 24.7600002288818 | 25.7800006866455 | 26.6399993896484 | 27.4400005340576 | .. | .. |
1585 | Vietnam | VNM | Employment in industry, female (% of female employment) (modeled ILO estimate) | SL.IND.EMPL.FE.ZS | 10.3999996185303 | 9.13000011444092 | 9.84000015258789 | 10.1199998855591 | 11.1499996185303 | 11.6999998092651 | 12.9700002670288 | 13.7299995422363 | 14.7799997329712 | 15.8999996185303 | 16.0900001525879 | 16.4400005340576 | 16.9699993133545 | 17.25 | 16.5599994659424 | 16.8400001525879 | 16.9599990844727 | 17.5 | 19.3199996948242 | 20.7700004577637 | 21.8099994659424 | 22.5599994659424 | 23.2800006866455 | .. | .. |
1586 | Vietnam | VNM | Employment in industry, male (% of male employment) (modeled ILO estimate) | SL.IND.EMPL.MA.ZS | 14.8400001525879 | 13.8900003433228 | 14.0100002288818 | 14.6199998855591 | 16.4400005340576 | 17.4899997711182 | 19.6000003814697 | 20.7099990844727 | 22.3999996185303 | 24.1599998474121 | 24.3799991607666 | 25.2299995422363 | 26.3600006103516 | 25.7199993133545 | 25.6200008392334 | 25.2199993133545 | 25.0900001525879 | 25.1000003814697 | 25.8799991607666 | 28.4300003051758 | 29.4200000762939 | 30.3799991607666 | 31.2600002288818 | .. | .. |
1587 | Vietnam | VNM | Employment in services (% of total employment) (modeled ILO estimate) | SL.SRV.EMPL.ZS | 22.0400009155273 | 23.6499996185303 | 23.0200004577637 | 22.3099994659424 | 22.1100006103516 | 23.2600002288818 | 23.9099998474121 | 24.75 | 26.4400005340576 | 28.1499996185303 | 30.3299999237061 | 30.3799991607666 | 30.6000003814697 | 29.6100006103516 | 30.4099998474121 | 31.4400005340576 | 32 | 32.2200012207031 | 33.2400016784668 | 33.3699989318848 | 34.0699996948242 | 34.6599998474121 | 35.3400001525879 | .. | .. |
1588 | Vietnam | VNM | Employment in services, female (% of female employment) (modeled ILO estimate) | SL.SRV.EMPL.FE.ZS | 23.5799999237061 | 25.2700004577637 | 24.7099990844727 | 23.6000003814697 | 23.8899993896484 | 25.1700000762939 | 25.3199996948242 | 26.2800006866455 | 28.2600002288818 | 30.3199996948242 | 32.439998626709 | 32.5999984741211 | 33.0099983215332 | 31.5599994659424 | 32.4900016784668 | 33.6599998474121 | 34.2599983215332 | 34.3800010681152 | 35.2400016784668 | 35.75 | 36.7200012207031 | 37.5400009155273 | 38.4199981689453 | .. | .. |
1589 | Vietnam | VNM | Employment in services, male (% of male employment) (modeled ILO estimate) | SL.SRV.EMPL.MA.ZS | 20.5799999237061 | 22.1299991607666 | 21.4400005340576 | 21.0900001525879 | 20.4699993133545 | 21.4899997711182 | 22.6100006103516 | 23.3400001525879 | 24.7399997711182 | 26.1399993896484 | 28.3700008392334 | 28.3199996948242 | 28.3700008392334 | 27.8400001525879 | 28.5 | 29.3999996185303 | 29.9200000762939 | 30.2199993133545 | 31.4099998474121 | 31.2000007629395 | 31.6299991607666 | 32.0200004577637 | 32.5099983215332 | .. | .. |
1590 | Vietnam | VNM | Employment to population ratio, 15+, female (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.FE.ZS | 68.9079971313477 | 68.6880035400391 | 68.6460037231445 | 67.2740020751953 | 67.2249984741211 | 67.3820037841797 | 66.6370010375977 | 65.9130020141602 | 66.9960021972656 | 68.0419998168945 | 69.1110000610352 | 69.6849975585938 | 70.318000793457 | 70.754997253418 | 70.875 | 71.0449981689453 | 71.7710037231445 | 71.8310012817383 | 71.1949996948242 | 70.6790008544922 | 70.197998046875 | 69.6910018920898 | 68.9199981689453 | 67.6999969482422 | 68.1809997558594 |
1591 | Vietnam | VNM | Employment to population ratio, 15+, female (%) (national estimate) | SL.EMP.TOTL.SP.FE.NE.ZS | 69 | 68.8000030517578 | 68.6999969482422 | 67.4000015258789 | 67.3000030517578 | 67.4000015258789 | 66.6999969482422 | 65.9499969482422 | .. | .. | 69.1699981689453 | .. | 70.370002746582 | 70.8000030517578 | 70.9300003051758 | 71.0800018310547 | 71.8199996948242 | 71.8899993896484 | 71.2600021362305 | 70.7300033569336 | 70.2300033569336 | 69.7200012207031 | 69.3499984741211 | 66.1999969482422 | 66.6399993896484 |
1592 | Vietnam | VNM | Employment to population ratio, 15+, male (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.MA.ZS | 75.6119995117188 | 75.5210037231445 | 75.0989990234375 | 74.2369995117188 | 74.9400024414063 | 74.7259979248047 | 74.3079986572266 | 74.0429992675781 | 74.9779968261719 | 75.8529968261719 | 76.7330017089844 | 77.7799987792969 | 78.8720016479492 | 80.0709991455078 | 80.3170013427734 | 79.9309997558594 | 80.3939971923828 | 80.4670028686523 | 80.5199966430664 | 79.7750015258789 | 79.3830032348633 | 79.963996887207 | 79.1259994506836 | 78.427001953125 | 77.6620025634766 |
1593 | Vietnam | VNM | Employment to population ratio, 15+, male (%) (national estimate) | SL.EMP.TOTL.SP.MA.NE.ZS | 75.6999969482422 | 75.6999969482422 | 75.0999984741211 | 74.3000030517578 | 75.0999984741211 | 74.8000030517578 | 74.4000015258789 | 74.0899963378906 | .. | .. | 76.8000030517578 | .. | 78.9199981689453 | 80.120002746582 | 80.370002746582 | 79.9800033569336 | 80.4400024414063 | 80.5400009155273 | 80.5800018310547 | 79.8300018310547 | 79.4100036621094 | 80 | 79.5999984741211 | 77.5199966430664 | 75.879997253418 |
1594 | Vietnam | VNM | Employment to population ratio, 15+, total (%) (modeled ILO estimate) | SL.EMP.TOTL.SP.ZS | 72.1679992675781 | 72.0120010375977 | 71.7870025634766 | 70.6660003662109 | 70.9850006103516 | 70.9629974365234 | 70.379997253418 | 69.8820037841797 | 70.8949966430664 | 71.8610000610352 | 72.8410034179688 | 73.6500015258789 | 74.5110015869141 | 75.3249969482422 | 75.5070037841797 | 75.4049987792969 | 76.0029983520508 | 76.0690002441406 | 75.7720031738281 | 75.1439971923828 | 74.7060012817383 | 74.7330017089844 | 73.9290008544922 | 72.9649963378906 | 72.8349990844727 |
1595 | Vietnam | VNM | Employment to population ratio, 15+, total (%) (national estimate) | SL.EMP.TOTL.SP.NE.ZS | 72.1999969482422 | 72 | 71.8000030517578 | 70.6999969482422 | 71 | 70.9000015258789 | 70.4000015258789 | 69.879997253418 | .. | .. | 72.8399963378906 | .. | 74.5100021362305 | 75.3199996948242 | 75.5100021362305 | 75.4000015258789 | 76.0100021362305 | 76.0800018310547 | 75.7699966430664 | 75.1399993896484 | 74.6999969482422 | 74.7399978637695 | 74.3600006103516 | 71.7399978637695 | 71.1600036621094 |
1596 | Vietnam | VNM | Employment to population ratio, ages 15-24, female (%) (modeled ILO estimate) | SL.EMP.1524.SP.FE.ZS | 63.6160011291504 | 61.6650009155273 | 58.9440002441406 | 54.875 | 58.2859992980957 | 56.8390007019043 | 54.2649993896484 | 53.0069999694824 | 52.7709999084473 | 52.507999420166 | 52.2770004272461 | 53.8339996337891 | 55.4650001525879 | 53.9070014953613 | 51.2820014953613 | 50.2639999389648 | 52.056999206543 | 52.3089981079102 | 51.9160003662109 | 49.976001739502 | 49.367000579834 | 49.6129989624023 | 47.382999420166 | 45.5349998474121 | 46.2389984130859 |
1597 | Vietnam | VNM | Employment to population ratio, ages 15-24, female (%) (national estimate) | SL.EMP.1524.SP.FE.NE.ZS | .. | .. | .. | .. | .. | .. | .. | 52.689998626709 | .. | .. | 51.5 | .. | 54.9700012207031 | 53.4500007629395 | 50.5099983215332 | 49.2099990844727 | 50.9500007629395 | 51.2099990844727 | 51.2400016784668 | 49.3600006103516 | 48.9700012207031 | 49.3499984741211 | 51.1599998474121 | 46.0499992370605 | 40.2799987792969 |
1598 | Vietnam | VNM | Employment to population ratio, ages 15-24, male (%) (modeled ILO estimate) | SL.EMP.1524.SP.MA.ZS | 61.0359992980957 | 59.1440010070801 | 55.9809989929199 | 52.3009986877441 | 56.617000579834 | 55.7060012817383 | 54.6790008544922 | 54.4029998779297 | 54.3310012817383 | 54.2000007629395 | 54.0979995727539 | 56.6209983825684 | 59.2120018005371 | 59.2070007324219 | 58.9269981384277 | 57.1769981384277 | 58.9959983825684 | 58.7150001525879 | 59.1290016174316 | 56.2360000610352 | 55.9259986877441 | 56.1450004577637 | 54.2330017089844 | 53.4379997253418 | 52.7809982299805 |
1599 | Vietnam | VNM | Employment to population ratio, ages 15-24, male (%) (national estimate) | SL.EMP.1524.SP.MA.NE.ZS | .. | .. | .. | .. | .. | .. | .. | 54.3400001525879 | .. | .. | 53.310001373291 | .. | 58.4900016784668 | 58.5900001525879 | 58.1100006103516 | 56.2200012207031 | 58.0299987792969 | 57.7299995422363 | 58.5099983215332 | 55.5999984741211 | 55.5499992370605 | 55.6199989318848 | 56.6599998474121 | 52.2400016784668 | 44.5400009155273 |
1600 | Vietnam | VNM | Employment to population ratio, ages 15-24, total (%) (modeled ILO estimate) | SL.EMP.1524.SP.ZS | 62.3050003051758 | 60.382999420166 | 57.4360008239746 | 53.5639991760254 | 57.4360008239746 | 56.2620010375977 | 54.476001739502 | 53.7200012207031 | 53.568000793457 | 53.3720016479492 | 53.2080001831055 | 55.2589988708496 | 57.3819999694824 | 56.6199989318848 | 55.1969985961914 | 53.8050003051758 | 55.6129989624023 | 55.5929985046387 | 55.6160011291504 | 53.1889991760254 | 52.734001159668 | 52.9690017700195 | 50.9070014953613 | 49.6080017089844 | 49.6160011291504 |
1601 | Vietnam | VNM | Employment to population ratio, ages 15-24, total (%) (national estimate) | SL.EMP.1524.SP.NE.ZS | .. | .. | .. | .. | .. | .. | .. | 53.5499992370605 | .. | .. | 52.4300003051758 | .. | 56.7400016784668 | 56.060001373291 | 54.4099998474121 | 52.8600006103516 | 54.6500015258789 | 54.5900001525879 | 54.9799995422363 | 52.5499992370605 | 52.3499984741211 | 52.5 | 54.0200004577637 | 49.25 | 42.4799995422363 |
1602 | Vietnam | VNM | Exports of goods and services (annual % growth) | NE.EXP.GNFS.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1603 | Vietnam | VNM | Exports of goods and services (constant 2015 US$) | NE.EXP.GNFS.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1604 | Vietnam | VNM | External health expenditure (% of current health expenditure) | SH.XPD.EHEX.CH.ZS | .. | .. | .. | 4.24706507 | 3.92210269 | 4.69086123 | 4.8854022 | 5.50130939 | 4.00909662 | 4.00868273 | 3.59759212 | 2.20431662 | 2.45537496 | 2.24441743 | 2.35883379 | 2.42122793 | 2.23614025 | 3.19134188 | 2.16096139 | 2.29792619 | 1.08494616 | 1.01668346 | 0.97050571 | .. | .. |
1605 | Vietnam | VNM | External health expenditure per capita (current US$) | SH.XPD.EHEX.PC.CD | .. | .. | .. | 0.80340642 | 0.90945037 | 0.92203293 | 1.09292419 | 1.58130656 | 1.40468477 | 1.69540496 | 1.78111402 | 1.30429115 | 1.58216323 | 1.76491001 | 2.11316423 | 2.63768493 | 2.67267802 | 3.74710137 | 2.54697145 | 2.85079388 | 1.52071842 | 1.65872883 | 1.75388049 | .. | .. |
1606 | Vietnam | VNM | External health expenditure per capita, PPP (current international $) | SH.XPD.EHEX.PP.CD | .. | .. | .. | 4.09288255 | 4.79527705 | 4.89444577 | 5.60016725 | 7.79061877 | 6.04929481 | 6.98765966 | 6.92360593 | 4.26496029 | 5.13762619 | 5.64241612 | 6.26729828 | 7.6653087 | 7.59146289 | 10.60340589 | 7.4544302 | 8.54776839 | 4.60000611 | 5.02232967 | 5.42389473 | .. | .. |
1607 | Vietnam | VNM | Female share of employment in senior and middle management (%) | SL.EMP.SMGT.FE.ZS | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 16.2999992370605 | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 20.1000003814697 |
1608 | Vietnam | VNM | Final consumption expenditure (annual % growth) | NE.CON.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1609 | Vietnam | VNM | Final consumption expenditure (constant 2015 US$) | NE.CON.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1610 | Vietnam | VNM | GDP (constant 2015 US$) | NY.GDP.MKTP.KD | 79042755277.69421 | 83599139703.15303 | 87589817268.2927 | 93534815307.67822 | 99327326629.08156 | 105605629137.18712 | 112891428542.21062 | 121399390142.70738 | 130561702856.11649 | 139672239482.9771 | 149630178059.7694 | 158101896399.67126 | 166636074780.50104 | 177339506819.39932 | 188706969206.52283 | 199085852512.88156 | 210135117327.34973 | 223625791859.75934 | 239257234710.75732 | 255263543712.9125 | 272978833646.58673 | 292633309669.1421 | 313556591310.4859 | 322775155095.00836 | 331131560170.1764 |
1611 | Vietnam | VNM | GDP growth (annual %) | NY.GDP.MKTP.KD.ZG | 8.152084143301636 | 5.7644554639463905 | 4.773586880570676 | 6.7873164082254505 | 6.192893311810323 | 6.320820987713333 | 6.899063491737607 | 7.536410611825687 | 7.547247727223862 | 6.977954811833882 | 7.129504483964368 | 5.661771208023183 | 5.397897542769471 | 6.423238217173093 | 6.410000000000011 | 5.5 | 5.550000000001631 | 6.419999999997032 | 6.990000000000364 | 6.6900000000023 | 6.939999999999259 | 7.200000000000429 | 7.1500000000000625 | 2.9399999999981503 | 2.5889245015491724 |
1612 | Vietnam | VNM | GDP per capita (constant 2015 US$) | NY.GDP.PCAP.KD | 1024.756434072708 | 1070.1962199762454 | 1108.228658203725 | 1170.4959859069957 | 1230.1740301462248 | 1295.2277979088622 | 1371.6788003911297 | 1461.537082466553 | 1557.4085295790378 | 1650.6297775830901 | 1751.7080281371693 | 1833.2052354469515 | 1913.3283935195273 | 2015.9626492191853 | 2123.371559134522 | 2216.9441278228437 | 2315.47232294894 | 2438.29903400369 | 2581.6224415736065 | 2725.9969874436456 | 2885.591735846729 | 3062.749201869878 | 3250.567479931974 | 3316.004251828983 | 3373.0825104389946 |
1613 | Vietnam | VNM | GDP per capita growth (annual %) | NY.GDP.PCAP.KD.ZG | 6.659536763526063 | 4.434203523167454 | 3.5537817754882184 | 5.6186354000442975 | 5.098526176745992 | 5.288175995302453 | 5.902514029246191 | 6.550971120192344 | 6.559631518256651 | 5.985664405552569 | 6.12361729606512 | 4.6524424162426925 | 4.3706594615436245 | 5.364173554695697 | 5.327921623792875 | 4.406792032500519 | 4.4443246850273965 | 5.3046071783021915 | 5.878007806720049 | 5.592395833917394 | 5.854546029881959 | 6.139380835562491 | 6.132342731407107 | 2.013087631651885 | 1.7212963034811963 |
1614 | Vietnam | VNM | GDP per capita, PPP (constant 2017 international $) | NY.GDP.PCAP.PP.KD | 3194.8720361594883 | 3336.5391645475647 | 3455.112485309283 | 3649.2426585202206 | 3835.3002507178558 | 4038.1176779240927 | 4276.468140381033 | 4556.618333221621 | 4855.515705574287 | 5146.150580868863 | 5461.281147920504 | 5715.364108516623 | 5965.163210687174 | 6285.144918129291 | 6620.0125133090205 | 6911.742697296059 | 7218.922984157567 | 7601.858490971296 | 8048.6963265264 | 8498.811284575726 | 8996.378103224013 | 9548.70001638809 | 10134.259027786931 | 10338.270542834875 | 10516.222811532576 |
1615 | Vietnam | VNM | GDP per capita, PPP (current international $) | NY.GDP.PCAP.PP.CD | 2106.809038612602 | 2224.993547684418 | 2336.534601075478 | 2523.725508328889 | 2712.155584379781 | 2900.0842422622154 | 3131.8765297715418 | 3426.6247572408065 | 3765.900154500675 | 4114.46961237354 | 4484.427753507313 | 4783.072978692322 | 5024.122070621181 | 5357.243036390215 | 5759.911338058719 | 6329.555554199924 | 6688.774305485697 | 7202.924214749318 | 7555.845810877604 | 8232.25409438726 | 8996.378103224013 | 9776.819499921392 | 10561.97127588917 | 10904.452145544894 | 11553.069924366397 |
1616 | Vietnam | VNM | GDP per person employed (constant 2017 PPP $) | SL.GDP.PCAP.EM.KD | 6724.784829718157 | 6947.170083142797 | 7122.128648747991 | 7546.906068671305 | 7775.713256277521 | 8086.442983837558 | 8537.859739384776 | 9056.258423466343 | 9395.184158426073 | 9727.902617758637 | 10075.823818492088 | 10318.51063299028 | 10550.687360861708 | 10925.397630757969 | 11434.231475226597 | 11924.59195286178 | 12342.601000669738 | 12982.029412077805 | 13800.484343615422 | 14695.410597873346 | 15659.288896491245 | 16630.91410155958 | 17852.298690633663 | 18447.53694388192 | 18792.415605649934 |
1617 | Vietnam | VNM | GDP, PPP (constant 2017 international $) | NY.GDP.MKTP.PP.KD | 246430742077.9615 | 260636132454.5182 | 273077824679.39386 | 291612480681.0835 | 309671730493.5865 | 329245526227.6402 | 351960384125.79065 | 378485563864.4692 | 407050806981.1007 | 435454628353.4471 | 466500385607.5365 | 492912570125.1811 | 519519485635.97003 | 552889459783.0007 | 588329674155.0911 | 620687806233.6211 | 655135979479.5972 | 697195709362.1678 | 745929689446.5859 | 795832385670.5797 | 851063153236.112 | 912339700269.1157 | 977571988838.358 | 1006312605310.1875 | 1032365278911.2407 |
1618 | Vietnam | VNM | GDP, PPP (current international $) | NY.GDP.MKTP.PP.CD | 162504948218.82202 | 173806955172.77426 | 184670047317.63794 | 201671942621.74545 | 218986222271.78445 | 236456646042.80984 | 257758605996.47202 | 284625111991.61206 | 315705434778.00287 | 348156317576.15063 | 383057971120.3603 | 412508590924.3049 | 437562095405.05756 | 471264107176.3269 | 511891292330.5702 | 568406279491.1505 | 607023612214.6012 | 660607910992.8867 | 700253741794.0602 | 770871854428.954 | 851063153236.112 | 934135595089.8898 | 1018830013907.7188 | 1061423920238.6497 | 1134151345830.1677 |
1619 | Vietnam | VNM | General government final consumption expenditure (annual % growth) | NE.CON.GOVT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1620 | Vietnam | VNM | General government final consumption expenditure (constant 2015 US$) | NE.CON.GOVT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1621 | Vietnam | VNM | Gini index | SI.POV.GINI | 35.4 | .. | .. | .. | .. | 37 | .. | 36.8 | .. | 35.8 | .. | 35.6 | .. | 39.3 | .. | 35.6 | .. | 34.8 | .. | 35.3 | .. | 35.7 | .. | .. | .. |
1622 | Vietnam | VNM | GNI (constant 2015 US$) | NY.GNP.MKTP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 227117625051.7483 | .. | .. | .. | .. | .. | .. |
1623 | Vietnam | VNM | GNI growth (annual %) | NY.GNP.MKTP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1624 | Vietnam | VNM | GNI per capita (constant 2015 US$) | NY.GNP.PCAP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 2450.6341821567958 | .. | .. | .. | .. | .. | .. |
1625 | Vietnam | VNM | GNI per capita growth (annual %) | NY.GNP.PCAP.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1626 | Vietnam | VNM | GNI per capita, Atlas method (current US$) | NY.GNP.PCAP.CD | 330 | 340 | 350 | 380 | 400 | 420 | 460 | 530 | 630 | 720 | 840 | 980 | 1110 | 1360 | 1610 | 1970 | 2190 | 2380 | 2460 | 2570 | 2700 | 3030 | 3280 | 3390 | 3560 |
1627 | Vietnam | VNM | GNI per capita, PPP (constant 2017 international $) | NY.GNP.PCAP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 8452.92762659652 | .. | .. | .. | .. |
1628 | Vietnam | VNM | GNI per capita, PPP (current international $) | NY.GNP.PCAP.PP.CD | 2080 | 2190 | 2300 | 2500 | 2680 | 2860 | 3090 | 3380 | 3710 | 4040 | 4390 | 4670 | 4850 | 5200 | 5560 | 6130 | 6460 | 6930 | 7170 | 7780 | 8450 | 9280 | 10020 | 10410 | 11040 |
1629 | Vietnam | VNM | GNI, Atlas method (current US$) | NY.GNP.ATLS.CD | 25824451835.992306 | 26759132282.297726 | 27962757382.14431 | 30203568807.801342 | 32186355227.626743 | 34037168505.051006 | 38120159465.099655 | 44415418929.92248 | 52884327653.60776 | 61119346852.98477 | 71581154220.60484 | 84934003165.45354 | 96710386688.10202 | 119609653004.27972 | 143347738257.03696 | 176756624830.77814 | 198876403902.1552 | 218736555384.62076 | 228402526065.42444 | 240488084750.5525 | 255478639060.5367 | 289797229428.3562 | 316877790597.8615 | 329909670241.7276 | 349343920489.7716 |
1630 | Vietnam | VNM | GNI, PPP (constant 2017 international $) | NY.GNP.MKTP.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | 799652388708.4948 | .. | .. | .. | .. |
1631 | Vietnam | VNM | GNI, PPP (current international $) | NY.GNP.MKTP.PP.CD | 160455108868.82788 | 170704940454.92365 | 182033864597.0576 | 199396494294.43692 | 216678469549.7092 | 233430455681.3067 | 254530378027.60434 | 280425434801.16693 | 311140869479.81635 | 342264477678.0185 | 374597682837.04926 | 402842107077.82166 | 422717893590.6781 | 457125151920.5075 | 494567476171.5819 | 550239826157.7155 | 586182065656.6821 | 635585897754.9548 | 664723752082.7053 | 728469391535.0537 | 799652388708.4948 | 886259355168.4095 | 967029632928.5355 | 1013136799979.7418 | 1084230081276.1854 |
1632 | Vietnam | VNM | Gross capital formation (annual % growth) | NE.GDI.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1633 | Vietnam | VNM | Gross capital formation (constant 2015 US$) | NE.GDI.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1634 | Vietnam | VNM | Gross fixed capital formation (annual % growth) | NE.GDI.FTOT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1635 | Vietnam | VNM | Gross fixed capital formation (constant 2015 US$) | NE.GDI.FTOT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1636 | Vietnam | VNM | Gross national expenditure (constant 2015 US$) | NE.DAB.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1637 | Vietnam | VNM | Gross value added at basic prices (GVA) (constant 2015 US$) | NY.GDP.FCST.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1638 | Vietnam | VNM | Hospital beds (per 1,000 people) | SH.MED.BEDS.ZS | 1.6699999571 | .. | .. | 2.34 | 2.4000000954 | 1.4 | .. | 2.8 | 2.34 | 2.66 | .. | 2.9 | 3.1 | 2.91 | .. | 2.5 | 3.18 | 2.6 | .. | .. | .. | .. | .. | .. | .. |
1639 | Vietnam | VNM | Households and NPISHs Final consumption expenditure (annual % growth) | NE.CON.PRVT.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1640 | Vietnam | VNM | Households and NPISHs Final consumption expenditure (constant 2015 US$) | NE.CON.PRVT.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1641 | Vietnam | VNM | Households and NPISHs Final consumption expenditure per capita (constant 2015 US$) | NE.CON.PRVT.PC.KD | 590.1373667464828 | 608.7337333361097 | 617.2652550533218 | 629.2899379309687 | 650.6538360019798 | 693.4834371404016 | 742.0533182350437 | 787.414161767874 | 836.8139784049055 | 890.9471850222609 | 968.8947394586129 | 1033.2285278376748 | 1046.2005068051856 | 1120.5813634019078 | 1154.6289956594862 | 1198.417792461926 | 1247.2918618837139 | 1309.753263525246 | 1417.0701774433483 | 1504.8736007023901 | 1599.0845857719482 | 1698.2082803181106 | 1805.8806620156204 | 1799.999310551725 | .. |
1642 | Vietnam | VNM | Households and NPISHs Final consumption expenditure per capita growth (annual %) | NE.CON.PRVT.PC.KD.ZG | 4.4495191232407905 | 3.1511928641549076 | 1.401519457523051 | 1.948057626637052 | 3.394921288786719 | 6.582548010720018 | 7.003755027650158 | 6.112881974669975 | 6.273676425392296 | 6.468965387091345 | 8.748841204813317 | 6.63991512793325 | 1.255480139970416 | 7.109617717913494 | 3.0383900151806245 | 3.792456015486522 | 4.078216272255531 | 5.00776149915707 | 8.193674099292195 | 6.196123851639811 | 6.26039190438226 | 6.198777439800722 | 6.340351943010219 | -0.3256777475722572 | .. |
1643 | Vietnam | VNM | Households and NPISHs Final consumption expenditure, PPP (constant 2017 international $) | NE.CON.PRVT.PP.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1644 | Vietnam | VNM | Households and NPISHs Final consumption expenditure, PPP (current international $) | NE.CON.PRVT.PP.CD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1645 | Vietnam | VNM | Imports of goods and services (annual % growth) | NE.IMP.GNFS.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1646 | Vietnam | VNM | Imports of goods and services (constant 2015 US$) | NE.IMP.GNFS.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1647 | Vietnam | VNM | Income share held by fourth 20% | SI.DST.04TH.20 | 21 | .. | .. | .. | .. | 21.1 | .. | 21.8 | .. | 22.3 | .. | 21.8 | .. | 21.4 | .. | 22.2 | .. | 22.4 | .. | 22.4 | .. | 22.3 | .. | .. | .. |
1648 | Vietnam | VNM | Income share held by highest 10% | SI.DST.10TH.10 | 29.1 | .. | .. | .. | .. | 29.8 | .. | 28.8 | .. | 27.7 | .. | 28 | .. | 30.9 | .. | 27.7 | .. | 26.8 | .. | 27.1 | .. | 27.5 | .. | .. | .. |
1649 | Vietnam | VNM | Income share held by highest 20% | SI.DST.05TH.20 | 44.2 | .. | .. | .. | .. | 45.4 | .. | 44.5 | .. | 43.3 | .. | 43.5 | .. | 46.3 | .. | 43 | .. | 42.2 | .. | 42.5 | .. | 42.9 | .. | .. | .. |
1650 | Vietnam | VNM | Income share held by lowest 10% | SI.DST.FRST.10 | 3.3 | .. | .. | .. | .. | 3.2 | .. | 2.9 | .. | 2.9 | .. | 3 | .. | 2.5 | .. | 2.8 | .. | 2.7 | .. | 2.6 | .. | 2.5 | .. | .. | .. |
1651 | Vietnam | VNM | Income share held by lowest 20% | SI.DST.FRST.20 | 8 | .. | .. | .. | .. | 7.5 | .. | 7.2 | .. | 7.2 | .. | 7.4 | .. | 6.5 | .. | 7.1 | .. | 7.1 | .. | 6.9 | .. | 6.7 | .. | .. | .. |
1652 | Vietnam | VNM | Income share held by second 20% | SI.DST.02ND.20 | 11.7 | .. | .. | .. | .. | 11.2 | .. | 11.3 | .. | 11.5 | .. | 11.6 | .. | 10.8 | .. | 11.6 | .. | 12 | .. | 11.9 | .. | 11.9 | .. | .. | .. |
1653 | Vietnam | VNM | Income share held by third 20% | SI.DST.03RD.20 | 15.2 | .. | .. | .. | .. | 14.8 | .. | 15.3 | .. | 15.8 | .. | 15.7 | .. | 15 | .. | 16.1 | .. | 16.4 | .. | 16.3 | .. | 16.3 | .. | .. | .. |
1654 | Vietnam | VNM | Industry (including construction), value added (annual % growth) | NV.IND.TOTL.KD.ZG | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1655 | Vietnam | VNM | Industry (including construction), value added (constant 2015 US$) | NV.IND.TOTL.KD | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. | .. |
1656 | Vietnam | VNM | Industry (including construction), value added per worker (constant 2015 US$) | NV.IND.EMPL.KD | 4229.316083035133 | 4863.778540053114 | 4938.03430733128 | 5119.15640927316 | 4876.427314017197 | 4807.596402124056 | 4624.843052161006 | 4710.726405345075 | 4633.55017082853 | 4529.956001997673 | 4724.05891124709 | 4673.255607783518 | 4669.807675740685 | 4126.950448494001 | 4441.604217467813 | 4716.3246299552975 | 4853.051178108873 | 5030.369944804254 | 5177.126382512189 | 5091.2962055097005 | 5225.452944222844 | 5411.286600026288 | 5744.824180426878 | .. | .. |
1657 | Vietnam | VNM | International migrant stock (% of population) | SM.POP.TOTL.ZS | .. | .. | .. | 0.070690168791617 | .. | .. | .. | .. | 0.0614793982557822 | .. | .. | .. | .. | 0.0698931135375467 | .. | .. | .. | .. | 0.07789713082094 | .. | .. | .. | .. | .. | .. |
1658 | Vietnam | VNM | International migrant stock, total | SM.POP.TOTL | .. | .. | .. | 56754 | .. | .. | .. | .. | 51768 | .. | .. | .. | .. | 61756 | .. | .. | .. | .. | 72793 | .. | .. | .. | .. | .. | .. |