105 lines
7 KiB
Markdown
105 lines
7 KiB
Markdown
### [ ] Canagarajah2001
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* looks at distribution of earnings in rural Uganda (& Ghana) by income type and gender
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* results:
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* non-farm earnings contribute to rising inequality
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* but lower income groups benefit through strong overall growth in non-farm earnings
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* inequality is induced through self-employment; wage employment reduces inequality
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* determinants of non-farm income: location, education, age, distance to market
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* gender:
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* self-employment increased inequality among women, wage-work reduced inequality
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* self-employment was mixed among men, wage-work increased inequality
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* may show men being employed in wider variety of not just low-income waged jobs
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### [ ] Jagger2012
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* looks at income inequality in Uganda and how income from forests and other wild areas relates to it
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* wild areas: fallows, agricultural lands, wetlands, grasslands, shrub land; most important: forests, fallows, agricultural lands
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* income from forest and wild products plays important role in reducing income inequality between households
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* deforestation, environmental degradation and thus loss of income important implications for rural livelihoods
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### [x] Ssewanyana2012
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* looks at households in poverty and examines drivers of income inequality
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* poverty:
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* nearly 10% of households continue to live in persistent or chronic poverty
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* significant differences across geographical areas (significantly reduced in Northern/Easter, rural areas)
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* clear increase in poverty in Western households (but insignificant)
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* absolute terms: people in poverty fell significantly 28.5% (05/06) to 23.9% (09/10)
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* rural households make up 94.3% of chronically poor HHs
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* transient poverty more common than chronic poverty (25.6% HHs slipped into or out of poverty)
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### [x] Lwanga-Ntale2014
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* looks at inequality numbers in Uganda long-term (1992-2013)
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* degree of inequality somewhat variable, mostly on increase
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* top 10 percentile earned 2.3 times more than bottom 40% (2009)
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* poverty line set very low, so existing figures of mask a lot of poverty dynamics and characteristics (and 'extent of deprivation')
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* consumption distribution very flat, many households presumed escaped poverty still high level of vulnerability
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* structural factors ('drivers') and economic 'maintainers' provide complex mix
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* structural and deeply rooted inequalities in basic set-up of Ugandan society, including way of asset distribution and social relation mediation
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* creates further exclusion, marginalization, pronounced inequality
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* enduring legacy of unequal power relations in gender, ethnicity, language, religion, age, cultural groups, disability status
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* 'maintainers' and 'aggravating' factors of inequality are contemporary and dynamic
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* persistent poverty not just reflectino of lack of 'sufficient' economic growth
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* unequal growth itself is cause for grouting inequality
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* responses to inequality need to include more inclusive growth path
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* Gini: [604]
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* Uganda: 0.36 (92/93), 0.40 (99/00), 0.43 (02/03), 0.41 (05/06), 0.43 (09/10), 0.39 (12/13)
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* significant increases in 02/03 and 09/10
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* rural: 0.33 (92/93), 0.33 (99/00), 0.36 (02/03), 0.36 (05/06), 0.37 (09/10), 0.35 (12/13)
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* urban: 0.40 (92/93), 0.43 (99/00), 0.48 (02/03), 0.43 (05/06), 0.45 (09/10), 0.41 (12/13)
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* also contains western and western rural/urban breakdown & quintiles
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* 1st quintile: 0.14 (92/93), 0.15 (99/00), 0.14 (02/03), 0.13 (05/06), 0.14 (09/10), 0.14 (12/13)
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* 2nd quintile: 0.06 (92/93), 0.07 (99/00), 0.06 (02/03), 0.06 (05/06), 0.06 (09/10), 0.06 (12/13)
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* other indicators
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* welfare of average rural household 83% of national average
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* avg urban household 1.9 times more welfare than rural (09/10), 1.6 (12/13)
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* poverty 24.5% (09/10), 20.3% (12/13) - income growth may have been pro-poor with lower income distributions having larger increases
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* Central and Western Uganda major drivers for reduced inequality 09->13
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* relative mean of expenditure (mean expenditure relative to Uganda average)
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### [x] vandeVen2021
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* looks at 3 case studies (Isingiro; Tanzania and Ethiopia) to establish living income (US$PPP/Adult Equivalent/day)
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* finds that around 3.82 US$ PPP should constitute living income, thus also poverty line to meet basic human rights for a decent living
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* current national poverty line set at between 0.94$PPP and 1.07$PPP depending on region, even below international 1.90$PPP [@WorldBank2016]
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### [x] Esaku2021
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* looks at effects of shadow economy on income inequality (short-/long-run) 1992-2015
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* Gini coeff: 43.9 (mean 91-2015); 43.9 (median); 43.0 (min); 44.4 (max)
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* results:
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* long-term large shadow economy significantly increases income inequality
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* people who fail to get into formal economy face fewer livelihood opportunities, using 'shadow economy' as means of survival
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### [x] Esaku2021a
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* looks at effects of income inequality on shadow economy (short-/long-run) 1991-2017
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* increase in income inequality significantly increases size of shadow economy, both short- and long-run
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* large subsistence sector creates revenue tax shortfall, undermining government's efforts to attain equitable income distribution in economy and prevent creation of social safety nets for poor
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* poor will be forced to operate in informal sector
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### [x] Atamanov2022
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* looks at Uganda inequality and poverty
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* poverty:
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* share of people below poverty line fluctuated but at level of 12/13 - ~30% (19/20)
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* fluctuations driven largely by rural households: surge in poverty 2012/13 and 16/17 (linked to drought 16/17)
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* improvement 19/20 (prior to pandemic, favorable weather cond)
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* pandemic pushed both urban and rural residents into poverty
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* drivers/patterns remain largely unchanged:
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* low-productivity agriculture (prod increase 17 due to weather not production practices)
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* slow structural change negatively affected by COVID, many ppl returned to agriculture following job losses/small business closure
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* working in agriculture and lack of education strongest predictors of high poverty
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* poverty rate in HHs with uneducated heads ~48% (19/20) (17% of all heads); with heads primary education 25.% (also 17% of all)
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* education level differences also one of biggest endowment factors accounting for urban-rural consumption gap
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* inequality:
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* largely unchanged between 12/13-19/20
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* shift out of agricultural sector mainly taking place amongst men, older individuals, those with at least some level of formal education, those from more well-off households
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* HHs income generation strategies impacted by resilience capabilities as reported frequency of extreme weather shocks increased
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* water access
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* general access to improved drinking water 87% urban, 74% rural (19/20);
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with only small amounts of inequality (75/74 rural poor/nonpoor; 76/90 poor/nonpoor)
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* but very little access to improved sanitation 39% urban, 25% urban; 19% rural poor, 29% nonpoor; 22% urban poor, 43% urban nonpoor
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