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 # Older study - Morabito, Negre, Niño-Zarazúa: The distributional impacts of development cooperation projects
 ## RQs
 * Are the projects primarily helping reduce inequality in Benin, Djibouti-Ethiopia, Uganda, Vietnam?
    * reducing inequality = affecting the bottom 40% of wealth distribution
    * are they explicitly targeting a reduction of inequality?
    * are the bottom 40% the direct beneficiaries of the programme?
 * is the method of scoreboard and equity tool combined effective for establishing this?
 ## Methodology
 2 sides:
 * explicit targeting:
    * Inequality Markers/Scoreboard assessing whether inequality reduction is central objective
 * primary beneficiaries:
    * Equity Tool to estimate distributional impact of measures
 * in-depth:
    * assessment of explicit aims of project to benefit lower part of wealth distribution (qualitative)
    * for budget support/support for government spending assessment of disproportional effects for bottom 40% of income distribution
    * geographical allocation assessment analyzes direction of benefits to areas with high proportion of households at bottom of income distribution
    * willingness of programme/project to address inequality as goal through associated documentation for project/agency's country strategy
 * advantages of methodology:
    * allows possibility to obtain relevant information within limited budget/timeframe
    * can be implemented ex-ante at baseline or ex-post at end line of policy interventions
 # New Study - Inequality in Vietnam, Uganda, Benin, Ethiopia-Djibouti
 ## What I do (TOR)
 1. Review of project documents for context familiarization
 2. Review of recent literature on level and drivers of inequalities in each country case study:
    * focus on income inequality (bases on bottom 40% wealth distribution, Gini coefficient, other inequality meaures)
    * policy areas of AFD development interventions (e.g. inequalities in access to safe drinking water in Uganda)
 3. Descriptive analysis of composition and trends of development assistance to sector of interest in recipient country by:
    * by type of finance (does this overlap with OECD DAC type of aid?)
    * cooperation modality
    * type of donor
   based on OECD DAC (Development Assistance Committee) CRS (Creditor Reporting System) dataset and DAC CRS codes
 ## What I do (detailed steps)
 1. analysis of inequality levels in country, and primary drivers:
    * Gini coefficients over time
    * Povcalnet (poverty headcounts)
    * + primary drivers from literature on country inequality
 2. analysis of donor/national plans:
    * inequality reduction contained in objective of AFD / EU interventions
    * assessment with scorecard built from indicators from Robilliard and Lawson (2017)
    * how well are inequality drivers assessed for country/sectors
 3. analysis of potential inequality reducing effects:
    * a. of programmes/projects:
        * provide first order assessment of potential effects on inequality no accounting for indirect/general equilibrium effects
        * see if more than 40% of beneficiaries are below 40% of income/wealth distribution - likely to have reducing effect
        * use equity tool to see beneficiaries' wealth distribution
    * b. of budget support operations:
        * incidence analysis of government expenditure to identify extent of benefiting bottom 40% of income distribution
        * 'Commitment to Equity (CEQ)' assessment tools and Standard indicators
        * Gini coefficients broken down into market income/disposable and final incomes as well as their pre-/post-distribution
 ## Projects
 * Vietnam [AFD](https://www.afd.fr/en/page-region-pays/vietnam)
    * Loans:
        * Improving Electricity Interconnection - Powerline construction loan [here](https://www.afd.fr/en/carte-des-projets/improving-electricity-interconnection-vietnam)
        * Drainage, Irrigation Improvement project - Irrigation area construction loan/expertise [here](https://www.afd.fr/en/carte-des-projets/improving-electricity-interconnection-vietnam)
 * Uganda
    * Loans:
        * Electricity Substation Construction Aid [here](https://www.afd.fr/en/carte-des-projets/high-voltage-line-and-its-associated-substations-improve-access-electricity-west)
        * Electrification Network Grid Extensions [here](https://www.afd.fr/en/carte-des-projets/extending-rural-electrification-grid-order-boost-economic-dynamism-west-regions)
        * Drinking water access improvement [here](https://www.afd.fr/en/carte-des-projets/improving-access-drinking-water-and-sanitation-kampala)
        * ASToN Smart Town technical expertise provision [here](https://www.afd.fr/en/carte-des-projets/aston-financing-african-smart-towns-network-making-digital-transition)
        * Creative Entrepreneurship Support Grant [here](https://www.afd.fr/en/carte-des-projets/afrique-creative-promoting-creative-entrepreneurship-africa)
 * Ethiopia-Djibouti
 * Benin
 ## Resources
 * Sector classification: https://www.oecd.org/dac/financing-sustainable-development/development-finance-standards/purposecodessectorclassification.htm
 * Type of finance (e.g. budget support, project-type interventions): https://www.oecd.org/dac/financing-sustainable-development/development-finance-standards/type-aid.htm
 * DAC CRS codes: https://www.oecd.org/development/financing-sustainable-development/development-finance-standards/dacandcrscodelists.htm
 * Global Picture development committee: https://www.oecd.org/dac/financing-sustainable-development/development-finance-data/
 * DAC CRS dataset: stats.oecd.org
 * Equity Tool: https://www.equitytool.org/
 * Commitment to Equity:
    * data access here - https://commitmentoequity.org/datacenter
    * visualizations with xls export here (ex Ethiopia) - https://commitmentoequity.org/datavisualization/country/ETH
 * WorldBank (poverty/inequality) indicators: (ex Eth) https://data.worldbank.org/country/ethiopia
 ## Questions
 1. How is the project selection going to go - e.g. there are already 8 AFD projects operating in Uganda - who picks and chooses?
    * Are the development programs/projects pre-selected?
 2. Do we already have a questionnaire conducted with EquityTool for the individual project-based development or is this something to be done after programme assessments?
 3. what is the general time plan for the project - when would analysis/writing be ideal
    * TOR states June to end of Sep - is this project period as well?
    * I can maybe devote a couple hours here/there in June but mostly to the end of June
    * only really begin with analysis come July
 4. When it says 'type of finance' in the analysis, is that the same facet as type of aid (meaning budget support, project-type intervention) or something different?
 ## Meeting
 Projects:
 * Uganda - AFD drinking access rural/poor
    * not just income/ Gini
    * unequality of water access
    * what are underpinning problems
 * Benin - electricity
    * how unequal is el distrib.
    * rural
 * Vietnam - water distribution/dam lock projects
    * how do floodings affect people unequally
    * water management inequality problems
    * infrastructure quality difference - per area etc
 * Djibouti-Eth - trade between countries
    * problems between conflict
    * may include it, may not - prepare for background anyways
 * results should be ~10 pg overviews overall (incl graphs tables)
    * use policy reports as inputs, e.g. gov doc / international policy reports on inequality
    * distribution within countries / esp within B40
 * ideally there will come info from AFD /other donors
 * look into tax exemption
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 # Background information
 An apology for getting back to you until now.
 I send attached some background information about the AFD projects in each of countries covered by the project. Please review these project documents to familiarize with the context.
 As you will see, each project focuses on addressing distinct constraints:
  Data Sources
 PovcalNet
 Provides country, regional, and global poverty and Gini estimates
 World Development Indicators
 Builds on PovcalNet and includes a large number of additional indicators from several sources
 World Bank’s Poverty and Shared Prosperity
 Reports for shared prosperity data premium (SDG10.1)
 World Bank’s Systemic Country Diagnostics
 Systematic Country Diagnostic (SCD) reports are prepared by World Bank Group staff in close consultation with national authorities and other stakeholders. They identify key challenges and opportunities for a country to accelerate progress towards development objectives that are consistent with the twin goals of ending absolute poverty and boosting shared prosperity in a sustainable manner.
 UNU-WIDER’s World Income Inequality Database (WIID)
 The World Income Inequality Database (WIID) presents information on income inequality for developed, developing, and transition countries. It provides the most comprehensive set of income inequality statistics available and can be downloaded for free. 
 World Inequality Database (WID)
 Provides information on top incomes shares for some countries
 National Development Plans, SDGs National Reports, and reports from National Statistical Agencies Offices
 Other rigorous distributional studies
 For inequalities in the policy areas of the development interventions, please conduct searches to identify the most recent information.
 As a third step, please conduct a descriptive analysis on the composition and trends of development assistance of the sectors of interest in the recipient country by type of finance, cooperation modality, and type of donor, based on the OECD DAC CRS dataset, and DAC CRS codes. The idea is to generate basic charts to show aid flows to support e.g., electrification in Benin, or the provision of drinking water in Uganda, who contributes and in what proportions, overtime.
 https://stats.oecd.org/Index.aspx?DataSetCode=crs1
 https://www.oecd.org/dac/financing-sustainable-development/development-finance-standards/dacandcrscodelists.htm
 The main goal is to produce individual reports for each country. Don’t worry about the length of number of pages. The important thing for us is to have good background sections discussing the levels and drivers of inequalities in income and relevant dimensions for each country.
 ## TODO
 * produce individual reports for each country
    * levels of inequality
    * drivers of inequality
 * in income and relevant dimensions for each country
 ### Literature review: Levels and drivers of inequality
 1. conduct review of most recent literature on level and drivers of inequalities in each country case study
 * focus on:
    * income inequality, based on bottom 40%, Gini coefficient, other inequality measures
    * inequality in policy areas of development interventions:
        * Uganda inequalities in access to safe drinking water
        * Benin inequalities in access to electricity
        * Vietnam varation in incidence of catastrophic weather events (e.g. floodings) and unequal impact of these events on households
        * Djibouti unequal distribution of benefits from trade
 ### Descriptive statistical analysis: Levels and drivers of inequality
 Descriptive statistical analysis of level and trends of inequalities in income and areas of interest
 based on secondary data sources, including:
 * PovcalNet
    Provides country, regional, and global poverty and Gini estimates
 * World Development Indicators
    Builds on PovcalNet and includes a large number of additional indicators from several sources
 * World Bank’s Poverty and Shared Prosperity
    Reports for shared prosperity data premium (SDG10.1)
 * World Bank’s Systemic Country Diagnostics
    Systematic Country Diagnostic (SCD) reports are prepared by World Bank Group staff in close consultation with national authorities and other stakeholders. They identify key challenges and opportunities for a country to accelerate progress towards development objectives that are consistent with the twin goals of ending absolute poverty and boosting shared prosperity in a sustainable manner.
 * UNU-WIDER’s World Income Inequality Database (WIID)
    The World Income Inequality Database (WIID) presents information on income inequality for developed, developing, and transition countries. It provides the most comprehensive set of income inequality statistics available and can be downloaded for free. 
 * World Inequality Database (WID)
    Provides information on top incomes shares for some countries
 * National Development Plans, SDGs National Reports, and reports from National Statistical Agencies Offices
 * Other rigorous distributional studies
 For inequalities in the policy areas of the development interventions, please conduct searches to identify the most recent information.
 ### Descriptive Analysis: Composition and trends of development assistance
 As a third step, please conduct a descriptive analysis on the composition and trends of development assistance of the sectors of interest in the recipient country by:
 * type of finance
 * cooperation modality
 * and type of donor
 based on the OECD DAC CRS dataset, and DAC CRS codes
 The idea is to generate basic charts to show aid flows to support e.g., electrification in Benin, or the provision of drinking water in Uganda, who contributes and in what proportions, overtime.
 * https://stats.oecd.org/Index.aspx?DataSetCode=crs1
 * https://www.oecd.org/dac/financing-sustainable-development/development-finance-standards/dacandcrscodelists.htm
 ## Benin
 The project in Benin has the objective of provide access to electricity to approximately 182,000 people in 59 rural villages. The programme will also benefit 57,000 households living in the administrative perimeters of the targeted villages, but outside the areas that will be covered by the project. A large part of the beneficiary population is below the 1.90 dollar a day poverty line.
 ## Uganda
 The project in Uganda aims to improve access to drinking water of 550,000 people living in the rural district of Isingiro, on the border with Tanzania to the Southwest of the country. The country is expected to benefit refugee camps in the area. Only 37% of inhabitants have access to water, half the average access in rural areas at national level.
 # Djibouti-Ethiopia
 The project in Djibouti and Ethiopia focuses on facilitating trade between Ethiopia and Djibouti through four components. Our study focuses on the fourth component, which targets vulnerable groups, notably women in Djibouti (where women unemployment reaches 50% rates), building their capacities to take advantage of the new opportunities arising from the development of the Djibouti-Ethiopia corridor.
 # Vietnam
 The project in Vietnam aims to contribute to the adaptation of climate change, in particular to changes in rainfall regime, and increases in the frequency and violence of extreme climatic events and to the rise in sea level.
 To do so, the project will build the Kim Dai dam-lock in Ninh Binh province, and the rehabilitation of the irrigation-drainage system in Thach Ha district in Ha Tinh province, and the banks of the Can Tho river.
 [literature](2208141732_literature.md)
 * possible starting factors:
    * ethnicity: majority (Kinh) or one of 53 minorities
        * increasing income gap
    * income
    * declining agricultural contributions to household incomes
    * household stability?
    * restructuring economy -> away from agriculture
    * geographic location (more urban, less agricultural in South)
    * housing and working conditions
    * climate change
        * saltwater intrusion
        * temperature changes
        * rainfall pattern changes (exacerbation of wet/dry season)
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 # Research Vietnam
 * focus on:
    * income inequality, based on bottom 40%, Gini coefficient, other inequality measures
    * focus on: Vietnam varation in incidence of catastrophic weather events (e.g. floodings) and unequal impact of these events on households
 ## Literature
 ### Benjamin2017 - Growth with Equity: Income Inequality in Vietnam, 2002–14
 * economic/trade liberalization reforms:
    * Enterprise Law (2000)
    * US-Vietnam Bilateral Trade Agreement (2001)
    * accession to WTO (2007)
 * tightly integrated in international economy:
    * rising inflows of FDI
    * increased trade-to-GDP ratio
 * economic shifts:
    * ongoing shift of GDP/labor from agriculture to manufacturing/services [@Cling2009; @McCaig2013; @McCaig2014; @McCaig2015]
    * sustained high rates of overall economic growth
    * even throughout 2008+ (with declining external demand, tightening monetary/fiscal policies) (real) GDP per capita grew 5.1% annually
    * similar trajectory to China - even more remarkable rates of growth over a longer period of time but at cost of higher inequality
 * marked reduction in absolute poverty in country
    * rate of decline slowed somewhat since mid-2000s [@WorldBank2013; @VASS2006; @VASS2011]
    * some decline can be directly attributed to liberalization of markets instead of growth more generally [@McCaig2011; @Benjamin2004; @Edmonds2006]
 * inequality in Vietnam is largely intersectional between ethnicity, regional situation, and a strong rural-urban divide
    * persistent poverty severe among ethnic minorities [@Baulch2012]
        * [@WorldBank2013; Baulch2012; vandeWalle2001; vandeWalle2004]
    * consumption inequality since early 1990s has been relatively constant, moving within narrow range
    * income inequality markers werwe (and are) significantly higher than consumption measures, but dropped sharply in the 1990s
        * flattening off in 2000s
    * robust grwoth in agricultural incomes were and continue to play an important role in moderating inequality increases (through other sources of income) [@Benjamin2004]
 * looks at income growth and inequality over time (2002-2014) and importantly the income sources
    * "The decompositions allow us to identify the income sources, and thus markets, that underlie Vietnam's particular experience of structural change, growth, and distribution of income." [27]
    * construction household per capita income, including a moderate grwoth slow-down in 2010.
    * **overall small income inequality decrease in Vietnam (2002-2014)**
        * suggests growth has been accompanied by equity extending beyond poverty reduction
        * rural inequality slightly increased, urban decreased
            * rural driven by slow income grwoth among ethnic minorities - a growing proportion of population
            * incomes of minorities rose, but gap to ethnic majority still widened
        * but offset by decreased urban-rural inequality
    * decomposition insights:
        * farm incomes remain "important, relatively equalizing source of opportunity for rural households"" [27]
        * growth of wage income driven by rising earnings among wage-workers more than increased participation in wage labor
    * sampled stratified into
        * households, communes, districts, provinces, regions
 While in 2002 the ethnic minority population living in rural areas was below 15% in 2002, it rose to over 18% in 2014 - both due to higher fertility among minorities and ethnic majority Kinh urbanizing at a higher rate - and the ratio of Kinh to minority incomes rose to more than 2.0 in 2014 [@Benjamin2017].
 The same study finds that income inequality rose even more sharply *within* ethnic minorities, while that of rural Kinh, though increasing from 2002 to 2014, fell back to 2002 levels around 2014.
 These findings suggest that the primary drivers of rural income inequality are a growing gap between Kinh and minorities while at the same time a similar rising inequality develops among minority rural populations themselves.
 * structural income composition: [41]
    * 2002
        * family business & wage income main drivers of income inequality (overall) (>60%) (account for higher share of inequality than income)
        * crop and agricultural sidelines income is relatively equalizing (account for lower share of inequality than income)
        * Gini coefficient: wage and family business very unequally distributed; also remittances and 'other incomes' also unequal but overall small share means they have lower impact
    * 2014:
        * wage income now 42% of total income (30.5% 2002), less unequally distributed, suggesting a labor market that is both more prevalent and more equally distributed
        * however, still majorly correlated with overall income thus driver of inequality (as are remittances)
        * overall, points to labor markets and wage labor opportunities as driver of equality during high growth BUT this is for overall population, not rural/minority population
        <!-- TODO find study for vietnam minority/rural population income inequality (within/to Kinh) -->
 * location inequality:
    * fallen dramatically, inequality increasingly within-location outcome, less due to differences between locations
    * primarily due to migration across locations
    * true for differences between urban/rural within/between provinces
 Overall: - slight reduction of of inequality through reduction in influence of wage labor on inequality while existing within-rural inequalities, those between Kinh and minorities, and those within minorities are further pushed apart.
 <!-- TODO look at 2 lowest quintiles -->
 ### Bui2019 - Determinants of Rural-Urban Inequality in Vietnam: Detailed Decomposition Analyses Based on Unconditional Quantile Regressions
 * examines determinants of rural-urban gap of household welfare in Vietnam through detailed decomposition analyses (consumption inequality) 2008-2012
 * basic education primary factor being beneficial to rural poort and ethnic minorities (in improving living standards)
 * remittances improve rural welfare but do not help reducing within or between-inequality
 * policy should ensure easy education access and support for self-employed to raise and stabilize income (instead of wage work, see @Benjamin2017)
 * other studies on income inequality [@Imai2011; Imbert2011; Takahashi2007; vandeWalle2001]
    * most have tendency to mask within-group heterogeneity
    * e.g. within rural area there is high degree of heterogeneity depending on geographic characteristics (remoteness) or cultural factors [@Cao2008]
 * previous studies on urban-rural expenditure:
    * @Thu2014 - urban-rural inequality continued to increase over years due to both covariate effects and returns to those covariate effects
        * in 90s until 2002, but marginally decreased 2002-2006 [also @Fritzen2005]
    * @Nguyen2007 - welfare disparity mainly explained by impact of structural effects
        * return to education, ethnicity, agricultural activies dramatically changed from 93-98
        * return to education improved the most
        * -> suggested development policy had urban bias (better education, more likely to benefit from economic reform)
        * confirmed by @Fesselmeyer2010 - Theil Index decomposition found period inequality within rural-urban sectors remained stable but between inequality increased 61.9%
    * @Cao2008 - within-gap for 2002-2004
    * this study builds upon their insights and uses reweighted regressions to arrive at rebust results
 * in 90s widening gap between urban and rural
    * in last decade mostly within-group disparity (due to number of salaried workers in households within each sector)
 * in 2000s within-group inequality including regional, rural-urban, ethnic, gender increased/newly analyzed
 Doi Moi policies: controlling credit growth, reducing subsidies to state-owned enterprises, besides opening economy to international trade
 results:
 * urban-rural gap increasing in 2010, decreasing afterwards
 * effects of primary&secondary education on expenditure have become more positive across distribution in rural sector in recent years
    * -> suggests welfare inequality results from inequality in opportunity to improve human capital (agrees with @Thu2014)
 * thus, with within inequality as main overal inequality contributor, and large proportion of uneducated heads of households in rural sectors, facilitating education access for disadvantaged groups (poor households and ethnic minorities) would narrow gap within and between
    * higher education widens inequality gap again (between&within)
    * low social mobility among rural poor
        * e.g. they do not get the same social insurance as urban residents
 ### WorldBank2013
 * marked reduction in absolute poverty in country
    * rate of decline slowed somewhat since mid-2000s [@WorldBank2013; @VASS2006; @VASS2011]
    * some decline can be directly attributed to liberalization of markets instead of growth more generally [@McCaig2011; @Benjamin2004; @Edmonds2006]
 * inequality in Vietnam is largely intersectional between ethnicity, regional situation, and a strong rural-urban divide
    * persistent poverty severe among ethnic minorities [@Baulch2012]
 * focuses on consumption inequality
 ## Descriptive statistical analysis ideas
 real GDP per capita growth rate (see @Benjamin2017, fn.1)
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 ## Script
 Vietnam's economy is now firmly in the third decade of ongoing economic reform (*Doi Moi*) as a market-based economy,
 which lead to remarkable growth phases through opening the economy to international trade while,
 seen over the bulk of its population, attempting to keep inequality rates managed through policies of controlling credit and reducing subsidies to state-owned enterprises [@Bui2019].
 <!-- TODO find better source - World Bank? -->
 Early income studies also generally highlighted the important role of agricultural incomes in reducing, or at the very not exacerbating, income inequality [@Benjamin2004].
 <!-- geographical inequality -->
 <!-- rural inequality -->
 In the 1990s, as the initial stages of the Doi Moi reform bore fruit with economic growth,
 the first amplifications of inequalities along new rural-urban boundaries became equally visible.
 There are two complementary views on the primary dimensions of rural inequalities.
 On the one hand, the urban-rural divide may be driven by structural effects:
 the welfare returns to education and agricultural activities changed dramatically from,
 and with it the requirements on policy adaptations required for stemming inequality.
 Nguyen et al. [-@Nguyen2007] argue this for the period of 1993-1998, with their findings that income returns to education improved dramatically over this time and arguing through this that suggested development policies had a strictly urban bias ---
 on the whole they would benefit both from better education and vastly benefit from the restructuring of Vietnam's economy.
 This view was in turn confirmed when Theil Index decomposition found within-sector inequality remaining largely stable while between-sector inequality rose dramatically [@Fesselmeyer2010].
 On the other, Thu Le and Booth [-@Thu2014] argue that the urban-rural inequality continued to increase over the years due to both covariate effects and the returns to those covariate effects.
 <!-- TODO look into covariate effects and what they are/mean -->
 The gap between urban and rural sectors grew, a gap which would continue to widen until 2002, when within-sector rural inequalities started to become more important for inequalities than those between the sectors [@Fritzen2005; @Thu2014].
 In the time of within-sector inequality becoming more pronounced many studies, while important contributions to continued inequality research, had a tendency to mask those inequalities in favor of continued analysis of between-sector trends ---
 often to the detriment of the high degree of heterogeneity depending on geographic characteristics such as remoteness or cultural factors, as Cao and Akita [-@Cao2008] note.
 In a recent study, Bui and Imai [-@Bui2019] build on the insights of these viewpoints and also find access to basic education the linchpin of improving rural welfare while its lack combined with economic restructuring precluded many from equal opportunities toward human capital improvement.
 They found that, as within-sector became more pronounced again after 2010,
 the large proportion of uneducated heads of households in rural sectors and low social mobility of rural poor combine to increase within-sector inequality while the economy overall changing toward salaried work compounded within-rural and urban-rural disparities.
 Benjamin et al. [-@Benjamin2017] expand on this over a longer time-frame by decomposing different household income sources underlying Vietnam's structural economic changes.
 They find that, while there is an overall decrease in income inequality throughout Vietnam between 2002 and 2014 and the urban-rural divide also continued its downward trend,
 rural inequality indeed increased over this time.
 Wage income and family business income were the main drivers of overall inequality in 2002 (accounting for over 30% of income but 60% of inequality) and remittances add a small share on top,
 which, while decreased in effect (risen to 42% of total income),
 remain majorly correlated with income distributions and thus income inequality.
 Thus, while the study points to more prevalent and equally distributed labor markets and wage labor opportunities,
 these effects apply to the overall population and not just within-rural inequalities which,
 as we will see, are driven in large part by ethnicity, education and environmental factors.
 <!-- poor/poverty <40%; mention low social mobility: different social insurances [@Bui2019] -->
 * marked reduction in absolute poverty in country
    * rate of decline slowed somewhat since mid-2000s [@WorldBank2013; @VASS2006; @VASS2011]
    * some decline can be directly attributed to liberalization of markets instead of growth more generally [@McCaig2011; @Benjamin2004; @Edmonds2006]
 * inequality in Vietnam is largely intersectional between ethnicity, regional situation, and a strong rural-urban divide
 <!-- minority income inequality -->
 * persistent poverty severe among ethnic minorities [@Baulch2012]
    * [@WorldBank2013; Baulch2012; vandeWalle2001; vandeWalle2004]
 Ethnic minorities in Vietnam are distinctly over-represented in poverty in addition to often being left behind in the development process, not least due to being extreme representatives of the economic situation of Vietnam's rural population.
 Ethnic minority households have a tenuous economic position - and it is deteriorating.
 While in 2002 the ethnic minority population living in rural areas was below 15% in 2002, it rose to over 18% in 2014 - both due to higher fertility among minorities and ethnic majority Kinh urbanizing at a higher rate - and the ratio of Kinh to minority incomes rose to more than 2.0 in 2014 [@Benjamin2017].
 The same study finds that income inequality rose even more sharply *within* ethnic minorities, while that of rural Kinh, though increasing from 2002 to 2014, fell back to 2002 levels around 2014.
 These findings suggest that the primary drivers of rural income inequality are a growing gap between Kinh and minorities while at the same time a similar rising inequality develops among minority rural populations themselves.
 <!-- TODO Find levels of population rural/urban in other sources -->
 In the same vein as the urban-rural divide, one can argue for structural policy failures which essentially lowered the returns on ethnicity along sectorial dividing lines of education and primary income types [@Nguyen2007].
 <!-- structures of income -->
 <!-- health inequality -->
 <!-- restructuring -->
 <!-- environmental inequality -->
 <!-- climate change exacerbations -->