Horizontal inequalities in Africa: measurement issues

SK Tetteh-Baah, K Harttgen, I Günther Chair of Development Economics ETH Zurich, Switzerland

Abstract This study estimates different indicators of horizontal or between-group inequality to track the progress made against inequality of opportunity across 38 African countries between 1990 and 2016. Such progress largely depends on the assumptions held in measuring horizontal inequality [HI]. Previous studies have shown with traditional methods of measurement that HI has been generally falling in Africa. The traditional use of a relative measure of inequality assumes that people are sensitive to relative, not absolute, differences when comparing distributions. The traditional use of plutocratic method of weighting also assumes that majority groups count more than, not equal to, minority groups. Using data from the Demographic and Health Survey program, the study demonstrates that the traditional approach to the measurement of HI embellishes the progress made against unequal opportunities over time, compared to what more egalitarian approaches would suggest. Much of the reduction in horizontal inequalities in educational attainment and wealth in Africa, as shown in previous studies, is being driven by overall growth in living standards, and not necessarily the narrowing of absolute gaps in sub- national regional, ethnic, gender, or religious outcomes over time. However, the study finds falling horizontal inequalities in child non-stunting and child survival, which is robust to the measure of inequality applied, indicating greater equality of opportunity for the new generation of African people.

JEL codes:

D63 Equity, Justice, Inequality, and Other Normative Criteria and Measurement

J71 Discrimination

Key words: horizontal inequality, inequality of opportunity, gender, ethnicity, sub-national region, religion, Africa, educational attainment, wealth, child non-stunting, child survival

1. Introduction and background literature

The cause of social development has, more than ever, been geared toward the equalization of opportunities for all. As is articulated in the Sustainable Development Goals [SDGs], the leaders of world have pledged to “leave no one behind” by 2030 (United Nations, 2015, 2017). Equality of opportunity is achieved if the outcomes of people depend solely on their choices and not on circumstances they face outside of their control, usually determined at birth, such as their gender, ethnicity, and parental background (Roemer, 1998, 2013; Roemer, Trannoy and Haven, 2015). There are both intrinsic and instrumental reasons to reduce inequality of opportunity. For the former, it is fair to work toward a world where all people, everywhere, enjoy sufficient freedom to pursue the lives of their choosing, regardless of their gender, ethnicity or race, place of birth, and religious beliefs. For the latter, a large body of empirical literature suggests (somewhat) negative relationship between inequality of opportunity and social, economic and political outcomes (Stewart, 2000, 2008; Klasen, 2002; Murshed and Gates, 2005; Østby, 2006; Mancini, 2008; Cederman, Weidmann and Gleditsch, 2011; Marrero and Rodríguez, 2013; Ferreira et al., 2018).

This study identifies the estimation of horizontal inequality across developing countries over time as a means of tracking progress toward equality of opportunity in the developing world. Horizontal inequality [HI] is inequality in social outcomes observed between socio-cultural groups defined by identity cleavages, such as gender, religion, ethnicity, geographical location, among others. HI may reflect inequality of opportunity directly; e.g., gender inequality in educational attainment observed in a country may indicate the lack of equal opportunity for females to access formal education. HI may also reflect inequality of opportunity indirectly; e.g., the fact that inequality in outcomes today translates into inequality in opportunities in the next generation (Atkinson, 2015).

In 2014, the United Nations University - World Institute for Development Economics Research (UNU-WIDER) echoed the salience of HI in developing countries, which was originally documented by Stewart (2000), and revived research on HI when it launched the project, “Group-based inequalities: patterns and trends within and across countries” (Gisselquist, 2014). In the years that followed, there has been a spike in the number of studies providing estimates of horizontal inequalities for developing countries (e.g., Gachet et al., 2016; Leivas and dos Santos, 2016; Maliti, 2016; Argaw, 2017; Thi and Hoai, 2017; Canelas and Gisselquist, 2018; Günther, Harttgen and Tetteh-Baah, forthcoming). These studies find relatively low and generally falling horizontal inequalities across most developing countries, especially in non-income indicators of well-being. This impressive conclusion is, however, driven by underlying measurement assumptions. Thus, the aim of this study is to highlight how horizontal inequality [HI] levels and trends may differ markedly depending on the assumptions held in constructing inequality indices for the measurement of HI.

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In a preceding study, we take a more comprehensive approach to the measurement of HI, compared to previous studies in this body of literature, expanding the country and time coverage, analyzing data from 70 developing countries between 1990 and 2016, while expanding the indictors of well-being and group categories (Günther, Harttgen and Tetteh-Baah, forthcoming). The preceding study provides estimates of sub-national regional, gender, religious, and ethnic inequalities in terms of educational attainment, wealth, child non-stunting, and child survival. The results show that countries in Africa, though they have relatively high levels of HI, have seen large reductions in horizontal inequalities over time, though progress is slow.

Similar to previous studies, the preceding study measures HI using the Group Gini (GGini) Index, following the recommendations of the pioneering works in this literature (Mancini, Stewart and Brown, 2008; Stewart, Brown and Mancini, 2010). This inequality index follows the same idea of the well-known Gini Index, which obtains the average of all pairwise absolute differences in individual outcomes, normalized by the overall mean, yielding a relative measure of inequality. However, with the GGini Index, group mean outcomes take the place of individual outcomes in constructing the Index, and group mean outcomes enter the GGini Index formula with plutocratic weights equal to the corresponding shares of groups in the population.

By convention, economists select inequality indices that fulfill “axioms” or “desirable properties” of inequality measurement, including transfer principle, population principle, anonymity, decomposability, scale independence, and translation independence (Harrison and Seidl, 1994; Cowell, 2016).1 The variance, for instance, is a measure of dispersion but is not a standard measure of inequality because it does not fulfill the scale independence axiom of inequality measurement (Harrison and Seidl, 1994; Cowell, 2016). The scale independence axiom states that the level of inequality remains unchanged if all outcomes change by the same proportion; say, the doubling of all incomes. Each axiom is predicated on an assumption or judgment about distributions. Thus, the axioms are inherently value-laden and could be contested philosophically. For the scale indepedence axiom, this assumption is that people are sensitive to relative differences when comparing distributions. If the income of the rich doubles and the income of the poor also doubles, the ratio of their incomes is the same as before, and the level of inequality

1 Transfer principle, population priniciple, and decomposability, are not relevant for the purposes of the study and are not discussed any further than the following. The transfer principle states that a mean-preserving, rank- preserving transfer from a poorer individual or group to a richer one must increase inequality; conversely, a similar transfer from a richer individual or group to a poorer one must decrease inequality (Pigou, 1912; Dalton, 1920). The population principle, also known as “replication invariance axiom”, states that the level of inequality in distribution 퐴 is the same for another distribution 퐵 that is a combination of 퐴 and 퐴’s replication (Cowell, 2011). The decomposability axiom can be described in the following way. Take two distributions 퐴 and 퐵 with the same population size and the same mean, but 퐴 is more unequal than 퐵. If another distribution 퐶 with the same mean (but not necessarily the same population size) is merged with 퐴 and 퐵, separately, 퐴 merged with 퐶 will also be more unequal than 퐵 merged with 퐶 (Cowell, 2011). 2 remains unchanged in a relative sense. A relative measure of inequality conforms to the scale independence axiom of inequality measurement (e.g., the Relative GGini Index).

The translation independence axiom of inequality states that the level of inequality remains unchanged if all outcomes change by the same amount; say, a lump-sum transfer of $100 to every employee in an organization (Harrison and Seidl, 1994; Cowell, 2016). The assumption underlying this axiom is that people are sensitive to absolute differences when comparing distributions. With a lump-sum transfer, the absolute difference between the incomes of the rich and the poor remains the same as before, and the level of inequality remains unchanged in an absolute sense. An absolute measure of inequality conforms to the translation independence axiom of inequality measurement (e.g., the Absolute GGini Index).

Whether people are sensitive to relative or absolute differences in outcomes when comparing distributions, or a combination of both, is an experimental question. Yet the experimental literature is limited and inconclusive on this (Cowell, 1992; Amiel and Cowell, 1999; Lembregts and Pandelaere, 2014; Ravallion, 2014). Using questionnaire-experiments, students have given support for both scale and translation independence axioms of inequality measurement when they were asked to compare income distributions (Cowell, 1992; Amiel and Cowell, 1999). Lembregts and Pandelaere (2014) observe the presence of “partial relative thinking” in income comparisons, suggesting that people may be sensitive to both absolute and relative differences when comparing distributions. The authors provide experimental evidence that the perception of inequality increases with a fixed percentage increase in all incomes, even though measured inequality remained unchanged in relative terms. Ravallion (2014) provides empirical evidence that the perception of rising income inequality in the developing world is consistent with rising Absolute Gini Index between 1980 and 2010, even though Relative Gini Index has been falling over the same period. It is shown that the Absolute Gini Index is a measure of inequality that effectively captures the perception of relative deprivation, because it is the weighted average of all pairwise absolute differences or gaps between individual or group outcomes (Kolm, 1976; Yitzhaki, 1979; Atkinson and Brandolini, 2015).

According to Ravallion (2014), who also finds support for both scale independence and translation independence in questionnaire-experiments administered to his students, it is a judgment call to use either a relative or absolute measure of inequality; one is not wrong and the other right (cf. Atkinson and Brandolini, 2004). Consequently, another literature proposes and/or applies an intermediate concept that incorporates into the measurement of inequality both relative and absolute concepts of inequality (Kolm, 1976; Atkinson and Brandolini, 2004, 2015; Subramanian and Jayaraj, 2013; Subramanian, 2015; Niño-Zarazúa, Roope and Tarp, 2017). Intermediate inequality measures have the property of decreasing when outcomes increase by the same amount, which is a violation of the translation independence axiom, at the same time increasing when all outcomes increase by the same proportion, which is also a violation of the scale

3 independence axiom. The reverse holds when all outcomes decrease by the same amount or proportion.

Kolm (1976) views the intermediate concept as “centrist”, while the absolute concept is “leftist” or more egalitarian and the relative concept is “rightist” or less egalitarian. Atkinson and Brandolini (2004) apply all these concepts to income data from the Penn World Table and find that international inequality, or inequality between countries, has been falling when using relative measures of inequality, but rising when using absolute and intermediate measures of inequality between 1970 and 2000. Similarly, intermediate measures of inequality, such as the Krtscha Index and Intermediate Gini Index, mimic a rising trend in “global income inequality” (or, inequality between and within countries) showed by absolute measures of inequality between 1975 to 2010 (Niño-Zarazúa, Roope and Tarp, 2017). Subramanian and Jayaraj (2013) also conclude from absolute and intermediate measures of inequality that consumption and wealth inequalities have been rising in India beween 1961 and 2003 instead of having no trend, as suggested by relative measures.

Another axiom of inequality measurement is the principle of anonymity, which states that the level of inequality remains the same for every permutation of the distribution (Harrison and Seidl, 1994; Cowell, 2016). That is to say, if all outcomes are re-allocated across individuals or groups, the level of inequality remains unchanged. The assumption underlying this axiom is that all individuals or groups are identical, except for differences in outcomes. This assumption is far- fetched, but is an important restriction that favors the measurement of inequality, because it simplifies the comparison of individuals or groups in a distribution. For the measurement of horizontal inequalities, in particular, it may be hard to assume away the fact that groups have different shares in the population, especially when there are minority and majority ethnic or religious groups co-existing in many developing countries. To this end, Stewart, Brown and Mancini (2010) suggest that group mean outcomes carry a weight equal to groups’ corresponding shares in the population when estimating HI. Population weighting assumes that majority groups count proportionally more than minority groups within countries. Population weighting, also known as plutocratic weighting, may favor efficiency concerns. However, if one counterargues that all population sub-groups are equally important, regardless of their shares in the population, all group mean outcomes may carry equal, democratic weights when estimating HI. While plutocratic weighting may favor efficiency concerns, democratic weighting may favor equity concerns.

There are pros and cons to measuring HI with plutocratic or democratic weights. While plutocratic weighting ensures that the measurement of HI is representative of the population, the level of HI may be too low if minority groups have relatively low outcomes. On the other hand, democratic weighting may overrepresent minority groups in the data and the level of HI may be too high if minority groups have relatively low outcomes. It boils down to which population sub-groups in

4 the distribution one cares more about, whether the majority or minority group. A social planner with high aversion to HI, or who favors affirmative action, might prefer applying democratic weights, so as to highlight the relative deprivations of minority and marginalized groups in the data. One has to make important value judgments regarding the relative importance of efficiency and equity, even if at all there are important tradeoffs between the two, before deciding whether to apply plutocratic or democratic weights in the measurement of HI.

It remains a debate of great political importance whether or not there are tradeoffs between efficiency and equity (Okun, 1975; Sandmo, 1981; Klasen, 2008; Andersen and Maibom, 2016). Recent research however suggests that there are limited or no tradeoffs between efficiency and equity, and equity may be efficient in and of itself (Osberg, 1995; Klasen, 2008; Cingano, 2014; Ostry, Berg and Tsangarides, 2014). For example, more equal countries, such as the Nordic ones, seem to be more efficient (Osberg, 1995). In many developing countries, rising inequality has not accompanied growth (Ravallion, 2014; Freund, 2016; Klasen et al., 2016). Policies are being made to make growth more inclusive (e.g., OECD, 2016). In fact, much of the concern about possible equity-efficiency tradeoffs is discussed in the context of income. In the context of non-income indicators of well-being, such as educational attainment, it is more apparent to expect no such tradeoffs, rather possible complementaries resulting from human capital formation (Osberg, 1995). Researchers and policymakers may therefore be more inclined to embrace democratic weighting in the measurement of HI.

Stewart, Brown and Mancini (2005) constructed the GGini Index, arguing for plutocratic weighting, in the era of the United Nations’ Millenium Development Goals (MDG’s) when efficiency seemed to be more prominent in political debates. In this new era when the United Nations has pledged the Sustainable Development Goals (SDG’s) to promote greater equity “for all” and “leave no one behind” by 2030, this study argues to construct inequality indices in a way that emphasizes greater equity for marginalized and minority groups. Not only is the United Nations charting the course of development toward greater equity, but the World Bank is pursuing a similar cause alongside, which is to “ensure equality of opportunity everywhere in the world” (World Bank ex-president Jim Kim, 2018).2 It may be argued that the lives of everyone, however a minority, count just as much as the majority.

Accordingly, recent inequality research is paying attention to such equity concerns. For example, Milanovic (2016) emphasizes the relevance of plutocratic and democratic weighting in the measurement of income inequality and their implications for policy. He shows that globalization between 1960 and 2010 has come along with either declining or rising inequality between countries, depending on whether plutocratic or democratic weights are applied in measuring income inequality. Up until 2000, globalization has come with declining inequality between

2 http://www.worldbank.org/en/news/press-release/2018/04/26/world-bank-group-president-appoints-pinelopi- koujianou-goldberg-as-chief-economist 5 countries, when he accounts for populous countries like China and India, whose incomes have grown very fast within this period. When countries are weighted equally, however, globalization seems to have come with worsening inequality between countries.

The research objective of this study is to investigate if and how HI levels and trends in Africa will change when traditional assumptions held in the measurement of HI are relaxed. In doing so, the study compares estimates of HI using plutocratic weighting with estimates of HI using democratic weights, and compares estimates of HI across relative, intermediate, and absolute measures of inequality. The results show that, once we apply democratic weights instead of plutocratic weights, religious and ethnic inequalities in particular are significantly higher, and more persistent over time, across African countries. Thus, the traditional method of measuring HI using plutocratic weights may be doing us a disservice, as it conceals pockets of prejudice in the data against minority religious and ethnic groups that may be left behind. Additionally, the results show that the traditional approach of using a relative measure of inequality generally increases the rate of reduction in horizontal inequalities, or it embellishes progress made against unequal opportunities relative to what would be suggested by an absolute or intermediate measure of inequality. Particularly, absolute gender, ethnic and religious gaps in educational attainment and wealth have remained the same in 2016 as they were in 1990 across most developing countries, while absolute sub-national regional gaps in educational attainment and wealth have even worsened in most African countries over the time. Much of the reduction in horizontal inequalities in educational attainment and wealth in Africa, as shown in previous studies, is being driven by overall growth in living standards, and not necessarily the narrowing of absolute gaps in sub-national regional, ethnic, gender, or religious outcomes over time. The study, however, finds falling trends in horizontal inequalities in child non-stunting and child survival, which is robust to the measure of inequality applied, indicating greater equality of opportunity for the new generation of African people.

The rest of the study is organized as follows. Section 2 describes the data and methodology used to estimate and compare the levels and trends in horizontal inequalities across African countries. Section 3 presents the results, and Section 4 checks the robustness of the results. Section 5 concludes the study.

2. Data and methodology This study utilizes secondary data from the Demographic and Health Survey (DHS) database to estimate horizontal inequalities. The DHS program, sponsored by the United States Agency for International Development (USAID), has since the mid-1980s collected nationally representative household survey data on fertility, nutrition, reproductive health, maternal health, as well as socioeconomic and demographic characteristics, in well over 80 developing countries. The USAID has collaborated with country statistical offices to, as much as possible, standardize the collection and reporting of the data, a way to facilitate data analysis and cross-country comparisons. 6

For this study, 250 surveys in the DHS program conducted between 1990 and 2016 in 70 developing countries have been selected for analysis. Each of these countries has, on average, 3.7 surveys over the 27-year period. The data set consists of 38 countries in an Africa sub-sample (approximately 86% of the African population), and 32 countries in a non-Africa sub-sample, consisting of 12 countries in Latin America and the Carribean, 12 in Asia, and 7 in developing Europe. See Appendix A for a complete list of countries in the data set as well as the survey years for each country. The African countries have more surveys than the countries in the other developing regions. Thus, we have richer and more representative information for Africa, especially when estimating trends in horizontal inequalites, which requires at least 2 surveys for a country. As a result, the trend analysis of the study focuses on countries in the Africa sub- sample.

To operationalize the research objective of this study, a range of different indicators of HI are estimated in the following way. First, four indicators of well-being are constructed from the DHS data, namely educational attainment, household wealth, child non-stunting, and child survival. Educational attainment is the number of completed years spent in school by the population aged 15 to 64. Household wealth is an index constructed from the ownership of a set of household assets using principal components analysis, and is used as a proxy for standard of living. Child non-stunting and child survival are indicators of nutrition and health of children under 5. Second, four categorical variables are selected, subject to DHS data constraints. These include sub- national region, gender, religion, and ethnicity. Third, the indicators of well-being and categorical variables are combined to estimate HI using an inequality index, as explained in the following.3 By the traditional approach, HI is estimated for a particular country and survey year by applying the formula for Group Gini (GGini) Index, expressed in Equation (1) below, on mean outcomes of gender, sub-national region, religious, or ethnic groups in terms of educational attainment, wealth, child non-stunting, or child survival, as suggested by Stewart, Brown and Mancini (2005, 2010) and Mancini, Stewart and Brown (2008).

1 푅푒푙푎푡푖푣푒 퐺퐺푖푛푖 퐼푛푑푒푥 = ∑퐺 ∑퐺 푝 푝 |푦̅ − 푦̅ | (1) 2푦̅ 푔=1 푘=1 푔 푘 푔 푘 with: 푛푔 푛푘 퐺 푦̅푔 = ∑푖=1 푦푖푔, 푦̅푘 = ∑푖=1 푦푖푘, and 푦̅ = ∑푔=1 푝푔 푦̅푔 where:

3 The details about the well-being indicators, group categories, and estimation of HI can be found in Günther, Harttgen and Tetteh-Baah (forthcoming). See Appendix B for the list of sub-national regions, religions, and ethnicities for countries that have these data. Since the DHS program sometimes records different sub-national regions, religions, and ethnicities, Appendix B also shows how they have been harmonized across surveys to facilitate trend analysis. The rest of this section looks more directly at information that is more relevant for our purposes in the study.

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푦푖푔 is the observation of the outcome variable of interest (e.g., years of schooling) for household (member) 푖 in group 푔,

푦푖푘 is the observation of the outcome variable of interest (e.g., years of schooling) for household (member) 푖 in another group 푘, 푦̅ is the overall mean value,

푦̅푔 is group 푔’s mean value,

푦̅푘 is another group 푘’s mean value, 퐺 is the number of groups,

푛푔 is the total number of observations in group 푔,

푛푘 is the total number of observations in another group 푘,

푝푔 is group 푔’s population share,

푝푘 is another group 푘’s population share

The Relative GGini Index obtains a population-weighted average of all pairwise absolute differences in group mean outcomes, normalized by the overall mean. It is quite easy to interprete. For instance, if educational attainment is evenly distributed across both gender groups, the Index will be 0. On the other hand, if all educational attainment is attributed to only one gender group, the Index will be 100 (e.g., a society where females have no right to education).

The Relative GGini Index in Equation (1) applies plutocratic weights equal to groups’ population shares. However, Equation (1) may be adjusted by applying equal weights [푝푔 = 푝푘 = 1/퐺] to obtain Relative GGini Index with democratic weights. This study obtains estimates of HI with plutocratic and democratic weighting.

Additionally, HI can be estimated with Relative, Intermediate, and Absolute GGini Indices. Equation (1) is multiplied by the term in the denominator to obtain Absolute GGini Index, expressed as follows: 퐴푏푠표푙푢푡푒 퐺퐺푖푛푖 퐼푛푑푒푥 = [푅푒푙푎푡푖푣푒 퐺퐺푖푛푖 퐼푛푑푒푥 ] ∗ 2 ∗ 푂푣푒푟푎푙푙 푀푒푎푛 (2)

1 = [ ∑퐺 ∑퐺 푝 푝 |푦̅ − 푦̅ |] ∗ 2 ∗ 푦̅ 2푦̅ 푔=1 푘=1 푔 푘 푔 푘

퐺 퐺 = ∑푔=1 ∑푘=1 푝푔 푝푘|푦̅푔 − 푦̅푘| (3) Absolute GGini Index obtains a population-weighted average of all pairwise absolute differences in all group mean outcomes. It measures the absolute sub-national regional, gender, religious, and ethnic gaps in mean outcomes. Absolute GGini Index is not normalized to lie between 0 and 100, because it is mean-dependent as discussed earlier.

Intermediate GGini Index is the product of the Relative and Absolute GGini Indexes. It is expressed as follows:

퐼푛푡푒푟푚푒푑푖푎푡푒 퐺퐺푖푛푖 퐼푛푑푒푥 = 푅푒푙푎푡푖푣푒 퐺퐺푖푛푖 퐼푛푑푒푥 ∗ 퐴푏푠표푙푢푡푒 퐺퐺푖푛푖 퐼푛푑푒푥 (4) 8

퐺 퐺 2 (∑푔=1 ∑ 푝푔 푝푘|푦̅푔 − 푦̅푘|) = 푘=1 2푦̅

(퐴푏푠표푙푢푡푒 퐺퐺푖푛푖 퐼푛푑푒푥)2 = (5) 2푦̅ Intermediate GGini Index is also mean-dependent and is not normalized to lie betwee 0 and 100.

In summary, suppose 퐻퐼푖푗 is an estimate of HI, where 푖 runs from 1 to 3 representing relative, intermediate, or absolute measure of inequality, respectively, and 푗 runs from 1 to 2 representing plutocratic or democratic method of weighting, respectively. In total, 6 different estimates of HI are obtained, including:

퐻퐼11: Relative GGini Index with plutocratic weighting

퐻퐼21: Intermediate GGini Index with plutocratic weighting

퐻퐼31: Absolute GGini Index with plutocratic weighting

퐻퐼12: Relative GGini Index with democratic weighting

퐻퐼22: Intermediate GGini Index with democratic weighting

퐻퐼32: Absolute GGini Index with democratic weighting Thus, there are 2 factors along which HI estimates may vary, namely the measure of inequality and method of weighting.

The idea of the study is to investigate how the level or trend in HI changes if one factor varies, given the other. Theoretically, five different comparisons are possible: (1) 퐻퐼11, 퐻퐼21, and 퐻퐼31 or (2) 퐻퐼12, 퐻퐼22, and 퐻퐼32 or (3) 퐻퐼11 and 퐻퐼12 or (4) 퐻퐼21 and 퐻퐼22 or (5) 퐻퐼31 and 퐻퐼32. However, some of the comparisons are not practically intuitive. For example, it is not practically intuitive to compare the level of HI across the measures of inequality, because Absolute and Intermediate GGini Indices are mean dependent while Relative GGini Index is not. But, it is practically intuitive to compare the level of HI across the method of weighting. This study compares plutocratic and democratic weighting, given the traditional, relative measure of inequality. Thus, 퐻퐼11 and 퐻퐼12 are compared for the levels in HI. Further, it is not practically intuitive to compare the method of weighting given Absolute Gini Index [퐻퐼31 and 퐻퐼32], because Overall Mean cancels out from both HI estimates, yielding 퐻퐼11 and 퐻퐼12 as before. It is neither intuitive to compare the method of weighting given Intermediate GGini Index [퐻퐼21 and 퐻퐼22], because Intermediate GGini Index is a function of Absolute GGini Index by construction.

The trends in HI over time may be compared in all 5 different ways, but only 3 are particularly intuitive. First, the rates of change observed in Relative, Intermediate, and Abosolute GGini

Indexes with plutocratic weighing may be compared [퐻퐼11, 퐻퐼21, and 퐻퐼31]. For this study, we investigate how the trends observed in HI differ depending on the measure of inequality, given 9 the traditional, plutocratic method of weighting. Second, the rates of change observed in Relative,

Intermediate, and Abosolute GGini Indices with democratic weighting may be compared [퐻퐼12, 퐻퐼22, and 퐻퐼32]. This second investigation is done as robustness checks for the trend analysis. Third, the rates of change observed in Relative Gini Index with plutocratic and democratic weighting may be compared [퐻퐼11 and 퐻퐼12], which is the same comparison made for the levels in HI. This comparison shows how plutocratic and democratic weighting change the trends in HI. This third investigation is presented as part of the main results for the trend analysis in the study.

The rates of change in Absolute and Intermediate GGini Indices with plutocratic and democratic weighting can be determined from the rate of change in Relative GGini Index with plutocratic and democratic weighting, respectively, once the rate of change in Overall Mean is known. For this reason, comparing plutocratic and democratic weighting for the trends in HI will be limited to Relative GGini Index.

To investige the trends in HI further, the evolution of Equation (2) over time is explored as follows. Mathematically, the following equation holds from Equation (2): 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 퐴푏푠표푙푢푡푒 퐺퐺푖푛푖 퐼푛푑푒푥 = 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 푅푒푙푎푡푖푣푒 퐺퐺푖푛푖 퐼푛푑푒푥 + 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 푂푣푒푟푎푙푙 푀푒푎푛 (6)

Re-arranging: 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 푅푒푙푎푡푖푣푒 퐺퐺푖푛푖 퐼푛푑푒푥 = 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 퐴푏푠표푙푢푡푒 퐺퐺푖푛푖 퐼푛푑푒푥 − 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 푂푣푒푟푎푙푙 푀푒푎푛 (7)

Following from Equation (7) above, the rate of change in Relative GGini Index depends on the sign and size of the rates of change in Absolute GGini Index and Overall Mean. The trends observed in HI as measured by the traditional Relative GGini Index are partly driven by the trends in Absolute GGini Index and partly driven by the trends in Overall Mean. If absolute sub-national, gender, religious, and ethnic gaps in mean outcomes remain constant over time, the rate of change in Relative GGini Index and rate of change in Overall Mean will be in opposite directions to establish equality in Equation (7). The study investigates if the overall increase in living standards in the developing world has been driving the reduction in the trends in HI in the developing world observed in previous studies.

The evolution of Intermediate GGini Index expressed in Equation (4) is analogously given as: 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 퐼푛푡푒푟푚푒푑푖푎푡푒 퐺퐺푖푛푖 퐼푛푑푒푥 = 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 푅푒푙푎푡푖푣푒 퐺퐺푖푛푖 퐼푛푑푒푥 + 푅푎푡푒 표푓 퐶ℎ푎푛푔푒 푖푛 퐴푏푠표푙푢푡푒 퐺퐺푖푛푖 퐼푛푑푒푥(8)

Thus, the rate of change in Intermediate GGini Index depends on the rates of change in Relative and Absolute GGini Indices.

This study estimates the rates of change in Relative, Intermediate, and Absolute GGini Indices by regressing logarithmized observations of HI as measured by these Indices on a time variable, 10

푌푒푎푟, while controlling for country fixed-effects. The coefficient on the time variable, 푌푒푎푟, is the annualized rate of change in Relative, Intermediate, and Absolute GGini Indices, respectively. The country fixed-effects ensure that the estimates for the rate of change in HI are not driven by countries with more surveys. Similarly, the rate of change in Overall Mean is obtained by regressing logarithmized observations of Overall Mean on a time variable, 푌푒푎푟, while controlling for country fixed-effects. The coefficient on the time variable, 푌푒푎푟, is the annualized rate of change in Overall Mean.

3. Results As indicated earlier, the study compares the levels and trends in sub-national regional, ethnic, gender, and religious inequalities in educational attainment, wealth, child non-stunting, and child survival in respect of different indices used for measuring HI. The results are discussed with regard to the progress made against inequality of opportunities in the developing world. Due to data limitations in the Non-Africa sub-sample, the trend analysis in Section 3.2 focuses on countries in the Africa sub-sample.

3.1 Levels in horizontal inequality

Table 1 summarizes the levels in HI for both African and non-African countries. Table 1: Levels in HI - plutocratic vs. democratic weighting

Africa sub-sample Non-Africa sub-sample Educational attainment plutocratic democratic plutocratic democratic HI - Sub-national region 15.12 16.36 7.15 7.14 HI - Ethnicity 13.13 20.37 6.17 9.10 HI - Gender 10.00 9.87 3.74 3.72 HI - Religion 8.16 16.66 1.65 5.97 Wealth HI - Sub-national region 19.09 20.99 11.27 11.85 HI - Ethnicity 12.08 18.50 6.03 9.36 HI - Religion 4.55 12.61 1.55 4.21 Child non-stunting HI - Sub-national region 3.05 3.46 4.17 4.47 HI - Ethnicity 2.58 4.68 2.56 3.78 HI - Gender 1.05 1.05 0.74 0.75 HI - Religion 0.95 2.79 0.74 3.23 Child survival HI - Sub-national region 1.43 1.55 0.72 0.78 HI - Ethnicity 1.77 3.06 0.59 1.13 HI - Gender 0.49 0.49 0.27 0.27 HI - Religion 0.51 1.55 0.22 0.86 11

Notes: 1) These estimates are averages over country-year observations of HI. Each country has a weight of unity, so that countries with more surveys do not drive the results. 2) All estimates of HI are normalized to lie between 0 and 100, which are respectively the lower and upper bounds of the Gini Index, theoretically. 3) No estimates are provided for gender inequality in wealth, because the DHS asset profiles are available at the household level, and it is not possible to isolate which shares of the household assets are controlled by men and women. In all indicators of well-being, horizontal inequalities are generally lower with plutocratic weighting. For example, in the Africa sub-sample, sub-national regional, ethnic, gender, religious inequality in educational attainment is 15, 13, 10, 8 GGini points with plutocratic weighting, but is 16, 20, 10, 17 with democratic weighting, respectively. In the non-African sub-sample, the corresponding estimates are 7, 6, 4, 2 with plutocratic weighting and 7, 9, 4, 6 with democratic weighting, respectively. In particular, the difference is most striking with religious and ethnic inequalities. Figure 1 graphically highlights these differences and illustrates whether or not the differences are statistically significant for inequalities in educational attainment. (Similar graphs are shown for wealth, child non-stunting, and child survival in Appendix C.) At a significance level of 5%, estimates of HI with plutocratic and democratic weighting are statistically different from each other for religious and ethnic inequalities, particularly for the Africa sub-sample.

Besides, the study finds a re-ranking of the sources of inequality of opportunity, in both Africa and non-Africa sub-samples. With plutocratic weighting, the ranking in the Africa sub-sample in descending order is: sub-national region, ethnicity, gender, and religion. With democratic weighting, the ranking in the African sub-sample in descending order is: ethnicity, religion, sub- national region, and gender. Given the group categories analyzed in the study, religion ranks as the least important source of inequality of opportunity with plutocratic weighting, but ranks as second most important source of inequality of opportunity after ethnicity. With regard to sources of inequality of opportunity in Africa, religion may appear relatively innocuous with plutocratic weighting, but may appear relatively pernicious with democratic weighting. In the non-African sample, plutocratic weighting places sub-national region and ethnicity as the most important sources of inequality of opportunity, while democratic weighting places ethnicity and sub- national region as the most important sources of inequality of opportunity. In both Africa and non-Africa sub-samples, ethnic inequality keeps a high spot in the ranking with plutocratic or democratic weighting. This result highlights ethnicity as an important source of inequality of opportunity in the developing world.

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Figure 1: HI in educational attainment – plutocratic vs. democratic weighting

Figure 2 shows heterogeneity in sub-national regional, gender, religious, and ethnic inequalities in educational attainment across developing regions of the world. First, one can see that horizontal inequalities generally bulge out in the Africa quadrant, for both plutocratic and democratic weighting. This confirms that horizontal inequalities are more pronounced in the Africa region. Second, one can see the stark differences in estimates of religious and ethnic inequalities across all developing regions, comparing plutocratic and democratic weighting. Even for developing Europe, plutocratic weighting suggests almost no religious and ethnic inequalities, but democratic weighting reveals some minimal levels of religious and ethnic inequalities. Similar charts are in Appendix D for wealth, child non-stunting, and child survival.

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Fig. 2: HI in educational attainment across developing regions of the world

Next, the study graphically illustrates why democratic weighting significantly increases the levels of religious and ethnic inequalities; that is, minority religious and ethnic groups in the developing world often have relatively low mean outcomes. All country-year observations of HI with plutocratic and democratic weighting in both Africa and Non-Africa sub-samples are plotted on graphs with 45° lines. Figure 3 to Figure 6 plot horizontal inequalities in educational attainment, and similar graphs are in Appendix E for horizontal inequalities in wealth, child non-stunting, and child survival. Observations that are on the 45° line are cases where estimates of HI with plutocratic weighting are the same as estimates of HI with democratic weighting. All observations below the 45° line are cases where HI is greater with democratic weighting than with plutocratic weighting. This occurs when majority groups have relatively high mean outcomes and minority groups have relatively low mean outcomes. With plutocratic weighting, the relative deprivations of minority groups are weighted down; with democratic weighting, the relative deprivations of minority groups are weighted up. Most of the observations in Figure 3 to Figure 6 fall within this category. On the other hand, all observations above the 45° line are cases where HI is greater with plutocratic weighting than with democratic weighting. This occurs when majority groups have relatively low mean outcomes and minority groups have relatively high mean outcomes.

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With plutocratic weighting, the relative deprivations of majority groups are weighted up; with democratic weighting, the relative deprivations of majority groups are weighted down. Few of the observations in Figure 3 to Figure 6 fall within this category.

Figure 3: Religious inequality in educ. attainment Figure 4: Ethnic inequality in educ. attainment

Figure 3 highlights some countries with relatively high levels of religious inequality in educational attainment as well as countries where democratic weighting amplifies the level of religious inequality in educational attainment, such as Niger, Mali, Rwanda, and Cambodia. Chad is an exception, where the majority Moslem group is less educated than the minority Christian group. Figure 4 highlights some countries with relatively high levels of ethnic inequality in educational attainment as well as countries where democratic weighting amplifies the level of ethnic inequality in educational attainment, such as Ethiopia, Burkina Faso, and Nepal. Nigeria appears to be an exception, where the majority Hausa ethnic group is less educated than the less populous Yoruba and Ibo ethnic groups. But it is hard to make any concrete conclusions, given the very high ethnic diversity in Nigeria that is not well represented in the DHS data.

Figure 5: Regional inequality in educ. attainment Figure 6: Gender inequality in educ. attainment

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Figure 5 highlights some countries with relatively high levels of sub-national regional inequality in educational attainment as well as countries where democratic weighting amplifies the level of sub-national regional inequality in educational attainment, such as Ethiopia, Niger, and Chad. Unlike religious and ethnic inequalities, the deviations in the estimates of HI with plutocratic and democratic weighting are not large. In a number of countries, such as Madagascar, Senegal, and Cameroon, the relatively populous sub-national regions are less educated, so that HI with plutocratic weighting is higher.

Figure 6 plots a similar graph for gender inequality in educational attainment. As is expected, nearly all observations lie in the neighborhood of the 45° line. In the DHS data, females are generally more than males, but the ratio is almost 50:50. In countries such as Chad, Guinea, Benin, and Nepal, the more populous female gender group is less educated, but the difference in population shares between males and females is limited, hence observations of HI tilt only slightly above the 45° line. Indeed, the data show the presence of religious and ethnic minorities in terms of population shares; less so for gender and sub-national regional minorities. See Appendix F for stacked bar graphs that depict population shares of sub-national regional, ethnic, religious, and gender groups across countries.

3.2 Trends in horizontal inequality

HI falls, rises, or remains stable over time, depending on the measure of inequality and method of weighting applied. Table 2 presents the average rates of change in sub-national regional, ethnic, gender, and religious inequalities in terms of educational attainment, wealth, child non- stunting, and child survival for the Africa sub-sample.4 Estimates of HI with plutocratic weighting are used for the results of the trend analysis reported in this table.

In general, horizontal inequalities have been falling across African countries by the Relative GGini Index. By the Absolute GGini Index, horizontal inequalities have not fallen as much across African countries. Sub-national regional inequality in educational attainment and wealth have even increased by 0.96% and 1.32%, respectively. Ethnic inequality in wealth have also increased by 0.94%. The Intermediate GGini Index sums up the rate of change in the Relative GGini Index and Absolute GGini Index. For inequalities where Relative GGini Index and Absolute GGini Index change in opposite directions, as in educational attainment and wealth, Intermediate GGini Index takes the sign of one of the two rates that dominates. By the Intermediate GGini Index, sub- national regional and ethnic inequalities in educational attainment have been falling, but not as much as suggested by the Relative GGini Index. Horizontal inequalities in wealth have been rather persistent across African countries, as sugested by the Intermediate GGini Index, or worsening, as suggested by the Absolute GGini Index. For child non-stunting and child survival, both Relative

4 The trend analysis is limited to the Africa sub-sample due to data limitation in the Non-Africa sub-sample. 16

GGini Index and Absolute GGini Index have been falling over time, and Intermediate GGini Index magnifies the rates of reduction in HI, by construction.

Table 2: Trends in HI - Relative, Intermediate, Absolute - I Africa sub-sample Educational attainment Relative (%) Intermediate (%) Absolute (%) HI - Sub-national region -1.49*** -0.53 0.96*** HI - Ethnicity -1.86*** -1.13 0.73 HI - Gender -2.69*** -2.92*** -0.23 HI - Religion -2.64*** -2.88** -0.24 Wealth HI - Sub-national region -0.51 0.81 1.32*** HI - Ethnicity -0.91* 0.03 0.94* HI - Religion -0.75 0.17 0.92 Child non-stunting HI - Sub-national region -3.54*** -6.15*** -2.60*** HI - Ethnicity -4.11*** -7.24*** -3.13*** HI - Gender -4.03*** -7.09*** -3.07*** HI - Religion -3.92*** -7.00*** -3.08*** Child survival HI - Sub-national region -3.73*** -7.02*** -3.29*** HI - Ethnicity -4.03*** -7.58*** -3.54*** HI - Gender -1.14 -1.89 -0.75 HI - Religion -3.87*** -7.30*** -3.43*** Notes: 1) These estimates are obtained by regressing logarithmized country-year observations of HI on a time variable, 푌푒푎푟. 2) The coefficient on 푌푒푎푟 is, on average, the annualized rate of change (%) in HI reported in the table. 3) The regressions control for country fixed-effects, so that countries with more surveys do not drive the results. 4) ***, **, and * indicate statistical significance at 1%, 5%, and 10% levels, respectively. By the construction of the indices, changes in Overall Mean drive the results discussed above. In Africa, living standards have been rising rapidly in the past 3 decades, what some economists refer to as the “African Growth Miracle” (Radelet, 2010; Young, 2012; McMillan and Harttgen, 2014). As can be seen in Table 3, educational attainment has on average been rising by 2.5% per annum, wealth by 1.8% per annum, child non-stunting by 0.96% per annum, and child survival by 0.39% per annum across countries in the Africa sub-sample.

Table 3: Social outcomes in Africa, 1990 – 2016 Well-being indicator Level Change (%) Educational attainment (in years) 4.96 2.46 Wealth (in units) 1.83 1.80 Child non-stunting (%) 74.71 0.96 Child survival (per 1000 live births) 889.28 0.39 Notes: 1) All estimates are statistically significant at the 1% level. 2) For educational attainment, child non-stunting, and child survival, the overall means used for estimating HI by the gender category are used for this analysis, since gender has the highest number of country-year observations. For wealth, the overall means used for estimating HI 17 by the sub-national region category are used for this analysis, since sub-national region has the highest number of country-year observations.

As indicated already in Section 2, Relative GGini Index is Absolute GGini Index normalized by Overall Mean. Thus, the rate of change in Relative GGini Index depends on both the size and sign of the rates of change in Absolute GGini Index and Overall Mean. This relationship is illustrated with gender inequality in educational attainment in Africa, comparing results from Table 2 and Table 3. As measured by the Absolute GGini Index, gender inequality has been changing by -0.23% and Overall Mean has been changing by 2.46%, netting out to a rate of -2.69%, which is the rate of change in gender inequality as measured by the Relative GGini Index. As traditionally measured by the Relative GGini Index, gender inequality in Africa has seen a very impressive reduction of 2.69%, but this is largely driven by the rapid growth in educational attainment overall, so that the gender gaps in educational attainment in Africa countries have been remained more or less the same in 2016 as they were in 1990. (The result of -0.23% change in Absolute GGini Index as shown in Table 2 is not statistically different from zero.)

Real progress against unequal opportunities over time is observed when Relative GGini Index falls (significantly) faster than Overall Mean rises, implying that Absolute GGini Index falls at a (significant) negative rate and Intermediate GGini Index definitely also falls at a significant negative rate by construction. From Tables 2, such progress is observed in inequalities in child non-stunting and child survival in the Africa sub-sample. By the Absolute GGini Index, sub-national regional gaps in educational attainment as well as sub-national regional and ethnic gaps in wealth have been widening in most parts of Africa over time. These findings hold on average for countries in the Africa sub-sample, but there is important heterogeneity across countries. In Appendix G, rates of change in Relative, Intermediate, and Absolute GGini Index are reported to illustrate progress made against unequal opportunities in educational attainment, wealth, child non- stunting, and child survival at the country level.

As mentioned earlier on, HI trends also differs depending on the method of weighting. Relative GGini Index is used as the measure of inequality to compare plutocratic and democratic weighting. Table 4 shows that horizontal inequalities have generally been falling more rapidly across African countries with plutocratic weighting than with democratic weighting, especially religious inequalities. This finding is not too surprising, because democratic weighting generally increases the level of HI, so that rates of change in HI are expected to be lower with democratic weighting. Thus, the traditional, plutocratic method of weighting does not only reduce the levels in HI, but also suggests greater progress against HI or inequality of opportunities in Africa over time. Religion, in particular, remains an important identity cleavage in Africa, if minority religious groups are treated as equally important as majority religious groups. In fact, religious inequality in wealth has increased over time by 0.28%; though it is not statistically different from zero, it is

18 striking because all other horizontal inequalities with democratic weighting have a negative rate of change.

Table 4: Trends in HI - plutocratic vs. democratic weighting Africa sub-sample Educational attainment plutocratic (%) democratic (%) p-value HI - Sub-national region -1.49*** -1.65*** 0.16 HI – Ethnicity -1.86*** -1.36** 0.14 HI – Gender -2.69*** -2.68*** 0.38 HI – Religion -2.64*** -1.94*** 0.05 Wealth HI - Sub-national region -0.51 -0.40 0.29 HI - Ethnicity -0.91* -1.27*** 0.31 HI - Religion -0.747 0.28 0.01 Child non-stunting HI - Sub-national region -3.54*** -3.16*** 0.05 HI - Ethnicity -4.11*** -4.30*** 0.75 HI - Gender -4.03*** -4.03*** 0.90 HI - Religion -3.92*** -2.52** 0.08 Child survival HI - Sub-national region -3.73*** -3.47*** 0.11 HI - Ethnicity -4.03*** -3.54*** 0.40 HI - Gender -1.14 -1.14 0.14 HI - Religion -3.87*** -2.75** 0.09 Notes: 1) These estimates are obtained by regressing logarithmized country-year observations of HI as measured by Relative GGini Index on a time variable, 푌푒푎푟. 2) The coefficient on 푌푒푎푟 is, on average, the annualized rate of change (%) in HI reported in the table. 3) The regressions control for country fixed-effects, so that countries with more surveys do not drive the results. 4) ***, **, and * indicate statistical significance at 1%, 5%, and 10% levels, respectively. 5) P-value is the significance level of a chi-square test of the null hypothesis that the trends in HI with plutocratic and democratic weighting are not different from each other. Chi-square tests are conducted under the assumptions of Seemingly Unrelated/Related Regressions (SUR).

4. Robustness checks

First, the study finds that HI is lower when measured with plutocratic weighting, particularly religious and ethnic inequalities. But is this result driven by the lack of representativeness of the data across religious and ethnic groups? The DHS data are representative at the sub-national regional level, but not necessarily at other demographic disaggregation, such as religion and ethnicity.

One possible way of addressing this question is to focus on the results for sub-national regional inequalities, where the data are more representative, and investigate if the findings of the study still hold. As indicated earlier, in Fig. 1 and Appendix C, the levels in sub-national regional inequalities are lower with plutocratic weighting, though not pronounced or statistically significant.

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Another possible way of addressing the problem of representativeness is to pool the data across countries, for the sample sizes of population sub-groups to increase significantly. This approach is attractive for the measurement of religious inequalities in the Africa sub-sample, where there are 3 main religious categories in most countries, namely Christian, Muslim, and Other. (Ethnic groups are, by contrast, highly varied across countries in Africa.) Appendix H shows results for such an investigation, comparing the levels in religious inequalities with plutocratic and democratic weighting with respect to educational attainment, wealth, child non-stunting rate, and child survival rate.

Assuming Africa is one country, religious inequality is lower with plutocratic weighting, though this is marginal in terms of percentage or point differences. In terms of educational attainment, the GGini Index is 28 with plutocratic weighting and is 29 with democratic weighting. In terms of wealth, the GGini Index is 28 with plutocratic weighting and is 30 with democratic weighting. In terms of child non-stunting rate, the GGini Index is 9 with plutocratic weighting and is 9 with democratic weighting. In terms of child survival rate, the GGini Index is 3 with plutocratic weighting and is 4 with democratic weighting.

Figure 7: Pooling together religions in African countries Note: The bar graph is constructed from data covering 20 countries with 3 main religious groups, namely Christian, Muslim, and Other.

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However, the level of religious inequality is relatively high overall, comparing with the level of religious inequality at the country level; for example, religious inequality in educational attainment is 8 with plutocratic weighting and is 16 with democratic weighting. This is due to the fact that pooling the data means that we do not only account for inequality within countries but also inequality between countries, which tends to be generally greater. See tables in Appendix H.

Second, the study analyzes trends in HI with plutocratic weighting to show how trends differ depending on whether Relative, Intermediate, or Absolute GGini Index is used in measuring HI. As robustness checks, the trend analysis is repeated with democratic weighting. Table 5 shows these results and buttresses findings already discussed. In terms of educational attainment and wealth, Relative GGini Index generally increases reductions in HI than what would be suggested by Intermediate or Absolute GGini Indices. Absolute GGini Index in particular suggests that the gaps in sub-national, ethnic, gender, and regional inequalities in educational attainment and wealth have remained more or less that same in 2016 as they were in 1990 in most African countries, or have even widened. However, for child non-stunting and child survival, both Relative and Absolute GGini Indices have been falling, so that Intermediate GGini Index has also been falling. Taken together, progress against unequal opportunities in Africa are clearly observed in terms of child non-stunting and child survival, but not in terms of educational attainment and wealth.

Table 5: Trends in HI - Relative, Intermediate, Absolute - II Africa sub-sample Educational attainment Relative (%) Intermediate (%) Absolute (%) HI - Sub-national region -1.65*** -0.88** 0.77*** HI - Ethnicity -1.36** -0.19 1.17** HI - Gender -2.68*** -2.93*** -0.25 HI - Religion -1.94*** -1.48 0.46 Wealth HI - Sub-national region -0.40 0.96 1.36*** HI - Ethnicity -1.27*** -0.82 0.45 HI - Religion 0.28 1.94 1.66** Child non-stunting HI - Sub-national region -3.16*** -5.38*** -2.22*** HI - Ethnicity -4.30*** -7.62*** -3.32*** HI - Gender -4.03*** -7.10*** -3.07*** HI - Religion -2.52** -4.17* -1.65 Child survival HI - Sub-national region -3.47*** -6.51*** -3.03*** HI - Ethnicity -3.53*** -6.59*** -3.05*** HI - Gender -1.14 -1.89 -0.75 HI - Religion -2.747** -5.01** -2.26** Notes: 1) These estimates are obtained by regressing logarithmized country-year observations of HI on a time variable, 푌푒푎푟. 2) The coefficient on 푌푒푎푟 is, on average, the annualized rate of change (%) in HI reported in the 21 table. 3) The regressions control for country fixed-effects, so that countries with more surveys do not drive the results. 4) ***, **, and * indicate statistical significance at 1%, 5%, and 10% levels, respectively. 5. Discussion and conclusion

The study estimates different indices for measuring HI in the quest to better track the progress made against inequality of opportunities in Africa. The study demonstrates that the traditional approach to the measurement of HI, namely Relative GGini Index with plutocratic weighting, seems to belie the progress made against unequal opportunities, relative to what would be suggested by more egalitarian approaches. First, Relative GGini Index with plutocratic weighting generally lowers the levels in HI, particularly when there are minority religious and ethnic groups. Second, Relative GGini Index with plutocratic weighting generally suggests more rapid reductions in HI over time, particularly religious inequalities. Third, Relative GGini Index with plutocratic weighting generally embellishes the negative rate of reduction observed in horizontal inequalities in educational attainment and wealth, relative to what would usually be suggested by Intermediate and Absolute GGini Indices. Much of the reduction in horizontal inequalities in educational attainment and wealth in Africa is being driven by overall growth in living standards, and not necessarily the narrowing of absolute gaps in sub-national regional, ethnic, gender, or religious outcomes between 1990 and 2016.

It is, however, important to acknowledge that whichever measurement method is applied is not free of value judgments. The point is to caution that relatively low and falling levels of horizontal inequalities in developing countries observed in previous studies may not be robust to different measurement assumptions. This study highlights the value judgment embedded in available inequality indices for the measurement of HI. The choice between plutocratic and democratic weighting may reflect value judgments over efficiency and equity. The choice between Relative, Intermediate, and Absolute GGini Indices may reflect value judgments about whether people are sensitive to relative or absolute differences when comparing distributions, or a mix of both. For short, underneath this whole enterprise of measuring horizontal inequalites is a philosophical debate, which may be hard to resolve. Depending on which value judgment one holds, different conclusions may be reached altogether and the emphasis of policy may go in different directions.

Previous studies have similarly compared different measures of inequality and methods of weighting in the measurement of inequality, and have found results similar to the results of this study. Niño-Zarazúa, Roope and Tarp (2017) apply relative, intermediate, and absolute measures of inequality to investigate the trend in global income inequality between 1975 and 2010. The authors find that global income inequality has been falling with relative measures of inequality (e.g., Gini Index), but rising with absolute measures of inequality (e.g., Absolute Gini Index) and intermediate measures of inequality (e.g., Intermediate Gini Index). Analyzing consumption and wealth inequalities in India, Subramanian and Jayaraj (2013) find that inequality trends are sensitive to the measure of inequality. The authors find that both consumption and wealth

22 inequalities have been rising when one uses intermediate and relative inequality measures in India between 1961 and 2001, though relative measures suggest no trend. Milanovic (2016) compares the trend in global income inequality using plutocratic weighting of countries’ per capita income with democratic weighting of countries’ per capita income over the period between 1960 and 2010, an era of unprecedented globalization. Up until 2000, he finds a declining trend in global income inequality with plutocratic weighting but a worsening trend in global income inequality with democratic weighting. High per capita income growth rates in emerging markets, in populous countries such as China and India, has set off great convergence toward per capita income levels in industrialized countries. As a result, the between-country component of global income inequality has declined so drastically global income inequality has declined. However, once Milanovic (2016) applies democratic weighting, less populous countries in Africa, for instance, become equally important, and global income inequality worsens over time.

One worrying result of the study is the fact that sub-national regional gaps in educational attainment and wealth have widened over time in Africa. This may be both a cause and consequence of internal migration. Unlike other group categories the study analyzes, such as gender and ethnicity, one is able to change their sub-national regional location, even more easily once international borders are not involved. On the one hand, migration is more likely when there are sub-national regional gaps in development. People are more likely to move from less prosperous regions to more prosperous ones in search of greener pastures, or from regions with less academic infrastructure to regions with better ones to obtain high-quality education. On the other hand, migrants in more developed regions are likely to stretch sub-national regional gaps in outcomes further, especially if migrants get greater opportunities to spend more years in school or secure better jobs. As long as migration is both a cause and consequence of regional gaps, migration within developing countries is likely to remain a self-sustaining, persistent phenonemon. Internal migration is often associated with social problems, such as urban poverty, limited sanitation, and urban housing deficits. Further studies could investigate the direction of causation between HI and migration for appropriate policy interventions; e.g., the provision of public goods and social ameneties in less developed regions if causation runs from HI to migration. Unfortunately, the DHS program does not generally collect data on how people move between rural and urban areas, or betweeen sub-national regions, over time. Due to this data limitation, the study does not analyze migration.

Although horizontal inequalities have been somewhat persistent, the results of the study still provide a glimmer of hope for countries in Africa. Namely, most of the persistence observed in the data is related to educational attainment and wealth, which can be linked to an older age cohort, as opposed to the child non-stunting rate and child survival rate. The results of this study show that Relative, Absolute and Intermediate GGini Indices have been falling rapidly in terms child non-stunting and child survival. This is a robust finding that sub-national regional, gender, 23 ethnic, and religious gaps are shrinking over time, suggesting greater equalization of opportunities for the children in Africa. Their gender and conditions they are born into, such as the religion, ethnicity and regional location of their parents, seem to be having less and less bearing on their outcomes as time passes. It is good news that in the decades to come, there will possibly be greater equalization in outcomes such as educational attainment and wealth in Africa, as childhold nutrition and health translate into better schooling and labour market outcomes in the future (Case et al., 2002; Case et al., 2005; Almond and Currie, 2011).

Regardless of persistent horizontal inequalities in educational attainment and wealth, the study takes cognizance of the fact that there is still some progress in Africa in these outcomes. As a first step, the impressive growth in social outcomes, especially in terms of educational attainment, suggests that the outcomes of all groups have increased over time. For illustrative purposes, male years of schooling was 2.8 and female years of schooling was 1.8 for Senegal’s population aged 15 to 64 in 1993. In 2016, male years of schooling in Senegal increased to 4.5 and for females 3.2. The gender gap in educational attainment has remained more or less stable (i.e., 1 in 1993 and 1.3 in 2016). But there is some value in the fact that women are now more educated in Senegal than before, even if compared to men they have not made any progress.

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Appendix

Appendix A: DHS countries and survey years used for data analysis

List of countries and survey years – Africa sub-sample Surveys, No. Country N = 147 Survey years 1 Benin 4 1996, 2001, 2006, 2012 2 Burkina Faso 5 1993, 1999, 2003, 2010, 2014 3 Burundi 2 2010, 2012 4 Cameroon 4 1991, 1999, 2004, 2011 5 Central African Republic [CAR] 1 1995 6 Chad 2 1997, 2004 7 Comoros 2 1996, 2012 8 Democratic Republic of the 2 2007, 2014 Congo 9 Egypt 7 1992, 1995, 2000, 2003, 2005, 2008, 2014 10 Ethiopia 3 2000, 2005, 2011 11 Gabon 2 2000, 2012 12 Gambia, The 1 2013 13 Ghana 5 1993, 1998, 2003, 2008, 2014 14 Guinea 3 1999, 2005, 2012 15 Ivory Coast 4 1994, 1999, 2005, 2012 16 Kenya 5 1993, 1998, 2003, 2009, 2014 17 Lesotho 3 2004, 2009, 2014 18 Liberia 2 2007, 2013 19 Madagascar 4 1992, 1997, 2004, 2009 20 Malawi 6 1992, 2000, 2004, 2010, 2014, 2016 21 Mali 5 1996, 2001, 2006, 2013, 2015 22 Morocco 2 1992, 2004 23 Mozambique 5 1997, 2003, 2009, 2011, 2015 24 Namibia 4 1992, 2000, 2007, 2013 25 Niger 4 1992, 1998, 2006, 2012 26 Nigeria 7 1990, 1999, 2003, 2008, 2010, 2013, 2015 27 Republic of Congo 3 2005, 2009, 2012 28 Rwanda 7 1992, 2000, 2005, 2008, 2010, 2013, 2015 29 Sao Tome and Principe 1 2009 30 Senegal 9 1993, 1997, 2005, 2006, 2008, 2011, 2013, 2014, 2016 31 Sierra Leone 3 2008, 2013, 2016 25

32 South Africa 1 1998 33 Tanzania 9 1992, 1996, 1999, 2004, 2005, 2008, 2010, 2012, 2016 34 The Kingdom of eSwatinii 1 2007 (formerly, eSwatini) 35 Togo 2 1998, 2014 36 Uganda 7 1995, 2001, 2006, 2009, 2011, 2014, 2016 37 Zambia 5 1992, 1996, 2002, 2007, 2014 38 Zimbabwe 5 1994, 1999, 2006, 2011, 2015 Note: If a survey spans two or more consecutive years, one of the years is randomly selected for data analysis.

List of countries and survey years – Non-Africa sub-sample No. Country Region Survey, Survey years N = 103 1 Albania Europe 1 2009 2 Armenia Europe 4 2000, 2005, 2010, 2016 3 Azerbaijan Europe 1 2006 4 Bangladesh Asia 7 1994, 1997, 2000, 2004, 2007, 2011, 2014 5 Bolivia LAC 4 1994, 1998, 2003, 2008 6 Brazil LAC 1 1996 7 Cambodia LAC 4 2000, 2005, 2010, 2014 8 Colombia LAC 6 1990, 1995, 2000, 2005, 2010, 2015 9 Dominican LAC 6 1991, 1996, 1999, 2002, 2007, 2013 Republic 10 Guatemala LAC 3 1995, 1999, 2015 11 Guyana LAC 2 2005, 2009 12 Haiti LAC 4 1995, 2000, 2006, 2012 13 Honduras LAC 2 2006, 2012 14 India Asia 4 1993, 1999, 2006, 2016 15 Indonesia Asia 6 1991, 1994, 1997, 2003, 2007, 2012 16 Jordan Asia 6 1990, 1997, 2002, 2007, 2009, 2012 17 Kazakhstan Asia 2 1995, 1999 18 Kyrgyz Asia 2 1997, 2012 Republic 19 Maldives Asia 1 2009 20 Maldova Europe 1 2005 21 Nepal Asia 5 1996, 2001, 2006, 2011, 2016 22 Nicaragua LAC 2 1997, 2001 23 Pakistan Asia 3 1991, 2007, 2013 24 Paraguay LAC 1 1990

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25 Peru LAC 9 1992, 1996, 2000, 2006, 2008, 2009, 2010, 2011, 2012 26 Philippines, Asia 5 1993, 1998, 2003, 2008, 2013 The 27 Timor Leste Asia 1 2010 28 Turkey Europe 3 1993, 1998, 2003 29 Ukraine Europe 1 2007 30 Uzbekistan Europe 1 1996 31 Vietnam Asia 3 1997, 2002, 2005 32 Yemen Asia 2 1991, 2013 Notes: If a survey spans two or more consecutive years, one of the years is randomly selected for data analysis. LAC stands for Latin America and the Caribbean.

Appendix B: Harmonizing sub-national regions, ethnicities, and religions across surveys

Harmonizing sub-national regions across surveys – Africa sub-sample No. Country No. of List of regions regions 1 Benin 6 Atacora/Donga, Queme/Plateau, Mono/Couffo, Borgou/Alibori, Atlantique/Litoral, Collines/Zou 2 Burkina Faso 4 West, Center, North, East 3 Burundi 5 Bujumbura, North, Centre-East, West, South 4 Cameroon 4 Adamaoua/North/Far North, Northwest/Southwest, West/Littoral, Central/South/East 5 CAR 6 RS I, RS II, RS III, RS IV, RS V, Bangui 6 Chad 8 B.E.T., N'djamena, Chari Baguirmi, Logone Occidental, Mayo Kebbi, Bar Azoum, Ouaddai, Moyen Chari 7 Comoros 3 Moheli, Ndzouani, Ngazidja 8 Democratic 11 Kinshasha, Bandundu, Bas-Congo, Equateur, Kasai- Republic of occidental, Kasai-oriental, Katanga, Maniema, Nord- the Congo kivu, Orientale, Sud-kivu 9 Egypt 5 Lower Egypt - Rural, Lower Egypt - Urban, Upper Egypt - Rural, Upper Egypt - Urban, Urban Governorates 10 Ethiopia 11 Addis Ababa, Afar, Amhara, Benishangul-gumuz, Dire dawa, Gambela, Harari, Oromiya, Somali, Tigray, Snnp 11 Gabon 5 North, East, West, South, Big Cities 12 Gambia, The 8 Banjul, Basse, Brikama, Janjanbureh, Kanifing, Kerewan, Kuntaur, Mansakonko 13 Ghana 10 Ashanti, Brong Ahafo, Central, Eastern, Greater Accra, Northern, Upper East, Upper West, Volta, Western 14 Guinea 5 Conakry, Forest Guinea, Central Guinea, Upper Guinea, Lower Guinea

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15 Ivory Coast 10 Centre, North, North East, Centre East, West, South, South West, Centre North, Centre West, North West 16 Kenya 7 Central, Eastern, Coast, Nairobi, Nyanza, Rift Valley, Western 17 Lesotho 10 Berea, Butha-buthe, Leribe, Mafeteng, Maseru, Mohale's hoek, Mokhotlong, Quash's nek, Quthing, Thaba-tseka 18 Liberia 5 North Central, North Western, South Central, South Eastern A, South Eastern B 19 Madagascar 6 Toliary, Fianarantsoa, Antananarivo, Toamasina, Mahajanga, Antsiranana 20 Malawi 3 Central, North, South 21 Mali 6 Bamako, Kayes, Koulikoro, Sikasso, Segou, Mopti 22 Morocco 7 Central, North West, North Central, South Central, Oriental, South, Tensift 23 Mozambique 10 Cabo Delgado, Maputo Provincia, Gaza, Inhambane, Manica, Nampula, Niassa, Sofala, Tete, Zambezia 24 Namibia 4 Central, Northeast, Northwest, South 25 Niger 6 Niamey, Tillaberi, Dosso, Zinder/Diffa, Tahoua, Maradi 26 Nigeria 4 Southeast, Southwest, Northwest, Northeast 27 Republic of 4 Brazaville, Nord, Sud, Point Noire Congo 28 Rwanda 5 North, South, West, East, Kigali City 29 Sao Tome and 4 Região Centro, Região do Principe, Região Norte, Principe Região Sul 30 Senegal 4 Central, West, North East, South 31 Sierra Leone 4 Eastern, Northern, Western, Southern 32 South Bfrica 9 Western Cape, Eastern Cape, Northern Cape, Free State, Kwazulu Natal, North West, Gauteng, Mpumalanga, Northern Province 33 Tanzania 6 Central, Coastal, Lake, Northern, South, Southern Highlands 34 The Kingdom 4 Hhohho, Manzina, Shiselweni, Lubombo of eSwatinii (formerly, eSwatini) 35 Togo 6 Centrale, Kara, Lome, Plateaux, Savanes, Marities 36 Uganda 4 Western, Central, Eastern, Northern 37 Zambia 9 Central, Copperbelt, Eastern, Luapula, Lusaka, North- western, Southern, Northern, Western 38 Zimbabwe 9 Bulawayo, Manicaland, Mashonaland Central, Mashonaland East, Mashonaland West, Masvingo, Matebeleland North, Matebeleland South, Midlands 28

Note: CAR, Gambia, Sao Tome and Pricipe, South Africa, and eSwatinii have only one survey.

Harmonizing sub-national regions across surveys – Non-Africa sub-sample No. Country No. of List of regions regions 1 Albania 4 Central, Coastal, Mountain, Urban Tirana 2 Armenia 11 Aragatsotn, Ararat, Armavir, Gegharkunik, Lori, Kotayk, Shiarak, Syunik, Tavush, Vayots Dzor, Yerevan 3 Azerbaijan 9 Absheron, Aran, Baku, Dakhlik Shirvan, Ganja Gazakh, Guba Khachmaz, Lankaran, Shaki Zaqatala, Yukhari Karabakh 4 Bangladesh 5 Barisal, Chittagong, Dhaka, Khulna, Rajashahi, Sylhet 5 Bolivia 3 Altiplano, Llano, Valle 6 Brazil 7 Centro Leste, Centro Oeste, Nordeste, Norte, Rio de Janeiro, Sao Paulo, Sul 7 Cambodia 15 Banteay Mean Chey, Bat Dambang/Krong Pailin, Kampong Cham, Kampong Chhnang, Kampong Speu, Kampong Thum, Kampot/Krong Kaeb/Koh Kong/Krong Preah Sihanouk, krong kaeb, Kandal, Mondol kiri/Rotanak Kiri, Otdar Mean Chey/Siem Reap, Phnom Penh, Preah Vihear/Stueng Traeng/Kratie, Pursat, Svay Rieng, Takeo 8 Colombia 5 Atlantica, Bogota, Central, Oriental, Pacifica 9 Dominican 8 Region 0, Region 1, Region 2, Region 3, Region 4, Region 5, Republic Region 6, Region 7 10 Guatemala 7 Central, Metropolitan, North, Northeast, Northwest, Southeast, Southwest 11 Guyana 10 Region 1, Region 10, Region 2, Region 3, Region 4, Region 5, Region 6, Region 7, Region 8, Region 9 12 Haiti 3 Metropolitan Area, North, South 13 Honduras 16 Atlántida, Choluteca, Colón, Comayagua, Copán, Cortés, El Paraiso, Francisco morazán, Intibuca, La Paz, Lempira, Ocotepeque, Olancho, Santa Bárbara, Valle, Yoro 14 India 25 Andhra Pradesh, Arunachalpradesh, Assam, Bihar, Goa, Gujarat, Haryana, Himachal Pradesh, Karnataka, Kerala, Madhya Pradesh, Maharashtra, Manipur, Meghalaya, Mizoram, Nagaland, New Delhi, Orissa, Punjab, Rajasthan, Tamil Nadu, Tripura, Uttar Pradesh, West Bengal 15 Indonesia 8 Bali, Central Java, East Java, Jakarta, Outer Java-Bali I, Outer Java-Bali II, West Java/Banten, Yogyakarta 16 Jordan 3 Central, North, South 17 Kazakhstan 5 Region 1, Region 2, Region 3, Region 4, Region 5 18 Kyrgyz 4 Bishkek, East, North, South Republic

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19 Maldives 6 Malé, North, North Central, Central, South Central, South 20 Maldova 4 North, Center, South, Chisinau 21 Nepal 5 Central, Eastern, Far-western, Mid-western, Western 22 Nicaragua 17 Boaco, Carazo, Chinandega, Chontales, Estelí, Granada, Jinotega, Leon, Madriz, Managua, Matagalpa, Masaya, Nueva segovia, Raan, Raas, Rivas, Rio san juan 23 Pakistan 4 Balochistan, Khyber pakhtunkhwa, Punjab, Sindh 24 Paraguay 4 Asuncin and Ma, North, Center - South, East 25 Peru 13 A.A.C Ceres, Arequipa, Chavin, Grau, Ica, La Libertad, Libertadores, Lima/Callao, Loreto, Mari Tegui, Nor-oriental, San Martin, Ucayali 26 Philippines, 13 Bicol, Cagayan Valley, Central Luzon, Central Mindanao, The Central Visayas, Cordillera, Eastern Visayas, Ilocos, NCR, Northern Mindanao, Southern Mindanao, Southern Tagalog, Western Visayas 27 Timor 13 Aileu, Airnaro, Baucau, Bobonaro, Cova Lima, Dili, Ermera, Leste Liquica, Lautem, Manufahi, Manatuto, Oecussi, Viqueque 28 Turkey 5 West, South, Central, North, East 29 Ukraine 5 North, Central, East, South, West 30 Uzbekistan 5 Region 1, Region 2, Region 3, Region 4, Tashkent 31 Vietnam 3 Center, North, South 32 Yemen 2 North & West, South & East Note: Albania, Brazil, Maldives, Moldova, Timor Leste, and Ukraine have only one surevey with observations for sub-national region.

Harmonizing ethnicities across surveys – Africa sub-sample No. Country No. of List of ethnicities ethnicities 1 Benin 8 Adja, Bariba,Betamaribe, Dendi, Fon, Peulh, Yoa/Lokpa, Yoruba 2 Burkina Faso 8 Mossi, Fulani, Gurma, Bobo, Gurunsi, Senuofo, Dioula, Lobi 3 Cameroon 46, 46, 10 Harmonized across 2 surveys - 1998, 2004; survey in 2011 cannot be harmonized 4 Central 9 Banda, Gbaya, Haoussa, Mandjia, Mboum, Ngbaka- African bantou, Sara, Yakoma-sango, Zande-nzakara Republic [CAR] 5 Chad 12 Arab, Baguirmien, Fitri-Batha, Gorane, Hadjarai, Kanem-Bornou, Peul, Sara, Ouaddai, Kebbi, Tandjile, Lac Iro

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6 Democratic 9 Bakongo Nord & Sud; Bas-kasai and Kwilu-kwngo; Republic of Basele-k , man. and Kivu; Uele lac albert; Ubangi et the Congo itimbiri; Cuvette central; Kasai, katanga, tanganika; Pygmy; Lunda 7 Ethiopia 54, 67, 59 Not harmonized across 3 surveys 8 Gabon 8 Fang, Kota-kele, Mbede-teke, Myene, Nzabi-duma, Okande-tsogho, Pygmee, Shira-punu/vili 9 Gambia, The 10 Bambara, Creole/Aku Marabout, Fula/Tukulur/Lorobo, Jola/Karoninka, Mandinka/Jahanka, Manjago, Non-Gambian, Serahuleh, Serere, Wollof 10 Ghana 7 Akan, Ga/Dangme, Ewe, Mole-Dagbani, Gruma, Grussi, Guan 11 Guinea 6 Guerzé, Kissi, Malinké, Soussou, Peulh, Toma 12 Ivory Coast 64, 6, 73 Not harmonized across 3 surveys 13 Kenya 10 Kalenjin, Kamba, Kikuyu, Taita/Taveta, Luo, Meru/Embu, Mijikenda/Swahili, Somali, Luhya, Kisii 14 Liberia 17 Bassa, Gbani, Belle, Dey, Gio, Gola, Grebo, Kissi, Kpelle, Krahn, Kru, Lorma, Mandingo, Mano, Mende, Marpo, Vai 15 Malawi 8 Chewa, Lomwe, Ngoni, Nkhonde, Sena, Tonga, Tumbuka, Yao 16 Mali 9 Bambara, Malinke, Sonrai, Snoufo/Minianka, Sarkole/Soninke/Marka, Bobo, Tamacheck, Peulh, Dogon 17 Mozambique 6, 21 Not harmonized 18 Namibia 9 Afrikaans, Damars/Nama, Herero, English, Tswana, Oshiwambo, San, Caprivi languages, Kavango languages 19 Niger 8 Arab, Djerma, Gourmantche, Peul, Touareg, Haoussa, Kanouri, Toubou 20 Nigeria 10, 317 Not harmonized 21 Republic of 67, 11 Not harmonized Congo 22 Rwanda 3 Hutu, Tutsi, Twa 23 Senegal 6 Diola, Soninke, Wolof, Mandingue, Serer, Poular 24 Sierra Leone 7 Kono, Mende, Limba, Loko, Temne, Mandingo, Sherbro 25 Togo 5 Adja-Ewe, Akposso-Akebou, Ana-ife, Kabye/Tem, Para-gourma/Akan 26 Uganda 17 Acholi, Alur, Atesa, Baganda, Bakiga, Banyankole, Basoga, Langi, Madi, Mufumbira, Mugwere, Mukonjo,

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Mutooro, Munyarwanda, Munyoro, Ngakaramajong, Lugbara 27 Zambia 40 Bemba, Bisa, Chewa, Kaonde, Lala, Subiya, Lamba, Mambwe, Mbunda, Namwanga, Tumbuka, Lunda, Lozi, Ushi, Nsenga, Lenje, Luchazi, Chishinga, Kunda, Chokwe, Kabende, Bwile, Ila, Kunda, Lungu, Luvale, Mashi, Ngoni, Ngumbo, Nkoya, Nyango, Tonga, Soli, Tabwa, Toka-leya, Unga, Totela, Kwanga, Sala, Swawka 28 Zimbabwe 4 Black, White, Colored, Asian Note: CAR, Liberia, Namibia, and Zimbabwe have observations for ethnicity in only one survey.

Harmonizing ethnicities across surveys – Non-Africa sub-sample No. Country No. of List of ethnicities ethnicities 1 Albania 2 Albanian, Non Albanian 2 Armenia 2 Armenian, Non Armenian 3 Azerbaijan 2 Azerbaijani, Other 4 Bolivia 3 Aymara, Guarani, Quechua 5 Brazil 3 Mixed, Other, White 6 Guatemala 2 Indian, Ladino 7 Guyana 4 African, Amerindian, Indian, Mixed 8 Honduras 9 Garifuna, Lenca, Maya chorti, Misquito, Negro Inglés, Nahoa, Pech (paya), Tawaka (sumo), Tolupán 9 India 3 Other, Scheduled Caste, Scheduled Tribe 10 Kazakhstan 5 German, Kazakh, Korean, Russian, Ukranian 11 Moldova 6 Bulgarian, Gagauzan, Moldovan, Romanian, Russian, Ukrainian 12 Nepal 77, 75, 10, Hill Brahmin, Hill Chhetri, Hill Dalit, Hill Janajati, 10 Muslim, Newar, Other Terai Caste, Terai Brahmin/Chhetri, Terai Dalit, Terai; harmonized across 2 surveys, not harmonized across 2 surveys 13 Pakistan 19 Balochi, Balti, Baruhi, Brushaski, Chitrali/Khwar, English, Farsi, Hindko, Kashmiri, Marwari, Pahari, Potowari, Punjabi, Pushto, Shina, Sindhi, Siraiki, Urdu, Wakhi 14 Philippines, 24 Akeanon/Aklanon, Bicolano, Bisaya, Boholano, The Cebuano, Chavakano, Cuyano, Ibaloi, Ifugao, Igorot, Ilocano, Ilonggo, Kankanaey, Kapampangan, Karay-a, Maguindanaon, Manabo, Maranao, Parggalatok/Panggasinense, Sama, Suriganon, Tagalog, Tausog, Waray Note: Observations for ethnicity are available in only one survey for all countries, except Nepal and India.

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Harmonizing religions across surveys – Africa sub-sample No. Country No. of List of religions religions 1 Benin 4 Christian, Muslim, Traditionalist, Other 2 Burkina Faso 4 Christian, Muslim, Traditionalist, Other 3 Burundi 3 Christian, Muslim, Other 4 Cameroon 3 Christian, Muslim, Other 5 Central African Republic [CAR] 3 Christian, Muslim, Other 6 Chad 3 Christian, Muslim, Other 7 Comoros 3 Muslim, Other 8 Democratic Republic of the 3 Christian, Muslim, Traditionalist, Other Congo 9 Ethiopia 3 Christian, Muslim, Other 10 Gabon 3 Christian, Muslim, Other 11 Gambia, The 2 Muslim, Other 12 Ghana 3 Christian, Muslim, Other 13 Guinea 4 Christian, Muslim, Traditionalist, Other 14 Ivory Coast 2 Christian, Muslim 15 Kenya 3 Christian, Muslim, Other 16 Lesotho 2 Christian, Other 17 Liberia 3 Christian, Muslim, Other 18 Madagascar 4 Christian, Muslim, Traditionalist, Other 19 Malawi 3 Christian, Muslim, Other 20 Mali 3 Christian, Muslim, Other 21 Mozambique 3 Christian, Muslim, Other 22 Namibia 2 Christian, Other 23 Niger 3 Christian, Muslim, Other 24 Nigeria 3 Christian, Muslim, Other 25 Republic of Congo 3 Christian, Muslim, Other 26 Rwanda 3 Christian, Muslim, Other 27 Sao Tome and Principe 2 Christian, Other 28 Senegal 3 Christian, Muslim, Other 29 Sierra Leone 3 Christian, Muslim, Other 30 Tanzania 3 Christian, Muslim, Other 31 The Kingdom of eSwatinii 3 Christian, Zionist, Other (formerly, eSwatini) 32 Togo 4 Christian, Muslim, Other, Traditionalist 33 Uganda 3 Christian, Muslim, Other 34 Zambia 3 Christian, Muslim, Other 35 Zimbabwe 3 Christian, Other, Traditionalist Note: Burundi, Comoros, Sao Tome and Principe, and eSwatinii have only one survey with observations for religion.

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Harmonizing religion across surveys – Non-Africa sub-sample No. Country No. of religions List of religions 1 Albania 3 Christian, Muslim, Other 2 Armenia 2 Christian, Other 3 Azerbaijan 2 Muslim, Other 4 Bangladesh 3 Hindu, Muslim, Other 5 Brazil 3 Catholic, Other, Protestant 6 Cambodia 4 Buddhist, Christian, Muslim, Other 7 Dominican Republic 3 Catholic, Evangelical, Other 8 Guatemala 3 Catholic, Evangelical, Other 9 Guyana 4 Hindu, Christian, Muslim, Other 10 Haiti 3 Catholic, Protestant, Other 11 Honduras 3 Catholic, Protestant, Other 12 India 5 Christian, Hindu, Muslim, Other, Sikh 13 Indonesia 4 Hindu, Muslim, Christian, Other 14 Kazakhstan 3 Christian, Muslim, Other 15 Moldova 2 Orthodox, Other 16 Nepal 4 Buddhist, Hindu, Muslim, Other 17 Philippines, The 4 Catholic, Muslim, Other, Protestant 18 Timor Leste 2 Catholic, Other 19 Turkey 2 Muslim, Other 20 Ukraine 2 Christian, Other Note: Most countries have observations for religion in only one survey, except Bangladesh, Cambodia, Dominican Republic, Haiti, Indonesia, and Nepal that have observations for religion in at least two surveys for harmonization.

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Appendix C: Levels in horizontal inequalities – bar charts

Fig. C1: HI in wealth – plutocratic vs. democratic weighting

Fig. C2: HI in child non-stunting – plutocratic vs. democratic weighting

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Fig. C3: HI in child survival – plutocratic vs. democratic weighting

Appendix D: Regional heterogeneity in HI levels

Fig. D1: HI in wealth across developing regions of the world

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Fig. D2: HI in child non-stunting across developing regions of the world

Fig. D3: HI in child survival across developing regions of the world

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Appendix E: Horizontal inequality across countries – plutocratic vs. democratic weighting

Fig. E1: Religious inequality in wealth Fig. E2: Ethnic inequality in wealth

Fig. E3: Regional inequality in wealth Fig. E4: Religious inequality in child non-stunting

Fig. E5: Ethnic inequality in child non-stunting Fig. E6: Regional inequality in child non- stunting 38

Fig. E7: Gender inequality in child non-stunting Fig. E8: Religious inequality in child survival

Fig. E9: Ethnic inequality in child survival Fig. E10: Regional inequality in child survival

Fig. E11: Gender inequality in child survival

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Appendix F: Populations shares of religious, ethnic, sub-national regional, and gender groups

Fig. F1: Population shares of religious groups across countries (Africa sub-sample)

Fig. F2: Population shares of religious groups across countries (Non-Africa sub-sample)

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Fig. F3: Population shares of ethnic groups across countries (Africa sub-sample)

Fig. F4: Population shares of ethnic groups across countries (Non-Africa sub-sample)

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Fig. F5: Population shares of sub-national regional groups across countries (Africa sub-sample)

Fig. F6: Population shares of sub-national regional groups across countries (Non-Africa sub- sample) 42

Fig. F7: Population shares of gender groups across countries (Africa sub-sample)

Fig. F8: Population shares of gender groups across countries (Non-Africa sub-sample) Notes: 1) In all the graphs in Appendix F, each color represents the share of one religious, ethnic, sub-national regional, or gender group in the population, averaged over all available surveys. 2) Only sub-national regions, ethnicities, and religions that have been harmonized across surveys have been included.

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Appendix G: Trends in horizontal inequality – heterogeneity across African countries

Table G1: Rate of change (%) in HI - sub-national regional inequality in educ. attainment Country Relative Intermediate Absolute Benin -1.29 0.87 2.16 Burkina Faso -0.72 1.82 2.54 Burundi 4.32 5.72 1.41 Cameroon -1.34 -0.52 0.82 Chad 3.60 9.23 5.63 Comoros -2.58 -1.00 1.59 DR Congo -4.20 -6.73 -2.53 Egypt -3.18 -4.98 -1.80 Ethiopia -5.20 -4.50 0.70 Gabon -3.90 -6.07 -2.18 Ghana -1.26 -1.14 0.12 Guinea -1.01 1.77 2.78 Ivory Coast -1.73 -2.91 -1.19 Kenya -0.72 0.22 0.94 Lesotho -1.70 -2.08 -0.38 Liberia 15.30 38.46 23.17 Madagascar -4.04 3.62 7.65 Malawi -3.09 -3.75 -0.66 Mali -1.64 0.20 1.83 Morocco -2.23 -1.59 0.65 Mozambique -1.68 0.81 2.49 Namibia -2.44 -2.75 -0.32 Niger -0.79 1.50 2.30 Nigeria -0.61 0.10 0.71 Republic of Congo -2.12 -2.65 -0.53 Rwanda 0.12 1.81 1.69 Senegal -2.42 -2.67 -0.26 Sierra Leone -7.91 -11.12 -3.21 Tanzania 0.85 3.43 2.58 Togo -1.49 0.09 1.58 Uganda -0.71 0.58 1.29 Zambia -0.98 -0.72 0.27 Zimbabwe -1.91 -2.57 -0.66

Table G2: Rate of change (%) in HI - gender inequality in educ attainment Country Relative Intermediate Absolute Benin -1.90 -0.34 1.55 Burkina Faso -1.81 -0.35 1.45 Burundi -6.04 -14.99 -8.95 Cameroon -3.14 -4.07 -0.93 44

Chad -2.51 -1.12 1.39 Comoros -4.80 -5.43 -0.63 DR Congo -2.25 -2.83 -0.58 Egypt -4.29 -7.21 -2.92 Ethiopia -3.78 -1.66 2.12 Gabon -6.01 -10.29 -4.29 Ghana -2.57 -3.75 -1.19 Guinea -1.91 -0.02 1.89 Ivory Coast -1.16 -0.77 0.39 Kenya -4.47 -7.36 -2.89 Lesotho -2.11 -2.91 -0.80 Liberia -3.14 -3.55 -0.40 Madagascar -6.94 -2.19 4.75 Malawi -4.37 -6.31 -1.94 Mali -0.99 1.43 2.41 Morocco -2.57 -2.26 0.31 Mozambique -3.99 -3.81 0.18 Namibia 8.49 19.10 10.61 Niger -0.27 2.55 2.82 Nigeria -2.34 -2.55 -0.21 Republic of Congo -3.10 -4.62 -1.51 Rwanda -4.14 -6.69 -2.56 Senegal -1.91 -1.65 0.25 Sierra Leone -8.11 -11.53 -3.42 Tanzania -3.54 -5.36 -1.81 Togo -2.26 -1.44 0.82 Uganda -4.24 -6.48 -2.24 Zambia -2.62 -4.02 -1.40 Zimbabwe -3.38 -5.50 -2.12

Table G3: Rate of change (%) in HI - religious inequality in educ attainment Country Relative Intermediate Absolute Benin -3.03 -2.38 0.66 Burkina Faso -2.12 -0.85 1.27 Cameroon -3.61 -4.81 -1.20 Chad 0.45 5.66 5.22 DR Congo -3.41 -5.05 -1.64 Ethiopia -6.64 -5.28 1.35 Gabon -0.16 1.16 1.32 Ghana -2.33 -3.18 -0.85 Guinea -1.44 1.50 2.94 Ivory Coast -1.44 -0.62 0.82 Kenya 2.59 6.54 3.96

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Lesotho -1.21 -1.20 0.00 Liberia -3.77 -6.20 -2.44 Madagascar -0.17 -0.97 -0.79 Malawi -2.38 -2.53 -0.14 Mali -5.31 -5.93 -0.62 Mozambique -2.94 -1.82 1.12 Namibia -1.65 -1.94 -0.29 Niger -9.88 -16.19 -6.31 Nigeria -0.21 1.14 1.35 Republic of Congo 11.63 24.47 12.84 Rwanda -7.98 -14.14 -6.16 Senegal -2.61 -2.58 0.02 Sierra Leone -7.98 -10.47 -2.49 Tanzania -2.27 -3.09 -0.82 Togo -2.90 -2.79 0.11 Uganda 0.18 2.58 2.40 Zambia 1.36 4.11 2.74 Zimbabwe -6.40 -11.55 -5.14

Table G4: Rate of change (%) in HI - ethnic inequality in educ attainment Country Relative Intermediate Absolute Benin -2.43 -1.14 1.30 Burkina Faso 2.48 8.21 5.73 Chad 0.18 5.27 5.09 DR Congo -3.51 -5.23 -1.73 Gabon -2.94 -4.30 -1.36 Ghana -1.39 -1.34 0.04 Guinea -1.90 0.62 2.51 Kenya -0.32 0.84 1.16 Malawi -2.74 -3.24 -0.50 Mali -3.18 -1.67 1.51 Niger 0.15 4.16 4.01 Senegal -3.30 -3.23 0.07 Sierra Leone -6.55 -7.32 -0.77 Togo -4.12 -5.29 -1.17 Uganda -2.37 -2.46 -0.09 Zambia -3.96 -6.55 -2.59

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Table G5: Rate of change (%) in HI - sub-national regional inequality in wealth Country Relative Intermediate Absolute Benin -0.41 0.86 1.27 Burkina Faso -0.64 1.24 1.87 Burundi 4.28 7.50 3.22 Cameroon 5.63 12.45 6.81 Chad -1.68 1.15 2.82 Comoros -3.54 -3.57 -0.02 DR Congo -1.46 -4.01 -2.55 Egypt -9.75 -21.89 -12.14 Ethiopia -3.48 -3.13 0.34 Gabon -4.15 -9.02 -4.88 Ghana -2.01 -2.22 -0.20 Guinea -0.52 1.88 2.40 Ivory Coast -2.34 -5.01 -2.67 Kenya -0.94 -0.38 0.56 Lesotho -1.22 1.73 2.95 Liberia 14.43 40.17 25.74 Madagascar 0.01 2.55 2.55 Malawi 4.09 10.34 6.25 Mali -2.15 -1.73 0.41 Morocco -5.48 -9.67 -4.19 Mozambique -0.46 2.70 3.17 Namibia -2.43 -2.89 -0.46 Niger -1.51 -0.64 0.87 Nigeria 0.81 2.38 1.57 Republic of Congo -3.93 -5.03 -1.09 Rwanda 2.86 9.25 6.39 Senegal -1.60 -0.96 0.64 Sierra Leone -2.13 -2.37 -0.24 Tanzania 1.64 4.86 3.22 Togo 0.17 2.18 2.01 Uganda -0.05 2.09 2.14 Zambia 0.33 0.48 0.15 Zimbabwe -1.12 -1.96 -0.83

Table G6: Rate of change (%) in HI - religious inequality in wealth Country Relative Intermediate Absolute Benin -2.58 -3.43 -0.84 Burkina Faso -3.42 -4.74 -1.32 Cameroon -0.78 0.32 1.09 Chad -8.01 -6.87 1.14 DR Congo 1.83 -2.45 -4.28

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Ethiopia -10.64 -18.68 -8.04 Gabon -2.81 -6.47 -3.66 Ghana -4.06 -6.65 -2.59 Guinea 0.53 4.03 3.49 Ivory Coast -0.63 -0.84 -0.21 Kenya -4.13 -6.54 -2.42 Lesotho 0.00 4.45 4.45 Liberia -7.79 -10.64 -2.85 Madagascar 2.50 1.44 -1.06 Malawi 4.30 10.29 5.98 Mali -1.72 -1.41 0.31 Mozambique -3.87 -3.70 0.17 Namibia 20.70 42.45 21.74 Niger -8.09 -12.69 -4.60 Nigeria 1.64 3.77 2.13 Republic of Congo 6.17 15.00 8.82 Rwanda -0.52 5.87 6.39 Senegal 3.46 7.86 4.40 Sierra Leone -7.60 -14.22 -6.62 Tanzania 0.97 1.50 0.53 Togo -1.51 -1.47 0.03 Uganda 0.84 4.17 3.33 Zambia 6.15 12.95 6.80 Zimbabwe -3.04 -6.12 -3.08

Table G7: Rate of change (%) in HI - ethnic inequality in wealth Country Relative Intermediate Absolute Benin -2.06 -2.38 -0.33 Burkina Faso 2.05 6.07 4.02 Chad -1.27 6.54 7.81 DR Congo -3.03 -12.12 -9.09 Gabon -3.27 -7.35 -4.08 Ghana -1.35 -1.26 0.10 Guinea -0.05 2.94 2.99 Kenya -0.19 1.61 1.80 Malawi 2.73 7.10 4.38 Mali -0.32 1.42 1.74 Niger 3.22 10.10 6.88 Senegal -1.97 -1.89 0.08 Sierra Leone -7.33 -13.20 -5.87 Togo -2.10 -2.73 -0.63 Uganda -1.09 0.37 1.46 Zambia -1.75 -2.85 -1.10

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Table G8: Rate of change (%) in HI - sub-national regional inequality in child non-stunting Country Relative Intermediate Absolute Benin 2.03 3.36 1.34 Burkina Faso -3.94 -6.70 -2.76 Cameroon -7.10 -12.92 -5.82 Chad 9.39 18.56 9.17 Comoros -0.46 -0.03 0.42 DR Congo -0.71 -1.72 -1.01 Egypt 0.62 1.60 0.98 Ethiopia 0.96 3.18 2.21 Gabon -5.92 -10.77 -4.85 Ghana -3.57 -6.06 -2.50 Guinea -3.78 -6.37 -2.59 Ivory Coast -5.82 -10.62 -4.80 Kenya 0.27 0.72 0.45 Lesotho -1.32 -2.31 -0.99 Liberia -12.15 -20.53 -8.37 Madagascar -8.83 -15.43 -6.59 Malawi -6.06 -9.99 -3.93 Mali -3.14 -5.28 -2.14 Morocco -0.91 -1.30 -0.40 Mozambique -0.25 -0.52 -0.27 Namibia -5.21 -9.60 -4.38 Niger -2.46 -3.60 -1.15 Nigeria 1.64 3.76 2.12 Republic of Congo -1.50 -0.60 0.90 Rwanda -3.29 -4.88 -1.59 Senegal -1.81 -3.13 -1.32 Sierra Leone -2.22 -4.17 -1.95 Tanzania -2.47 -4.26 -1.78 Togo -4.57 -7.98 -3.41 Uganda -8.33 -14.60 -6.27 Zambia -1.94 -3.70 -1.76 Zimbabwe -6.47 -12.73 -6.26

Table G9: Rate of change (%) in HI - gender inequality in child non-stunting Country Relative Intermediate Absolute Benin -18.12 -36.89 -18.77 Burkina Faso 0.15 1.48 1.33 Cameroon -6.42 -11.72 -5.30

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Chad -24.12 -48.30 -24.17 Comoros -6.83 -12.78 -5.95 DR Congo 19.29 38.28 18.99 Egypt 6.53 13.42 6.89 Ethiopia 5.50 12.25 6.75 Gabon -4.66 -8.26 -3.59 Ghana -7.86 -14.64 -6.79 Guinea -5.39 -9.59 -4.20 Ivory Coast -6.47 -11.85 -5.37 Kenya -4.29 -8.40 -4.10 Lesotho 2.37 5.06 2.69 Liberia -1.48 0.48 1.96 Madagascar -9.77 -17.30 -7.53 Malawi -10.98 -19.84 -8.85 Mali -11.09 -21.18 -10.09 Morocco 0.07 0.64 0.58 Mozambique -1.52 -3.06 -1.54 Namibia -8.94 -17.05 -8.11 Niger -7.00 -12.69 -5.69 Nigeria 4.27 9.05 4.78 Republic of Congo -24.48 -46.56 -22.08 Rwanda -1.49 -1.11 0.38 Senegal 1.34 3.17 1.83 Sierra Leone -38.24 -76.22 -37.98 Tanzania 0.48 1.71 1.24 Togo -17.88 -34.60 -16.72 Uganda -9.88 -17.68 -7.80 Zambia 1.03 2.22 1.19 Zimbabwe 3.78 7.77 3.99

Table G10: Rate of change (%) in HI - religious inequality in child non-stunting Country Relative Intermediate Absolute Benin -6.37 -13.40 -7.02 Burkina Faso -1.87 -2.55 -0.69 Cameroon -8.68 -16.24 -7.56 Chad 5.12 10.19 5.07 DR Congo -0.04 -0.37 -0.33 Ethiopia 10.97 23.19 12.22 Gabon -6.44 -11.81 -5.36 Ghana -5.43 -9.78 -4.36 Guinea -7.47 -13.74 -6.27 Ivory Coast -4.25 -7.46 -3.21 Kenya -6.50 -12.81 -6.31 Lesotho -4.03 -7.77 -3.74 50

Liberia -15.30 -27.18 -11.88 Madagascar -12.69 -23.14 -10.45 Malawi -5.48 -7.71 -2.23 Mali -5.85 -10.70 -4.85 Mozambique 2.29 4.55 2.26 Namibia -1.35 -1.88 -0.52 Niger -13.27 -25.44 -12.17 Nigeria 3.71 7.92 4.21 Republic of Congo -4.88 -7.36 -2.48 Rwanda -2.26 -4.51 -2.26 Senegal 7.99 14.63 6.64 Sierra Leone 16.02 32.28 16.26 Tanzania -0.63 -0.80 -0.17 Togo -4.94 -8.72 -3.78 Uganda -11.49 -20.91 -9.42 Zambia 1.70 3.57 1.86 Zimbabwe -6.08 -12.04 -5.96

Table G11: Rate of change (%) in HI - ethnic inequality in child non-stunting Country Relative Intermediate Absolute Benin -1.86 -4.34 -2.48 Burkina Faso -1.87 -2.57 -0.70 Chad 5.67 11.31 5.64 DR Congo 1.80 3.29 1.49 Gabon -4.49 -7.82 -3.33 Ghana -4.82 -8.57 -3.75 Guinea -6.70 -12.19 -5.49 Kenya 1.51 3.17 1.65 Malawi -14.21 -25.17 -10.96 Mali -2.61 -4.22 -1.60 Namibia -1.23 -2.25 -1.02 Niger -0.58 -0.05 0.52 Senegal -0.43 -0.35 0.08 Sierra Leone 3.64 7.47 3.83 Togo -9.82 -18.53 -8.71 Uganda -7.58 -13.21 -5.63 Zambia -4.24 -8.22 -3.98

Table G12: Rate of change (%) in HI - sub-national regional inequality in child survival Country Relative Intermediate Absolute Benin -2.56 -4.51 -1.95 Burkina Faso -0.23 -0.08 0.16 Cameroon -0.58 -1.23 -0.65 51

Chad 3.07 5.92 2.85 Comoros -11.91 -23.46 -11.55 DR Congo -3.65 -6.71 -3.06 Egypt -8.33 -16.37 -8.04 Ethiopia -10.03 -19.37 -9.34 Gabon -8.39 -16.65 -8.26 Ghana -3.16 -6.05 -2.88 Guinea 2.82 6.22 3.40 Ivory Coast 3.02 6.29 3.27 Kenya -7.75 -15.21 -7.46 Lesotho -1.30 -2.31 -1.01 Liberia 15.62 31.51 15.90 Madagascar -3.82 -7.05 -3.23 Malawi 0.40 1.58 1.18 Mali -6.90 -12.88 -5.98 Morocco -8.87 -17.50 -8.62 Mozambique -6.53 -12.13 -5.61 Namibia -1.28 -2.42 -1.15 Niger -3.47 -5.76 -2.29 Nigeria -4.03 -7.46 -3.43 Republic of Congo -8.95 -17.26 -8.31 Rwanda -12.27 -23.46 -11.19 Senegal -3.76 -7.09 -3.32 Sierra Leone 14.80 29.29 14.49 Tanzania -2.39 -4.58 -2.19 Togo -1.01 -1.67 -0.66 Uganda -6.39 -12.30 -5.90 Zambia -4.43 -8.21 -3.78 Zimbabwe -1.21 -2.29 -1.07

Table G13: Rate of change (%) in HI - gender inequality in child survival Country Relative Intermediate Absolute Benin 2.70 6.02 3.32 Burkina Faso -2.53 -5.15 -2.62 Cameroon -7.17 -14.37 -7.20 Chad 16.48 33.03 16.56 Comoros -20.39 -40.42 -20.04 DR Congo -21.16 -41.72 -20.55 Egypt 1.17 2.63 1.45 Ethiopia -5.51 -10.32 -4.81 Gabon 7.32 14.77 7.45 Ghana 5.46 11.20 5.74 Guinea -0.14 0.31 0.45 Ivory Coast 7.98 16.29 8.32 52

Kenya 3.39 7.05 3.66 Lesotho 1.57 3.44 1.86 Liberia -12.28 -24.39 -12.12 Madagascar -11.15 -21.71 -10.56 Malawi 5.83 12.52 6.69 Mali 10.86 22.22 11.35 Morocco 11.10 22.46 11.35 Mozambique -14.99 -29.07 -14.08 Namibia -6.62 -13.11 -6.49 Niger -4.59 -8.02 -3.43 Nigeria -5.90 -11.46 -5.57 Republic of Congo 20.58 41.79 21.21 Rwanda -0.24 -0.04 0.21 Senegal -2.54 -4.61 -2.07 Sierra Leone 5.52 10.81 5.29 Tanzania -4.35 -8.51 -4.16 Togo -15.17 -29.97 -14.81 Uganda 5.86 11.99 6.12 Zambia -0.38 -0.11 0.26 Zimbabwe -1.89 -3.68 -1.79

Table G14: Rate of change (%) in HI - religious inequality in child survival Country Relative Intermediate Absolute Benin -6.00 -11.37 -5.37 Burkina Faso -0.97 -1.56 -0.58 Cameroon -2.29 -4.59 -2.30 Chad -2.72 -5.36 -2.64 DR Congo -5.67 -10.73 -5.07 Ethiopia -26.46 -52.22 -25.76 Gabon 7.23 14.58 7.36 Ghana -2.19 -4.10 -1.91 Guinea 1.84 4.28 2.44 Ivory Coast 7.13 14.55 7.41 Kenya -6.92 -13.57 -6.65 Lesotho -7.56 -14.20 -6.65 Liberia 7.07 14.29 7.22 Madagascar -7.02 -13.44 -6.42 Malawi -10.89 -21.07 -10.17 Mali -1.18 -1.44 -0.26 Mozambique -3.72 -6.52 -2.80 Namibia -0.49 -0.85 -0.36 Niger 1.47 4.18 2.71 Nigeria -6.41 -12.38 -5.97 Republic of Congo -14.19 -27.74 -13.56 53

Rwanda -7.14 -13.79 -6.65 Senegal 7.48 15.54 8.06 Sierra Leone -30.55 -61.41 -30.86 Tanzania -8.83 -17.45 -8.62 Togo -2.97 -5.58 -2.61 Uganda -5.59 -10.68 -5.09 Zambia 0.33 1.30 0.97 Zimbabwe -9.95 -19.81 -9.86

Table G15: Rate of change (%) in HI - ethnic inequality in child survival Country Relative Intermediate Absolute Benin -0.03 0.56 0.59 Burkina Faso -0.59 -0.83 -0.23 Chad 3.54 7.20 3.67 DR Congo -8.50 -16.41 -7.91 Gabon -1.18 -2.26 -1.07 Ghana -3.48 -6.68 -3.20 Guinea -1.11 -1.64 -0.53 Kenya -6.36 -12.45 -6.09 Malawi -6.02 -11.32 -5.29 Mali -5.87 -10.81 -4.94 Namibia 5.66 11.50 5.84 Niger -15.35 -29.45 -14.10 Senegal -4.93 -9.47 -4.54 Sierra Leone 13.35 26.29 12.94 Togo -3.31 -6.28 -2.97 Uganda -2.87 -5.32 -2.45 Zambia -3.94 -7.07 -3.13

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Appendix H: Horizontal inequality – pooling together religions in all African countries

Table H1: Religious inequality - Africa sub-sample with plutocratic weighting GE(0) GE(1) Gini

Estimate Share (%) Estimate Share (%) Educational attainment 0.17095 100 0.13049 100 27.838 Within-country inequality 0.04649 27 0.03439 26 Between-country inequality 0.12446 73 0.09609 74 Wealth 0.13371 100 0.12338 100 28.16 Within-country inequality 0.02083 16 0.01591 13 Between-country inequality 0.11288 84 0.10747 87 Child non-stunting rate 0.0138 100 0.01386 100 9.533 Within-country inequality 0.0051 37 0.00502 36 Between-country inequality 0.0087 63 0.00884 64 Child survival rate 0.00198 100 0.00195 100 3.453 Within-country inequality 0.00102 52 0.001 51 Between-country inequality 0.00097 48 0.00095 49

Table H2: Religious inequality - Africa sub-sample with democratic weighting GE(0) GE(1) Gini

Estimate Share (%) Estimate Share (%) Educational attainment 0.1949 100 0.14252 100 29.013 Within-country inequality 0.10569 54 0.06923 49 Between-country inequality 0.08921 46 0.0733 51 Wealth 0.15262 100 0.14068 100 29.848 Within-country inequality 0.0565 37 0.04617 33 Between-country inequality 0.09613 63 0.09451 67 Child non-stunting rate 0.01513 100 0.01505 100 9.904 Within-country inequality 0.00766 51 0.0074 49 Between-country inequality 0.00746 49 0.00764 51 Child survival rate 0.00303 100 0.0029 100 3.977 Within-country inequality 0.00208 69 0.00196 68 Between-country inequality 0.00096 31 0.00094 32

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