Educational Inequality and Intergenerational Mobility in Africa∗

Educational Inequality and Intergenerational Mobility in Africa∗ Alberto Alesina Sebastian Hohmann Harvard University, CEPR and NBER London Business School Stelios Michalopoulos Elias Papaioannou Brown University, CEPR and NBER London Business School and CEPR March 14, 2018 Abstract We investigate the evolution of inequality and intergenerational mobility in educational attainment in Africa. Using census data covering more than 50 million people in 23 countries we document the following regularities. First, since independence, inequality has fallen across countries and intergenerational mobility has risen, reflecting the rise in education across the continent. Second, the overall drop in African inequality can be attributed mostly to declines in within-country, within-region and within-ethnicity components. Third, the initially moderate regional and ethnic differences in education persist, revealing strong inertia across these lines. Fourth, we describe the geography of educational mobility across regions and ethnic groups uncovering strong \poverty-trap" dynamics. Educational mobility is higher in regions and ethnicities with above-country-average schooling at independence. Fifth, we explore the geographic, historical, and contemporary correlates of intergenerational mobility both across regions and ethnic lines. Colonial investments correlate strongly with educational mobility, while geography and pre-colonial features play a lesser role. The analysis further uncovers \Gatsby Curve" dynamics with intergenerational mobility being low in regions with high inequality. Keywords: Africa, Development, Education, Inequality, Intergenerational Mobility. JEL Numbers. N00, N9, O10, O43, O55 ∗Alberto Alesina Harvard University and IGIER Bocconi, Sebastian Hohmann, London Business School, Stelios Michalopoulos. Brown University, Elias Papaioannou. London Business School. We thank Remi Jedwab and Adam Storey- gard for sharing their data on colonial roads and railroads in Africa, Julia Cagéand Valeria Rueda for sharing their data on protestant missions, and Nathan Nunn for sharing his data on Catholic and Protestant missions. We would like to thank for their comments conference participants at the university of Zurich, Brown University and Oriana Bandiera for her insightful discussion. 1 1 Introduction According to many observers Africa is not only the poorest continent but also the most unequal (Dowden (2008); World Bank (2016)). However, data on African income and wealth inequality are scant and incomplete. In addition we do not have much information on regional and ethnic differences in well- being and previous works have relied on luminosity to proxy for ethnic and spatial inequality (Alesina, Michalopoulos, and Papaioannou (2016)). Since the 2000s the formerly \hopeless continent" has become the \hopeful one" (Economist, 2000, 2011) and there is rising euphoria on Africa's future. However, we lack an understanding of the distribution of African growth post-independence across regions and ethnic groups. Likewise, while the Economist has recently coined Africa as the continent of 1:2 billion opportunities (2016), there is not much research on mobility. Where is the land of educational opportunity in Africa? Are regional differences in education present at independence declining? Are there systematic ethnic differences in educational mobility? What is the association between education levels, inequality, and intergenerational mobility across countries, regions, and ethnicities? And which factors correlate with educational mobility? We begin to answer this set of questions using census data on education covering more than 53 million individuals in 23 countries since independence. We organize our analysis into two main parts. 1.1 Overview of Descriptive Patterns We begin with a detailed description of the evolution of inequality in education across Africa, conducting the analysis across three domains: countries, administrative regions, and ethnic lines.1 We then study intergenerational mobility (IM) in education. Following Chetty et al. (2014) we measure in both relative and absolute terms. The relative IM index {that closely follows the literature{ is based on regressing children's years of schooling on parental education. The absolute IM index reflects the likelihood that offspring of parents who do not have any formal schooling (we term such individuals \illiterate"), manage to complete at least primary education (we call them \literate"). Our analysis uncovers the following regularities. First, since the late colonial times, inequality has fallen, as African countries have experienced rising education. However, there are sizeable and -if anything- growing asymmetries across countries. The between-country component of pan-African inequality has risen over time, reflecting the relative success (and failures) of African countries in expanding education. IM has risen too, but there are large cross- country differences. Second, when we look within countries we find that the drop in educational inequality stems from large declines in within-region inequality rather than a systematic decline of regional disparities. At- independence regional differences in education persist. A similar picture applies to IM in education, as we observe large differences in IM across administrative regions. Third, a similar decomposition of country-wide inequality into a between and a within-ethnicity 1For the regional analysis, we examine coarse and fine regional units. We label the coarse units as \provinces" and the fine regional units as \districts". Overall we have 346 admin-1 units (provinces) and 2; 444 admin-2 units (districts). 2 component reveals a sizeable drop of within-ethnicity inequality, but minuscule declines across ethnic lines. Likewise, there are non-negligible differences in IM across groups. The gains in education have disproportionately benefited some ethnic groups. This finding is consistent with the well documented phenomenon of ethnic favoritism and ethnic-based discrimination in Africa (e.g., Wimmer, Cederman, and Min (2009)). Fourth, the persistent regional and ethnic gaps in education and in educational IM apply to both males and females. They are especially strong for rural households, much attenuated in urban centers, and less pronounced for migrants. Fifth, the analysis uncovers stark regional and ethnic-specific components in the transmission of educational attainment. Regions that have gained the most since the 1960s are regions that at independence had higher educational attainment. And Africans belonging to ethnic groups with a higher parental education appear, on average, more intergenerationally mobile. This finding suggests the presence of poverty traps and/or peer effects in educational attainment. 1.2 Overview Correlation Analysis We then explore the correlates of inequality and IM in education across regions and ethnicities. We do not claim causality, but merely want to shed light on the role of geographic, historical (colonial and precolonial), and contemporary features for educational IM. We uncover the following: First, the strongest correlate of both spatial and ethnic IM is parental education. The likelihood that children of parents without formal education will complete at least primary school (absolute IM) is strongly and negatively correlated with the share of the \old" generation without formal education. This is true across countries, regions and ethnic groups. The share of parents without any schooling explains more than half of the observed variability in IM. Second, among various geographic variables, only distance to the capital and the ecological conditions favorable to malaria correlate negatively with IM. Natural resources, terrain features, and proximity to the coast do not seem to play a role. Third, proximity to colonial railroads/roads and to Christian, especially Protestant, missions correlate strongly with regional IM, even when one nets out the direct impact of these colonial investments on education at independence. Fourth, the only ethnic-specific (precolonial) trait which correlates with educational IM is the ethnicity's mode of subsistence economy. Individuals belonging to groups that during the pre-colonial era were mainly dependent on agriculture have, on average, higher IM, as compared to those tracing their ancestry to pastoral groups. In contrast, other ethnic features that have been linked to contemporary development, such as political centralization, slavery, class stratification, and polygyny do not systematically correlate with IM. Fifth, when we look at contemporary features, we find a strong negative association between (regional and ethnic) inequality and IM. This \Gatsby curve" result echoes the evidence on income inequality and IM across US regions documented by Chetty et al. (2014), as well as the cross-country patterns in Corak (2013). The analysis further shows a link between industrial specialization and educational IM, with educational IM being considerably higher (lower) in districts with a large (low) share of agriculture. 3 1.3 Related Literature Our paper lies in the intersection of three strands of literature. The first is the growing body of research documenting and understanding the evolution of inequality in income, wealth, consumption, education, and health, mostly across industrial countries (see for reviews, Alvaredo, Chancel, Piketty, Saez, and Zucman (2018), Alvaredo et al. (2013), Piketty (2014), and Atkinson, Piketty, and Saez (2011)). Especially related to our paper

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