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Measurement of cultural complexity

Having classified more than 300 African ethnic groups, we matched them with the groups listed in the Atlas Narodov Mira, published in 1964 by the Miklukho-Maklai Ethnological Institute in the Soviet Union, which provides the most comprehensive division of the world population into ethnic groups.8 We used the countries’ ethnic composition from the Soviet Atlas to calculate the share of each country’s non-European population belonging to centralized groups.9 This share represents our country-level index of precolonial centralization and we call it “Centralization”. Our sample consists of 42 countries in Sub-Saharan Africa.10 Table A1 shows our Centralization index. The measure displays a wide cross-country variation, ranging from the value of 1 for Lesotho (both of its ethnic groups, the Sotho and the Zulu are centralized) to the value of 0 for Liberia (both the Kru and the Peripheral Mande are fragmented). Consistent with its variety of centralized and fragmented groups, Uganda takes the intermediate value of 0.634. To study the role of precolonial centralization at the local level, we look at outcomes that are importantly determined by local authorities. These outcomes measure the country-level provision of local public goods such as education, health services, and basic infrastructure. Infant mortality and the percentage of infants immunized against DPT (diphtheria, pertussis and tetanus) represent our health outcomes. Adult illiteracy rate and average school attainment proxy for education. The percentage of roads paved (as a share of total roads) is our measure of infrastructure.11 These variables are from the 1960 to 2002 period, depending on data availability. Because we are interested in the impact of precolonial centralization in both the colonial and the postcolonial periods, we use the time averages of each public good outcome as our main dependent variables. However, we also look at how the role of precolonial centralization evolved over time. Tables A2–A4 show descriptive statistics, pairwise correlations between our dependent variables and between Centralization and the controls we use