We examine intergenerational mobility (IM) in educational attainment in Africa since independence using census data. First, we map IM across 27 countries and more than 2,800 regions, documenting wide cross-country and especially within-country heterogeneity. Inertia looms large as differences in the literacy of the old generation explain about half of the observed spatial disparities in IM. The rural-urban divide is substantial. Though conspicuous in some countries, there is no evidence of systematic gender gaps in IM. Second, we characterize the geography of IM, finding that colonial investments in railroads and Christian missions, as well as proximity to capitals and the coastline are the strongest correlates. Third, we ask whether the regional differences in mobility reflect spatial sorting or their independent role. To isolate the two, we focus on children whose families moved when they were young. Comparing siblings, looking at moves triggered by displacement shocks, and using historical migrations to predict moving-families' destinations, we establish that, while selection is considerable, regional exposure effects are at play. An extra year spent in a high-mobility region before the age of 12 (and after 5) significantly raises the likelihood for children of uneducated parents to complete primary school. Overall, the evidence suggests that geographic and historical factors laid the seeds for spatial disparities in IM that are cemented by sorting and the independent impact of regions.

Folklore is the collection of traditional beliefs, customs, and stories of a community passed through the generations by word of mouth. We introduce to economics a unique catalog of oral traditions spanning approximately 1,000 societies. After validating the catalog's content by showing that the groups' motifs reflect known geographic and social attributes, we present two sets of applications. First, we illustrate how to fill in the gaps and expand upon a group's ethnographic record, focusing on political complexity, high gods, and trade. Second, we discuss how machine learning and human classification methods can help shed light on cultural traits, using gender roles, attitudes toward risk, and trust as examples. Societies with tales portraying men as dominant and women as submissive tend to relegate their women to subordinate positions in their communities, both historically and today. More risk-averse and less entrepreneurial people grew up listening to stories wherein competitions and challenges are more likely to be harmful than beneficial. Communities with low tolerance toward antisocial behavior, captured by the prevalence of tricksters being punished, are more trusting and prosperous today. These patterns hold across groups, countries, and second-generation immigrants. Overall, the results highlight the significance of folklore in cultural economics, calling for additional applications.