![]() In this study, we leverage a group’s oral tradition to shed light on its cultural heritage and past social and economic structures. 2 Other weaknesses of the EA, the celebrated compilation of George Peter Murdock (1967), concern the uneven coverage of groups and attributes and measurement error. Furthermore, the absence of proxies of historical norms renders inquiries into how attitudes change and why they persist intractable. Much of this research, however, relies on valuable but incomplete ethnographic sources including the widely used Ethnographic Atlas (EA). Second, during the past two decades, a burgeoning body of work exploring the cultural, historical, and institutional roots of comparative development highlights the significance of ethnic, linguistic, and religious groups ( Michalopoulos and Papaioannou 2017 Nunn 2020). Despite their central role in connecting actions to values and needs, economists have only recently turned to the study of narratives (e.g., Akerlof and Snower 2016 Shiller 2017). Harari (2015), for example, identifies in the myths present in people’s collective imagination the roots of their successes and failures. We think in stories and explain the world by telling stories. First, narratives are central building blocks of our societies. Two broad observations motivate our study. Overall, the results highlight the significance of folklore in cultural economics, calling for additional applications. These patterns hold across groups, countries, and second-generation immigrants. Communities with low tolerance toward antisocial behavior, captured by the prevalence of tricksters being punished, are more trusting and prosperous 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. ![]() 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. 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. 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. After validating the catalog’s content by showing that the groups’ motifs reflect known geographic and social attributes, we present two sets of applications. ![]() We introduce to economics a unique catalog of oral traditions spanning approximately 1,000 societies. Folklore is the collection of traditional beliefs, customs, and stories of a community passed through the generations by word of mouth.
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