Common Ancestry, Uncommon Findings: Revisiting Cross-Cultural Research in Economics

Empirical research on culture and institutions in economics often relies on cross-cultural data to examine historical or contemporary variation in traits across ethnolinguistic groups. We argue that this work has not adequately addressed the problem of cultural non-independence due to common ancestry and show how phylogenetic regression, along with newly available global language trees, can be used to directly account for this issue. Our analysis focuses on Murdock's Ethnographic Atlas (EA), a widely used database of preindustrial societies, with broader implications for any cross-cultural study. First, we show that various economic, institutional, and cultural characteristics in the EA exhibit substantial phylogenetic signal - they tend to be more similar among societies with closer ancestral ties. Second, through simulations in a sample resembling the EA, we demonstrate that phylogenetic correlation leads to severe inefficiency of the standard OLS estimator and unacceptably high type I error rates, even when clustered standard errors are used. Phylogenetic generalized least squares (PGLS), exploiting the information on shared ancestry contained in language trees, improves estimation accuracy and enables reliable hypothesis testing. Third, we revisit some of the recently published results in a phylogenetic regression framework. In many specifications, PGLS estimates differ markedly from their OLS counterparts, indicating a smaller magnitude and weaker statistical significance of relevant coefficients.