UCLA

This dissertation investigates factors influencing economic growth in developing countries through their impact on the labor market. Chapter 1 analyzes the effects of industrial robot adoption on local labor markets in Mexico. Using data on robot imports alongside administrative, survey, and economic census data and leveraging spatial and temporal variations across commuting zones, the study finds that robot adoption does not negatively affect formal employment and average wages, unlike developed countries. Additionally, regions importing robots see increased gross value added per worker, indicating productivity gains offset potential displacement effects. Chapter 2 studies the connection between intergenerational social mobility and economic development, using a novel dataset on educational mobility for 52 Latin American sub-regions. Employing a new weighting procedure that accounts for cohort participation in the economy, the study finds that higher intergenerational mobility is strongly linked to economic growth and improved development indicators. The final chapter examines discrepancies in reported Type I errors in linked datasets, which are crucial for studying historical intergenerational mobility. The study reveals that differences arise from reporting conditional versus unconditional error rates. The higher unconditional error rate, considering all algorithm links, better reflects the true error rate and affects inferences from historical data lacking a ground truth.