Maldonado Salazar, Leonardo2024-02-092024-02-092023-12https://hdl.handle.net/11299/260650University of Minnesota Ph.D. dissertation. December 2023. Major: Applied Economics. Advisor: Stephen Polasky. 1 computer file (PDF); vii, 96 pages.This dissertation aims to unravel applications in the economic field derived from analyzing nighttime light data. The dissertation comprises three essays, each delving into distinct aspects of the relationship between nighttime lights and economic phenomena. The first essay investigates the relationship between nighttime lights and economic activity in oil-dependent countries, exploring whether that relationship differs in oil-producing and non-oil-producing regions. The main findings highlight differences in the predictive power of night light emissions by region, emphasizing the potential of light data to enhance economic growth measures. The second essay uses nighttime light imagery to estimate rural poverty rates in Venezuela from 2000 to 2020. The analysis reveals a significant increase in rural poverty rates between 2014 and 2020, shedding light on the impact of the Venezuelan economic collapse in recent years. Finally, the third essay examines regional inequality in the Andean countries using nighttime lights and population datasets, accounting for temporal and spatial dimensions (based on a multiple-stage nested Theil decomposition approach). The study identifies changes in overall inequality, driven by both between-country and within-country factors, providing insights for targeted initiatives to address inequality at the local level.enDMSPInequalityNighttime lightsRemote sensingRural povertyVIIRSThesis or Dissertation