Measuring inequality using geospatial data - Jaqueson K. Galimberti; Stefan Pichler; Regina Pleninger (ETH Zurich, KOF Swiss Economic Institute, 2021)
The main challenge in studying economic inequality is limited data availability, which is particularly problematic in developing countries. We construct a measure of economic inequality for 234 countries/territories from 1992 to 2013 using satellite data on night lights and gridded population data. Key methodological innovations include the use of varying levels of data aggregation, and a calibration of the lights-prosperity relationship to match traditional inequality measures based on income data. We obtain a measure that is significantly correlated with cross-country variation in income inequality. We provide three applications of the data in the fields of health economics and international finance. Our results show that light- and income-based inequality measures lead to similar results in terms of cross-country correlations, but not for the dynamics of inequality within countries. Namely, we find that the light-based inequality measure can capture more enduring features of economic activity that are not directly captured by income.
hdl:20.500.11850/473903
Keywords: D63; E01; I14; O11; O47; O57; 330; Nighttime lights; inequality; gridded population