This paper provides a new data set of regional income inequalities within countries based on satellite nighttime light data. We first empirically study the relationship between luminosity data and regional incomes for those countries where regional income data are available. We subsequently use our estimation results for an out-of-sample prediction of regional incomes based on the luminosity data, which allows us to investigate regional income differentials in developing countries as well, where official income data are lacking. Based on the predicted incomes, we calculate commonly used measures of regional inequality within countries. Investigating changes in the dispersion of regional incomes over time reveals that approximately 71-80% of all countries face sigma-convergence. Finally, we study different major determinants of the level of regional inequality based on cross-section data. Panel regressions investigate the within-country changes in inequality, i.e., the determinants of the convergence process. We find evidence for an N-shaped relationship between development and regional inequality. Geography, mobility and trade openness are also highly important.
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