Abstract
AbstractThe relationship between nighttime lights and GDP varies from country to country. However, which factors drive variations in the lights–GDP relationship across countries remains unclear. This paper examines the significance of approximately 600 potential drivers of uncertainty in the relationship between night lights and GDP worldwide. I employ three novel modern statistical techniques to select variables within a high-dimensional context: LASSO, minimax concave penalty, and spike-and-slab regression. Institutional quality emerges as the most important factor in explaining the difference between luminosity data and GDP across countries.
Publisher
Springer Science and Business Media LLC
Subject
Economics and Econometrics,Social Sciences (miscellaneous),Mathematics (miscellaneous),Statistics and Probability