Working Paper, Brown University, Department of Economics 2009-8
GDP growth is often measured poorly for countries and rarely measured at all for cities. We propose a readily available proxy: satellite data on lights at night. Our statistical framework uses light growth to supplement existing income growth measures. The framework is applied to countries with the lowest quality income data, resulting in estimates of growth that differ substantially from established estimates. We then consider a longstanding debate: do increases in local agricultural productivity increase city incomes? For African cities, we find that exogenous agricultural productivity shocks (high rainfall years) have substantial effects on local urban economic activity.
economic growth remote sensing urbanization income measurement