An Estimate of Gross Domestic Product (GDP) Derived From Satellite Data


Collection of data on economic variables, especially sub-national income levels, is problematic, due to various shortcomings in the data collection process. Additionally, the informal economy is often excluded from official statistics. Nighttime lights satellite imagery and the LandScan population grid provide an alternative means for measuring economic activity. We have developed a model for creating a disaggregated map of estimated total (formal plus informal) economic activity for countries and states of the world. Regression models were developed to calibrate the sum of lights to official measures of economic activity at the sub-national level for China, India, Mexico, and the United States and at the national level for other countries of the world, and subsequently unique coefficients were derived. Multiplying the unique coefficients with the sum of lights provided estimates of total economic activity, which were spatially distributed to generate a spatially disaggregated 1 km2 map of total economic activity.