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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.