Subnational measures of economic activity are crucial for analyzing inequalities that persist across subnational regions and for tracking progress towards sustainable development within a country. Eighteen of the Sustainable Development Goals (SDG) indicators require having estimates of Gross Domestic Product (GDP), making subnational GDP estimates crucial for local SDG monitoring. However, many countries do not produce official subnational GDP estimates. Using Paraguay as an example, we show how nightlights imagery from the Visible Infrared Imaging Radiometer Suite’s Day-Night Band (VIIRS-DNB) and data from neighboring countries can be used to produce subnational GDP estimates. We first estimate the relationship between VIIRS and economic activity in South American countries at the first subnational administrative level, employing various econometric models. Results suggest that nightlights are strongly predictive of subnational GDP variation in South American countries with available data. We assess various models’ goodness-of-fit using both cross-validation against other countries’ subnational GDP data and comparing predictions against an input–output accounting of Paraguay’s subnational GDP. Finally, we use the preferred model to produce a time series of department-level GDP in Paraguay.