We study the distribution of economic activity, as proxied by lights at night, across 250,000 grid cells of average area 560 square kilometers. We first document that nearly half of the variation can be explained by a parsimonious set of physical geography attributes. A full set of country...

In many regions of the world, sparse data on key economic outcomes inhibits the development, targeting, and evaluation of public policy. We demonstrate how advancements in satellite imagery and machine learning can help ameliorate these data and inference challenges. In the context of an...

The rigorous evaluation of anti-poverty programs is key to the fight against global poverty. Traditional approaches rely heavily on repeated in-person field surveys to measure program effects. However, this is costly, time-consuming, and often logistically challenging. Here we provide the first...

To understand how global firm networks operate, we need consistent information on their activities, unbiased by their reporting choices. In this paper, we collect a novel dataset on the light that factories emit at night for a large sample of car manufacturing plants. We show that nightlight...

We apply deep learning to daytime satellite imagery to predict changes in income and population at high spatial resolution in US data. For grid cells with lateral dimensions of 1.2km and 2.4km (where the average US county has dimension of 55.6km), our model predictions achieve R2 values of 0.85...

We use state-of-the-art, satellite-based PM2.5 estimates to assess the extent to which the EPA's existing, monitor-based measurements over- or under-estimate true exposure to PM2.5 pollution. Treating satellite-based estimates as truth implies a substantial number of "policy...

This paper proposes a methodology for defining urban markets based on economic activity detected by satellite imagery. We use nighttime lights data, whose use in economics is increasingly common, to define urban markets based on contiguous pixels that have a minimum threshold of light intensity....

The United Nations Human Development Index (HDI) is arguably the most widely used alternative to gross domestic product for measuring national development. This is in large part due to its multidimensional nature, as it incorporates not only income, but also education and health. However, the...

We estimate the long-term effect of public R&D on growth in manufacturing by analyzing new data from the Cold War era Space Race. We develop a novel empirical strategy that leverages US-Soviet rivalry in space technology to isolate windfall R&D spending. Our results demonstrate that public R&D...