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Proxying Economic Activity with Daytime Satellite Imagery: Filling Data Gaps Across Time and Space

Patrick Lehnert, Michael Niederberger, Uschi Backes-Gellner and Eric Bettinger ()

No 165, Economics of Education Working Paper Series from University of Zurich, Department of Business Administration (IBW)

Abstract: This paper develops a novel procedure for proxying economic activity with daytime satellite imagery across time periods and spatial units, for which reliable data on economic activity are otherwise not available. In developing this unique proxy, we apply machine-learning techniques to a historical time series of daytime satellite imagery dating back to 1984. Compared to satellite data on night light intensity, another common economic proxy, our proxy more precisely predicts economic activity at smaller regional levels and over longer time horizons. We demonstrate our measure's usefulness for the example of Germany, where East German data on economic activity are unavailable for detailed regional levels and historical time series. Our procedure is generalizable to any region in the world, and it has great potential for analyzing historical economic developments, evaluating local policy reforms, and controlling for economic activity at highly disaggregated regional levels in econometric applications.

Keywords: Daytime satellite imagery; Landsat; machine learning; economic activity; land cover (search for similar items in EconPapers)
JEL-codes: E01 E23 O18 R11 R14 (search for similar items in EconPapers)
Pages: 73 pages
Date: 2020-03, Revised 2022-09
New Economics Papers: this item is included in nep-big, nep-geo, nep-mac and nep-ure
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