Better Night Lights Data, For Longer

John Gibson

No 2020-08, CSAE Working Paper Series from Centre for the Study of African Economies, University of Oxford

Abstract: Night lights data are increasingly used in applied economics, almost always from the Defense Meteorological Satellite Program (DMSP). These data are old, with production ending in 2013, and are flawed by blurring, lack of calibration, and top-coding. These inaccuracies in DMSP data cause mean-reverting errors. This paper shows newer and better VIIRS night lights data have 80% higher predictive power for real GDP in a cross-section of almost 300 European NUTS2 regions. Spatial inequality is greatly understated with DMSP data, especially for the most densely populated regions. A Pareto correction for top-coding of DMSP data has a modest effect.

Keywords: DMSP; GDP; inequality; mean-reverting error; night lights, VIIRS (search for similar items in EconPapers)
JEL-codes: E20 R12 (search for similar items in EconPapers)
Date: 2020
New Economics Papers: this item is included in nep-big, nep-geo and nep-ure
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Citations: View citations in EconPapers (13)

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Journal Article: Better Night Lights Data, For Longer (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:csa:wpaper:2020-08

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