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Three Facts About Night Lights Data

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Abstract

The DMSP night lights data used in economics are old and not very accurate. Newer VIIRS night lights data have 60 percent higher predictive power for state-level GDP in the United States. Predictive accuracy is far higher in the cross section than for time series changes, either annually or quarterly. Night lights predict more weakly for agriculture than for manufacturing and other industries. These three facts suggest a need for caution in using night lights data, which may be unsuitable for many economics research purposes in many places.

Suggested Citation

  • John Gibson & Geua Boe-Gibson, 2020. "Three Facts About Night Lights Data," Working Papers in Economics 20/03, University of Waikato.
    • Handle: RePEc:wai:econwp:20/03
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    File URL: https://repec.its.waikato.ac.nz/wai/econwp/2003.pdf
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    1. Bluhm, Richard & Krause, Melanie, 2022. "Top lights: Bright cities and their contribution to economic development," Journal of Development Economics, Elsevier, vol. 157(C).
    2. John Gibson & Susan Olivia & Geua Boe‐Gibson, 2020. "Night Lights In Economics: Sources And Uses," Journal of Economic Surveys, Wiley Blackwell, vol. 34(5), pages 955-980, December.
    3. Gibson, John & Olivia, Susan & Boe-Gibson, Geua & Li, Chao, 2021. "Which night lights data should we use in economics, and where?," Journal of Development Economics, Elsevier, vol. 149(C).
    4. Goldblatt,Ran Philip & Heilmann,Kilian Tobias & Vaizman,Yonatan, 2019. "Can Medium-Resolution Satellite Imagery Measure Economic Activity at Small Geographies ? Evidence from Landsat in Vietnam," Policy Research Working Paper Series 9088, The World Bank.
    5. William Nordhaus & Xi Chen, 2015. "A sharper image? Estimates of the precision of nighttime lights as a proxy for economic statistics," Journal of Economic Geography, Oxford University Press, vol. 15(1), pages 217-246.
    6. J. Vernon Henderson & Adam Storeygard & David N. Weil, 2012. "Measuring Economic Growth from Outer Space," American Economic Review, American Economic Association, vol. 102(2), pages 994-1028, April.
    7. Ran Goldblatt & Kilian Heilmann & Yonatan Vaizman, 0. "Can Medium-Resolution Satellite Imagery Measure Economic Activity at Small Geographies? Evidence from Landsat in Vietnam," The World Bank Economic Review, World Bank, vol. 34(3), pages 635-653.
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    Cited by:

    1. Jesson A. Pagaduan, 2022. "Do higher‐quality nighttime lights and net primary productivity predict subnational GDP in developing countries? Evidence from the Philippines," Asian Economic Journal, East Asian Economic Association, vol. 36(3), pages 288-317, September.
    2. Eugenia Go & Kentaro Nakajima & Yasuyuki Sawada & Kiyoshi Taniguchi, 2023. "Satellite-Based Vehicle Flow Data to Assess Local Economic Activities," CIRJE F-Series CIRJE-F-1209, CIRJE, Faculty of Economics, University of Tokyo.
    3. Chong Peng & Weizeng Sun & Xi Zhang, 2022. "Crime under the Light? Examining the Effects of Nighttime Lighting on Crime in China," Land, MDPI, vol. 11(12), pages 1-20, December.
    4. John Gibson, 2021. "Better Night Lights Data, For Longer," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 770-791, June.

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    More about this item

    Keywords

    DMSP; GDP; night lights; VIIRS; United States;
    All these keywords.

    JEL classification:

    • E23 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Production
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)

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