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Using night light emissions for the prediction of local wealth

Author

Listed:
  • Nils B Weidmann

    (Department of Politics and Public Administration, University of Konstanz)

  • Sebastian Schutte

    (Zukunftskolleg & Department of Politics and Public Administration, University of Konstanz)

Abstract

Nighttime illumination can serve as a proxy for economic variables in particular in developing countries, where data are often not available or of poor quality. Existing research has demonstrated this for coarse levels of analytical resolution, such as countries, administrative units or large grid cells. In this article, we conduct the first fine-grained analysis of night lights and wealth in developing countries. The use of large-scale, geo-referenced data from the Demographic and Health Surveys allows us to cover 39 less developed, mostly non-democratic countries with a total sample of more than 34,000 observations at the level of villages or neighborhoods. We show that light emissions are highly accurate predictors of economic wealth estimates even with simple statistical models, both when predicting new locations in a known country and when generating predictions for previously unobserved countries.

Suggested Citation

  • Nils B Weidmann & Sebastian Schutte, 2017. "Using night light emissions for the prediction of local wealth," Journal of Peace Research, Peace Research Institute Oslo, vol. 54(2), pages 125-140, March.
  • Handle: RePEc:sae:joupea:v:54:y:2017:i:2:p:125-140
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    Citations

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    Cited by:

    1. Christian Otchia & Simplice Asongu, 2020. "Industrial growth in sub-Saharan Africa: evidence from machine learning with insights from nightlight satellite images," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 48(8), pages 1421-1441, December.
    2. Stelios Michalopoulos & Elias Papaioannou, 2018. "Spatial Patterns of Development: A Meso Approach," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 383-410, August.
    3. Dreher, Axel & Fuchs, Andreas & Hodler, Roland & Parks, Bradley C. & Raschky, Paul A. & Tierney, Michael J., 2021. "Is Favoritism a Threat to Chinese Aid Effectiveness? A Subnational Analysis of Chinese Development Projects," World Development, Elsevier, vol. 139(C).
    4. Ho Fai Chan & Bruno S. Frey & Ahmed Skali & Benno Torgler, 2019. "Political Entrenchment and GDP Misreporting," CREMA Working Paper Series 2019-02, Center for Research in Economics, Management and the Arts (CREMA).
    5. Karell, Daniel & Schutte, Sebastian, 2018. "Aid, Exclusion, and the Local Dynamics of Insurgency in Afghanistan," SocArXiv 6ea2r, Center for Open Science.
    6. Bunte, Jonas B. & Desai, Harsh & Gbala, Kanio & Parks, Bradley & Runfola, Daniel Miller, 2018. "Natural resource sector FDI, government policy, and economic growth: Quasi-experimental evidence from Liberia," World Development, Elsevier, vol. 107(C), pages 151-162.
    7. Ore Koren & Laura Mann, 2018. "Nighttime Light, Superlinear Growth, and Economic Inequalities at the Country Level," Papers 1810.12996, arXiv.org.

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