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Using night light emissions for the prediction of local wealth

Bibliographic Data

ID3918595
AuthorsNils B Weidmann (0000-0002-4791-4913, University of Konstanz, corresponding author), Sebastian Schutte (0000-0003-0701-9647, University of Konstanz)
Year2017
Volume54
Issue2
Pages125-140
Publication date2017-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournal of Peace Research (JOURNAL)
Journal identifiersISSN: 0022-3433 • E-ISSN: 1460-3578
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0022343316630359
OpenAlexW2353911097
LanguageEN
Citations received75
References cited16

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

Cartography · Developing country · Econometrics · Economic growth · Economics · Geography · Machine learning · Proxy (statistics) · Sample (material) · Scale (ratio) · Computer Science · Energy, Environment, and Transportation Policies · Impact of Light on Environment and Health · Urban Transport and Accessibility

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Unique citing works75
Citations per year8,33
Citation span2017 - 2026 (10)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 68

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