Estimating Local Inequality from Nighttime Lights

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WEIDMANN, Nils B., Gerlinde THEUNISSEN, 2021. Estimating Local Inequality from Nighttime Lights. In: Remote Sensing. MDPI. 13(22), 4624. eISSN 2072-4292. Available under: doi: 10.3390/rs13224624

@article{Weidmann2021-11-17Estim-55784, title={Estimating Local Inequality from Nighttime Lights}, year={2021}, doi={10.3390/rs13224624}, number={22}, volume={13}, journal={Remote Sensing}, author={Weidmann, Nils B. and Theunissen, Gerlinde}, note={Article Number: 4624} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:contributor>Theunissen, Gerlinde</dc:contributor> <dcterms:available rdf:datatype="">2021-12-07T16:00:48Z</dcterms:available> <dcterms:isPartOf rdf:resource=""/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:creator>Theunissen, Gerlinde</dc:creator> <dc:rights>Attribution 4.0 International</dc:rights> <dcterms:isPartOf rdf:resource=""/> <dcterms:issued>2021-11-17</dcterms:issued> <dcterms:rights rdf:resource=""/> <dc:contributor>Weidmann, Nils B.</dc:contributor> <dcterms:hasPart rdf:resource=""/> <dspace:isPartOfCollection rdf:resource=""/> <dc:language>eng</dc:language> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <bibo:uri rdf:resource=""/> <dc:creator>Weidmann, Nils B.</dc:creator> <dspace:isPartOfCollection rdf:resource=""/> <dspace:hasBitstream rdf:resource=""/> <dc:date rdf:datatype="">2021-12-07T16:00:48Z</dc:date> <dcterms:abstract xml:lang="eng">Economic inequality at the local level has been shown to be an important predictor of people’s political perceptions and preferences. However, research on these questions is hampered by the fact that local inequality is difficult to measure and systematic data collections are rare, in particular in countries of the Global South. We propose a new measure of local inequality derived from nighttime light (NTL) emissions data. Our measure corresponds to the local inequality in per capita nighttime light emissions, using VIIRS-derived nighttime light emissions data and spatial population data from WorldPop. We validate our estimates using local inequality estimates from the Demographic and Health Surveys (DHS) for a sample of African countries. Our results show that nightlight-based inequality estimates correspond well to those derived from survey data, and that the relationship is not due to structural factors such as differences between urban and rural regions. We also present predictive results, where we approximate the (survey-based) level of local inequality with our nighttime light indicator. This illustrates how our approach can be used for new cases where no other data are available.</dcterms:abstract> <dcterms:title>Estimating Local Inequality from Nighttime Lights</dcterms:title> </rdf:Description> </rdf:RDF>

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