Surface Groups Democratic Republic of the Congo 1984-2021

DOI

This project develops a novel procedure for proxying economic activity with daytime satellite imagery across time periods and spatial units, for which reliable data on economic activity are otherwise not available. In developing this unique proxy, we apply machine-learning techniques to a historical time series of daytime satellite imagery from the Landsat program dating back to 1984. Compared to satellite data on night light intensity, another common economic proxy, our proxy more precisely predicts economic activity at smaller regional levels and over longer time horizons. Our procedure is generalizable to any region in the world, and it has great potential for analyzing historical economic developments, evaluating local policy reforms, and controlling for economic activity at highly disaggregated regional levels in econometric applications. Therefore, we produce our proxy for any region in the world and publish the data as georeferend TIF files in this repository. In our paper, we demonstrate our measure’s usefulness for the example of Germany, where East German data on economic activity are unavailable for detailed regional levels and historical time series.

Identifier
DOI https://doi.org/10.48573/sz0v-cz85
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=50ecc11486ff743417ff33a436c7847f84130f5d139b5ecacd85e4e714f7904c
Provenance
Creator Lehnert, Patrick
Publisher FORS
Publication Year 2024
Rights Zusätzliche Einschränkungen: Kann nur für akademische Forschung und Unterricht verwendet werden; Additional Restrictions: Academic research and teaching only; Restrictions supplémentaires: Recherche et enseignement académiques uniquement; Sondergenehmigung: Nach vorheriger Zustimmung des Autors; Special permission: With prior agreement of author; Permission spéciale: Accord préalable de l'auteur·trice
OpenAccess true
Representation
Discipline Economics; Social and Behavioural Sciences
Spatial Coverage Afrika; Africa; Afrique; Amerikas; Americas; Amériques; Asien; Asia; Asie; Europa; Europe; Europe; Ozeanien; Oceania; Océanie