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Intercensal updating using structure‐preserving methods and satellite imagery
Koebe, Till; Arias‐Salazar, Alejandra; Rojas‐Perilla, Natalia; u. a. (2022): Intercensal updating using structure‐preserving methods and satellite imagery, in: Journal of the Royal Statistical Society : Series A, Statistics in society, London: Oxford University Press, Jg. 185, Nr. Supplement 2, S. 1–27, doi: 10.1111/rssa.12802.
Faculty/Chair:
Title of the Journal:
Journal of the Royal Statistical Society : Series A, Statistics in society
ISSN:
1467-985X
0964-1998
Publisher Information:
Year of publication:
2022
Volume:
185
Issue:
Supplement 2
Pages:
Language:
English
DOI:
Abstract:
Censuses are fundamental building blocks of most modern-day societies, yet collected every 10 years at best. We propose an extension of the widely popular census updating technique structure-preserving estimation by incorporating auxiliary information in order to take ongoing subnational population shifts into account. We apply our method by incorporating satellite imagery as additional source to derive annual small-area updates of multidimensional poverty indicators from 2013 to 2020 for a population at risk: female-headed households in Senegal. We evaluate the performance of our proposal using data from two different census periods.
Keywords: ; ; ;
multidimensional poverty
official statistics
small-area estimation
SPREE
DDC Classification:
RVK Classification:
Peer Reviewed:
Yes:
International Distribution:
Yes:
Open Access Journal:
Yes:
Type:
Article
Activation date:
April 28, 2022
Versioning
Question on publication
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https://fis.uni-bamberg.de/handle/uniba/53875