Small area estimation of non-monetary poverty with geospatial data : background paper World Development Report 2021 / Takaaki Masaki, David Newhouse, Ani Rudra Silwal, Adane Bedada, Ryan Engstrom
Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: World Bank E-Library Archive | Policy research working paper ; 9383Publisher: [Washington, DC, USA] : World Bank Group, Poverty and Equity Global Practice, September 2020Description: 1 Online-Ressource (circa 49 Seiten) : IllustrationenSubject(s): Genre/Form: Additional physical formats: Erscheint auch als: Small Area Estimation of Non-Monetary Poverty with Geospatial Data. Druck-Ausgabe Washington, D.C : The World Bank, 2020DOI: DOI: 10.1596/1813-9450-9383Online resources: Summary: This paper uses data from Sri Lanka and Tanzania to evaluate the benefits of combining household surveys with geographically comprehensive geospatial indicators to generate small area estimates of non-monetary poverty. The preferred estimates are generated by utilizing subarea-level geospatial indicators in a household-level empirical best predictor mixed model with a normalized welfare measure. Mean squared errors are estimated using a parametric bootstrap procedure. The resulting estimates are highly correlated with non-monetary poverty calculated from the full census in both countries, and the gain in precision is comparable to increasing the size of the sample by a factor of three in Sri Lanka and five in Tanzania. The empirical best predictor model moderately underestimates uncertainty, but coverage rates are similar to standard survey-based estimates that assume independent outcomes across clusters. A variety of checks, including adding noise to the welfare measure and model-based and design-based simulations, confirm that the main results are robust. The results demonstrate that combining household survey data with subarea-level geospatial indicators can greatly increase the precision of survey estimates of non-monetary poverty at comparatively low costPPN: PPN: 1735753092Package identifier: Produktsigel: ZDB-110-WBL | ZDB-1-WBA | ZDB-110-WBONo physical items for this record
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