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dc.contributor.author Tarozzi, Alessandro en_US
dc.contributor.author Deaton, A. en_US
dc.date.accessioned 2010-03-09T15:38:54Z
dc.date.available 2010-03-09T15:38:54Z
dc.date.issued 2008 en_US
dc.identifier.uri http://hdl.handle.net/10161/2002
dc.description.abstract Household expenditure survey data cannot yield precise estimates of poverty or inequality for small areas for which no or few observations are available. Census data are more plentiful, but typically exclude income and expenditure data. Recent years have seen a widespread use of small-area “poverty maps” based on census data enriched by relationships estimated from household surveys that predict variables not covered by the census. These methods are used to estimate putatively precise estimates of poverty and inequality for areas as small as 20,000 households. In this paper we argue that to usefully match survey and census data in this way requires a degree of spatial homogeneity for which the method provides no basis, and which is unlikely to be satisfied in practice. The relationships that are used to bridge the surveys and censuses are not structural but are projections of missing variables on a subset of those variables that happen to be common to the survey and the census supplemented by local census means appended to the survey. As such, the coefficients of the projections will generally vary from area to area in response to variables that are not included in the analysis. Estimates of poverty and inequality that assume homogeneity will generally be inconsistent in the presence of spatial heterogeneity, and error variances calculated on the assumption of homogeneity will underestimate mean squared errors and overestimate the coverage of calculated confidence intervals. We use data from the 2000 census of Mexico to construct synthetic “household surveys” and to simulate the poverty mapping process. In this context, our simulations show that while the poverty maps contain useful information, their nominal confidence intervals give a misleading idea of precision. en_US
dc.format.extent 774776 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.publisher Review of Economics and Statistics en_US
dc.subject Heterogeneity en_US
dc.subject Inequality en_US
dc.subject Small area statistics en_US
dc.subject Survey Methods en_US
dc.subject poverty en_US
dc.title Using Census and Survey Data to Estimate Poverty and Inequality for Small Areas en_US
dc.type Journal Article en_US
dc.department Economics

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