The small-area estimation technique developed for producing poverty maps has been applied in a large number of developing countries. Opportunities to formally test the validity of this approach remain rare due to lack of appropriately detailed data. This paper compares a set of predicted welfare estimates based on this methodology against their true values, in a setting where these true values are known. A recent study draws on Monte Carlo evidence to warn that the small-area estimation methodology could significantly over-state the precision of local-level estimates of poverty, if underlying assumptions of spatial homogeneity do not hold. Despite these concerns, the findings in this paper for the state of Minas Gerais, Brazil, indicate that the small-area estimation approach is able to produce estimates of welfare that line up quite closely to their true values. Although the setting considered here would seem, a priori, unlikely to meet the homogeneity conditions that have been argued to be essential for the method, confidence intervals for the poverty estimates also appear to be appropriate. However, this latter conclusion holds only after carefully controlling for community-level factors that are correlated with household level welfare.
Details
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Author
Elbers,Chris T.M., Lanjouw,Peter F., Pereira Guimaraes Leite,Phillippe George
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Document Date
2008/02/01
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Document Type
Policy Research Working Paper
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Report Number
WPS4513
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Volume No
1
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Total Volume(s)
1
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Country
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Region
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Disclosure Date
2010/07/01
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Disclosure Status
Disclosed
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Doc Name
Brazil within Brazil : testing the poverty map methodology in Minas Gerais
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Keywords
enumeration area;municipality level;Municipalities;small area;confidence interval;population with access to electricity;household per capita income;standard error;spatial correlation;household survey data;spatial distribution of poverty;welfare measure;life expectancy at birth;average per capita income;small number of household;census data;estimates of poverty;poverty estimate;cluster level effect;infant mortality rate;Poverty & Inequality;model specification;sources of errors;maximum likelihood estimation;formal sector employment;analysis of poverty;share of children;per capita consumption;national income estimate;income regression model;nationally representative survey;household income variable;census enumeration area;population census;weighting scheme;error component;local control;
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Citation
Elbers,Chris T.M. Lanjouw,Peter F. Pereira Guimaraes Leite,Phillippe George
Brazil within Brazil : testing the poverty map methodology in Minas Gerais (English). Policy Research working paper ; no. WPS 4513 Washington, D.C. : World Bank Group. http://documents.worldbank.org/curated/en/941401468231893568/Brazil-within-Brazil-testing-the-poverty-map-methodology-in-Minas-Gerais