Poverty Mapping

Indirect Estimation Techniques

In the late 1990’s, researchers in the World Bank’s Development Economics Research Group (DECRG), building on the work of Ghosh and Rao (1994), applied indirect estimation techniques to produce a census enumeration level poverty map for Ecuador, demonstrating that unbiased estimates of poverty can be derived for small areas by combining the richness of household surveys with the depth in coverage of censuses (Hentschel et al., 1998). Whereas survey data alone produce estimates that are representative nationally (or subnational to the first administrative level) for hundreds of thousands of households, small area estimation generates estimates of a subnational nature at a much finer-resolution, with comparable levels of statistical precision (Elbers at al. 2003).The ability to produce reliable estimates of poverty for small geographic areas, without the added costs of fielding additional household surveys, has made this technique attractive to policymakers.

Elbers, C., J.O. Lanjouw. and P. Lanjouw. 2003. "Micro-Level Estimation of Poverty and Inequality." Econometrica 71(1): 355–364. http://siteresources.worldbank.org/DEC/Resources/micestpovineq.pdf

Ghosh, M. and Rao, J.N.K. (1994) Small Area Estimation: An Appraisal. Statistical Science. 9(1): 55-93.  http://dx.doi.org/10.1214/ss/1177010647

Hentschel, J., J.O. Lanjouw, P. Lanjouw, and J. Poggi. 1998. Combining Census and Survey Data to Study Spatial Dimensions of Poverty and Inequality. The World Bank Economic Review, Policy Research Working Paper 1928, pp. 31. http://go.worldbank.org/EAQ1DX9WV0