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Abstract

Typical living standards surveys can provide a wealth of information about welfare levels, poverty, and other household and individual characteristics. However, these estimates are necessarily at a high level of aggregation, because such surveys usually include only a few thousand households, with coarse spatial stratification. Larger databases, such as national censuses, provide sufficient observations for more disaggregated analysis, but typically collect very little socioeconomic information. This paper combines data from the 1996–97 Mozambique National Household Survey of Living Conditions with the 1997 National Population and Housing Census to generate small-area (subdistrict) estimates of welfare, poverty, and inequality, with the associated standard errors. These small-area estimates are then used to explore several dimensions of poverty and inequality in Mozambique, particularly with regard to geographical targeting of antipoverty efforts. Reliably identifying and targeting the poor can be administratively costly, especially in rural Africa, where low population density and weak administrative capacity are common. Geographical targeting, or targeting poor areas, is sometimes proposed as a feasible alternative to targeting poor people, and poverty maps may serve as a valuable tool in this regard. Unfortunately, the notion of poor areas might not always be especially useful, as appears to be the case in Mozambique. The poverty maps do not reveal a particularly strong spatial concentration of poverty; the differences in poverty levels between areas tend to be subtle. This pattern is also observed in the decomposition of small-area inequality estimates, which shows that only about 20 percent of consumption inequality is accounted for by inequality between districts or between administrative posts. The picture that emerges of the poor living alongside the nonpoor indicates that targeting poor areas is likely to result in leakage to the nonpoor in that area, and considerable under-coverage of the significant numbers of poor households in areas that are less poor.

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