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Full-Text Articles in Social and Behavioral Sciences
How Well Can We Target Aid With Rapidly Collected Data? Empirical Results For Poverty Mapping From Cambodia, Tomoki Fujii
How Well Can We Target Aid With Rapidly Collected Data? Empirical Results For Poverty Mapping From Cambodia, Tomoki Fujii
Research Collection School Of Economics
We compare commune-level poverty rankings in Cambodia based on three different methods: small-area estimation, principal component analysis using aggregate data, and interviews with local leaders. While they provide reasonably consistent rankings, the choice of the ranking method matters. In order to assess the potential losses from moving away from census-based poverty mapping, we used the concentration curve. Our calculation shows that about three-quarters of the potential gains from geographic targeting may be lost by using aggregate data. The usefulness of aggregate data in general would depend on the cost of data collection.
Two-Sample Estimation Of Poverty Rates For Disabled People: An Application To Tanzania, Tomoki Fujii
Two-Sample Estimation Of Poverty Rates For Disabled People: An Application To Tanzania, Tomoki Fujii
Research Collection School Of Economics
Estimating poverty measures for disabled people in developing countries is di cult, partly because relevant data are not available. We develop two methods to estimate poverty by the disability status of the household head. We extend the small-area estimation proposed by Elbers, Lanjouw and Lanjouw (2002, 2003) so that we can run a regression on head's disability status even when such information is unavailable in the survey. We do so by aggregation and by moment adjusted two sample instrumental variable estimation. Our results from Tanzania show that both methods work well, and that disability is indeed associated with poverty.