How Well Can We Target Resources with 'Quick-and-Dirty' Data? : Empirical Results from Cambodia

We compare two methods of commune-level poverty rankings in Cambodia, one based on the small-area estimation and the other based on the principal component analysis of aggregate data. We also compare them against the rankings based on the local leaders. While all of the three produce reasonably consistent rankings, the choice of the method matters. Our calculation shows about a quarter of the potential gains from geographic targeting can be captured by using the aggregate data. The usefulness of such aggregate data in general would depend on the cost of data collection