This paper considers the practical problem of distributing a fixed budget for poverty alleviation to a population whose poverty status is not directly observable. Some information on the relationship between poverty status and a number of observable and verifiable characteristics is assumed to be available in the form of a household survey. The solution we propose differs from other academic work in that it explicitly accounts for administrative constraints on the shape of the transfer function and is computationally more straightforward. It improves on the techniques that are commonly used in practice by taking both the concavity of the social welfare function and the entire conditional distribution of poverty status into account, and by endogenously determining the optimal transfer levels. Although the superiority of our allocation rule over other techniques is tautological, we explore the magnitude of the improvement in an artificial dataset. Finally, we provide an intuitive discussion of the defects of currently operational methods.
