Finding the Poor vs. Measuring Their Poverty: Exploring the Drivers of Targeting Effectiveness in Indonesia

Abstract

Abstract Centralized targeting registries are increasingly used to allocate social assistance benefits in developing countries. There are two key design issues that matter for targeting accuracy: (i) which households to survey for inclusion in the registry; and (ii) how to rank surveyed households. We attempt to identify their relative importance by evaluating Indonesia's Unified Database for Social Protection Programs (UDB), among the largest targeting registries in the world, used to provide social assistance to over 25 million households. Linking administrative data with an independent household survey, we find that the UDB system is more progressive than previous, program-specific targeting approaches. However, simulating an alternative targeting system based on enumerating all households, we find a one-third reduction in undercoverage of the poor compared to focusing on households registered in the UDB. Overall, there are large gains in targeting performance from improving the initial registration stage relative to the ranking stage.