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

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. The authors 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, they 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, they 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.