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. This paper provides the first attempt to identify the relative importance of two key design issues for targeting accuracy: (i) which households to survey for inclusion in the registry and (ii) how to rank surveyed households. We evaluate 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, we identify large gains in targeting performance from improving the initial registration stage relative to the ranking stage.

Targeting poverty under complementarities: Evidence from Indonesia's unified targeting system

“…These estimates are even greater than our estimates of receiving a single program relative to receiving no program at all, casting serious doubt on the findings of many existing studies including: studies using Indonesian data that evaluate the targeting performance of single programs (e.g. Alatas et al 2012, Sparrow, et al 2013, papers that evaluate social programs in isolation (such as: Bah, et al 2014 and World Bank 2012a) as well as comparable programs that have been evaluated elsewhere (see: Coady, Grosh, and Hoddinott 2004).…”

“…Crucially we use the official PMT coefficients that are unique to all 482 districts of Indonesia in order to estimate each household's PMT score, thereby ensuring as close a comparison as possible with the official PMT used in developing the UDB. The TNP2K team using data from the SUSENAS and PODES surveys, developed PMT models that are unique to each regency and city because a variable affecting household welfare status in one municipality or district may have little significance in others areas (seeBah et al 2014). Using each district's unique PMT model, we predict household PMT scores and estimate household expenditures as pre-treatment indicators.…”

“… Pendataan Program Lindungan Sosial 2011. 12 The two-stage data collection involves (i) the earlier lists of households using data from PPLS08 and Population Census in 2010 are compiled through poverty mapping; the (ii) it was complemented with the results of consultations with low-income groups and through impromptu discussions and general observations(Bah et al 2014) …”

Targeting subsidised inpatient services to the poor in a setting with limited state capacity: proxy means testing in Myanmar's hospital equity fund scheme

“…We performed multivariate regression analysis to explore the socio‐economic correlates of targeting effectiveness. Our choice of explanatory variables was informed by the existing literature, whereby household characteristics related to education, location and demographic composition, among others, have been associated with inclusion and exclusion errors .…”

Welfare Measurement and Poverty Targeting Based on Participatory Wealth Rankings

“…A substantial branch of literature is concerned with the question how well different targeting methods, e.g. proxy means testing, geographical targeting, participatory methods, or self-selection, align with certain targeting objectives, usually poverty status as measured by consumption or income (Coady, Grosh and Hoddinott, 2004;Zeller, Feulefack and Neef, 2006;Banerjee et al, 2009;Coady and Parker, 2009;Yusuf, 2010;Alatas et al, 2012;Alatas et al (2016); Alatas et al, 2019;Bah et al, 2019;Karlan and Thuysbaert, 2019). A related yet less explored question is how the method of targeting affects acceptance and satisfaction with the programs in question.…”