Recent ASPIRE Survey–Based Evidence of Targeting Outcomes

Unpacking the Empirics of Targeting in Low- and Middle-Income Countries | 87

with household survey–type information (or special samples of the poor), although the comparisons must acknowledge that communities’ definitions of needs and those used in the surveys to assess welfare may be different, a theme taken up in chapter 6.

Despite all these caveats on the interpretation of the results, looking at household survey data is too useful to forgo, so that is done in the next section. Other papers use a range of country surveys to assess targeting performance across multiple contexts (for example, Kidd and Athias 2020). The next section extends this type of cross-country analysis using the ASPIRE database, which has the advantages of using harmonized survey data to enhance comparability and large country and program coverage. In addition, the section looks at a broader range of performance indicators than is commonly used. Kidd and Athias (2020) focus on exclusion errors, which are an important but incomplete view of targeting outcomes (see chapter 7). This chapter looks at coverage across the whole distribution, incidence across the whole distribution, the benefit level and adequacy of benefits, and changes in the poverty gap.8

Recent ASPIRE Survey–Based Evidence of Targeting Outcomes

This section presents ASPIRE’s main distributional performance indicators, including coverage, incidence, and impact on poverty and inequality. From the larger set of 432 surveys covering 125 countries over the past two decades, the chapter focuses on results from 2014 onward, essentially the most recent five years of data on the platform (when the data were drawn for this compilation in June 2021, only one survey for 2019 was available in ASPIRE).9 This yields a sample of 70 countries and their most recent surveys: 24 in Sub-Saharan Africa, 18 in Latin American and the Caribbean, 16 in Europe and Central Asia, 7 in East Asia and Pacific, 4 in South Asia, and 1 in the Middle East and North Africa. Annex 2A provides a complete list of the surveys. By income group, the sample has 7 high-income countries (all World Bank borrower clients, not traditional donor high-income countries), 28 upper-middle-income countries, 26 lower-middle-income countries, and 9 low-income countries.10 Use of the 2014 cutoff achieves a reasonably broad coverage of countries. The average year of survey was 2016 in East Asia and Pacific, Europe and Central Asia, the Middle East and North Africa, and Sub-Saharan Africa and 2017 in Latin American and the Caribbean and South Asia. As social assistance programming was a very fast-moving field even before COVID-19, older data in countries with nascent or reforming programs are not representative of social protection today, but history can still be a useful teacher.

88 | Revisiting Targeting in Social Assistance

ASPIRE estimates the distributional performance of the social protection program categories based on household survey data and information on the sizes of the programs (number of beneficiaries and spending) and design parameters (including the targeting methods used for eligibility determination) from its administrative database. The two databases are not yet linked at the program level, which limits the ability to use the information on targeting methods (from the administrative database) with the information on distributional performance (from the household survey database). Chapter 5 presents information on the prevalence of different targeting methods, alone or mixed, from the administrative database. As of June 2021, ASPIRE captures 2,623 individual social assistance transfer programs in its administrative database. The household survey database includes only social assistance program categories, aggregating the individual social assistance programs recorded in household surveys. As of June 2021, there were 857 individual social assistance programs captured in the most recent surveys of the 125 countries covered by ASPIRE’s household survey database. Although these represent only 30 percent of the programs captured in the administrative database, they tend to be the largest programs focused on households.11

In ASPIRE, indicators are presented for eight categories of social assistance programs: unconditional cash transfers, conditional cash transfers, social pensions, food and in-kind transfers, school feeding, labor intensive public works, fee waivers and targeted subsidies, and other social assistance. Where there are multiple programs observed in the questionnaire within a single category, the results for these programs are combined within the category. For example, a country may have both a “universal” agebased child allowance and a guaranteed minimum income program identified in the survey questionnaire. Since they are both unconditional cash transfers, they are reported on a single line despite having very different approaches to eligibility and presumably different program-specific results. Grouping the data facilitates the processing of hundreds of surveys in uniform and automatable ways. The results help in understanding world social assistance programming in aggregate, but the grouping is less helpful for understanding the results of specific programs or the potential of different targeting methods.12

The collation by category can be sensitive, depending on the programs that have been aggregated. For Ukraine, for example, there are six different unconditional cash transfer (UCT) programs observed in the questionnaire for the Household Living Conditions Survey. Three of these programs differentiate eligibility by welfare level (help for low-income families, help for single mothers, and assistance for children under guardianship or care) and three only by demographic characteristics/age of the children in the family (childbirth help, childcare benefit for children younger than three years,