Essay 5: Is Targeting the Poor Important for Outcomes Other Than Poverty?

52 | Revisiting Targeting in Social Assistance

generalize to other shocks, including economic shocks, whether occasioned by a global financial crisis or global pandemic. And it recognizes that helping households manage idiosyncratic shocks is an important aspect of social protection.

Adaptive social protection includes building resilience ex ante and responding quickly and appropriately once shocks hit, and both may imply targeting. Because the poor or near poor have so little ability to handle losses, improving the level or reliability of their incomes is important. Thus, programs that are designed to build resilience through training, financial inclusion, and asset transfers often focus on the poor, differentiating eligibility. The package of services is often common to all participants, although sometimes the size of the asset transfers may vary as well as whether they are provided as grants or loans. To ensure programs’ ability to respond with agility when a shock hits, systems and financing need to be set up ex ante as well, although responses are likely to be differentiated at least somewhat by the severity of the calamity. Natural disaster responses usually focus on geographic areas. Responses to economic crises may focus on the poorer, or on those whose jobs are the most affected. Responses to idiosyncratic shocks may require fewer resources overall, but an agile mechanism is needed. How delivery systems and targeting mechanisms can serve or be adapted to serve in response to shocks is a recurring theme in chapters 3, 4, and 5.

Essay 5: Is Targeting the Poor Important for Outcomes Other Than Poverty?

Larger effects on human capital and economic behaviors among the poorest are consistent with the logic that the marginal impact of a dollar of transfer income declines with base income. The logic suggests that the impact of a $1 transfer on a person living on $1 a day is much greater than that on a person living on $5, $10, or $50 a day. This gives additional weight to the economic rationale for focusing resources on the neediest— on whom the impacts on poverty and other dimensions of welfare will be greatest. This theory has been confirmed by evidence.

The body of impact evaluations confirms that social assistance transfers reduce immediate money metric poverty, but also that they improve a long vector of outcomes that are commonly associated with poverty or viewed as part of multidimensional poverty. For example, research on this looks at cash transfers (Attah et al. 2016; Bastagli et al. 2016; Davis et al. 2016), public works programs (McCord and Slater 2009; Subbarao et al. 2013), school feeding programs (Bundy 2011; Drake et al. 2017), Africa (Ralston, Andrews, and Hsiao 2017), and Asia (World Bank and DFAT, forthcoming).

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Research shows that to various degrees, depending on program design and context, transfers have raised school enrollment; increased the use of health services for children; improved the mental health, happiness, or optimism of family members; raised social capital; reduced intimate partner violence; reduced risky behaviors among teens; allowed households to invest in their livelihoods, pay down debts, or save; and generated positive local multiplier effects. Research shows that some programs have increased nutritional outcomes or learning. This evidence draws from a large range of programming with various targeting methods and outcomes. Importantly, where study design has allowed such measurement, the impacts have been larger among the groups within the program that were most disadvantaged at the beginning (Bastagli et al. 2016; OECD 2019). For example, in looking at the protective effects of Ethiopia’s rural Productive Safety Net Program in the months since COVID-19 hit, Abay et al. (2020) show that the program generally protected food security among participant households, with food security indicators for participant households declining much less than those among the poor, nonparticipant households. Moreover, the program had the greatest effects among the poorest participants and those in the most remote areas. In an evaluation of a school feeding program in Ghana, no effects were found on height for age for the whole treated population (all income levels and ages 5–15). However, disaggregating the results by poverty status highlighted a positive effect of school meals on height for age in children ages 5–8 in poor households of 0.21 standard deviation, nearly twice the size of the effect observed in the overall population ages 5–8 (Gelli et al. 2019).

In their evaluation of the Pakistan Waseela-e-Taleem conditional top-up to the Benazir Income Support Program, Cheema et al. (2016) find that the impact of the Waseela-e-Taleem program on enrollment was higher for children in the poorest third of households in the evaluation sample, at 18 percentage points, compared with 8 percentage points for children in the other two-thirds of households. In Cambodia, Filmer and Schady (2008) show that the impact of the Japan Fund for Poverty Reduction scholarship program on enrollment was approximately 50 percentage points for girls in the poorest two deciles of a composite measure of socioeconomic status, compared with 15 percentage points for girls in the richest two deciles. For Nicaragua, Maluccio and Flores (2005) show marked differences in impacts on school enrollment by initial welfare levels—about 5 percentage points for the nonpoor, 15 percentage points for the poor, and 25 percentage points for the extreme poor. For Indonesia, Sparrow (2004) shows that a scholarship program implemented during the East Asia financial crisis had the largest effects on the poorest students. And impacts are often larger when the transfer is higher (for example, Bastagli et al. 2016; Ralston, Andrews, and Hsiao 2017).