7.12 Impacts on Poverty and Inequality

488 | Revisiting Targeting in Social Assistance

recipients of social assistance transfers generally maintain their work effort and thus presumably their income; indeed, sometimes they increase these (see the discussion in chapter 2).

The challenge is more significant for countries that use consumption or expenditure to measure welfare. For an existing program, consumption or expenditure cannot be observed exclusive of any transfers that the program provides without an assumption that the individuals consume x percent of the transfer. Therefore, all transfers received under the program cannot be subtracted to get a different welfare measure for each person, ci –ti, where ti is the amount of transfer that person i received. In this case, it is important to assume the value x or estimate the income/consumption elasticity to estimate ci –xti as a counterfactual. Unfortunately, there is often no good way to estimate each person’s counterfactual from a single cross-sectional data set.11 In some instances, the assumption that there is no behavioral response to the social protection program may be a good one, while in others, it may be far from the truth.

Acknowledging the limitations, some sense of the impacts of the program on poverty and inequality can still be established. A perfectly targeted program may have no impact on poverty rates if the benefit or coverage is too small, but it can have an impact on the poverty gap and inequality as it brings people closer to the poverty line. From a targeting point of view, reductions of the FGT(1) and Gini are more relevant. The benefit-cost ratio is a measure that shows how much of a $1 transfer goes toward reducing the poverty gap. The benefit-cost ratio ranges from 0 to 1, and 1 is the upper bound where all transfers go to poverty gap reduction.

Using the 10-person economy and three scenarios in table 7.12, it can be shown that scenario 5, which transfers the precise income gap to each poor individual, fully reduces both the poverty headcount and the poverty gap and has a cost-benefit ratio of 1, while the Gini coefficient would drop 29 percent. Scenario 2 moves two of the four poor individuals from poverty, leading to a 50 percent reduction in the poverty headcount. The impact on the poverty gap is 53 percent as the two individual beneficiaries are not among the poorest. The total amount of money transferred per individual

Table 7.12 Impacts on Poverty and Inequality

Scenario 5 Scenario 2 Scenario 4 ∆FGT(0) (%) ∆FGT(1) (%) ∆Gini (%) Cost-benefit ratio

100 100 29 1

50 0 53 30 18 9 0.70 0.40

Source: Original compilation for this publication. Note: FGT(0) = poverty headcount; FGT(1) = poverty gap.