1.1 Contrasting Policy and Budget Scenarios: Base Case

48 | Revisiting Targeting in Social Assistance

rectangle ABCD (shaded in light blue) equals that of triangle AZH. This would raise the welfare of the poorest person to B, and much of the budget would be spent on those above the poverty line. (This would be analogous to paying everyone $6 dollars, with a budget of $30 million.) • A universal benefit that is large enough to eliminate poverty would result in welfare along line ZE, raise the income of the poorest person to the poverty/guarantee line, but use a budget of AZED, which is clearly larger than the budget in the prior scenarios. (This would be analogous to paying everyone $30, with a budget of $150 million.)

Figure 1.1, which illustrates the theoretical potential of targeting, relies on the assumption that it is possible and costless to identify who needs what benefits. But this assumption must be tempered by realism about errors and costs (themes that recur throughout the book, with their first detailed treatment in chapter 2). • It is not possible to know perfectly who is poor or what their income is; errors will occur, often including substantial errors. The theoretical power of targeting will diminish as a consequence, by an amount that depends on the frequency of the errors and where they occur in the welfare distribution.

Figure 1.1 Contrasting Policy and Budget Scenarios: Base Case

Posttransfer income

E

C

D

Z H

B

A

Pretransfer income

Sources: Based on Besley and Kanbur 1993; Coady and Le 2020.

Targeting within Universal Social Protection | 49

• Moreover, such an attempt at selectivity or customizing benefits has costs:

{ There are administrative costs in gathering the information used to differentiate eligibility or benefits. { People may face transactions cost as part of the administrative process of proving their eligibility, which reduces the net benefit to them.8 { There may be stigma or social discord as a result of making distinctions between people of different welfare levels. { Some criteria for determining eligibility or customizing benefits could create unwanted incentives. Particular attention is given to the concern that families could reduce work effort to stay poor enough to qualify for benefits in programs with an above/below threshold, or they may cease to work altogether with a minimum income guarantee formulation. { Political support for programs that treat some people differently than others may be less than for those that treat all alike. And with lower political support, the budgets for the programs may be lower.

Targeting is not an objective itself but a tool to be deployed on a selective basis. Policy makers must decide whether, how broadly or narrowly, and how to target a program based on their appreciation of the magnitude of the benefits of concentrating resources where they are most needed versus the magnitude of the various errors and costs and how these vary among different policy options.9 This book aims to provide policy makers updated information they can use in their decision-making.

The problem setup is simple and intuitive, but finding answers or generating consensus around the preferable degree of targeting is much harder. The budget and administrative costs are measured in dollars, but stigma and political division are not. The errors of inclusion or exclusion will vary depending on the data or method of selection used. There may be a link via political economy between the available budget, narrowness of selection, selection method, and errors. The trade-offs among some of the dimensions are not well mapped and, where they are partially mapped, they are somewhat variable across contexts. But raising taxes is always hard and there are so many calls for government expenditures that the question of how to make the best use of scarce resources keeps the issue of targeting the neediest perennially on the table.

The remainder of the book helps in generalizing from or thinking about different parts of this simplified version of the pros and cons of differentiating eligibility or benefits to concentrate resources on those most in need.