The targeting benefit of conditional cash transfers

https://doi.org/10.1016/j.jpubeco.2020.104330Get rights and content

Highlights

  • Sending a child to school can result in a discrete loss of child income.

  • Conditional cash transfers can target money to lower consumption households.

  • This targeting benefit can be expressed in terms of five sufficient statistics.

  • One third of the Progresa budget should go to a conditional transfer.

Abstract

Conditional cash transfers (CCTs) are a popular type of social welfare program that make payments to households conditional on human capital investments in children. From a targeting perspective, compared to unconditional cash transfers (UCTs), CCTs are costly because they exclude some low-income households as access is tied to normal investments in children. However, we argue that conditionalities on children’s school enrollment offer an unexplored targeting benefit over UCTs: CCTs target money to households who forgo a discrete amount of child income. We show that the size of the targeting benefit relative to the targeting cost of CCTs is directly related to the consumption differences between schooling and non-schooling households and two elasticities already popular in the literature: the income effect of a UCT and the price effect of a CCT. We estimate these elasticities for a large CCT program in rural Mexico, Progresa, using variation in transfers to younger siblings to identify income effects. In this setting, we find that the targeting benefit is a similar magnitude to the cost of excluding some low-income households; this implies that 33% of the Progresa budget should go to a CCT over a UCT based on targeting grounds alone.

Introduction

Conditional cash transfers (CCTs), cash transfers directed to poor households made conditional on investments in children’s human capital, have dramatically risen in prominence over the last two decades (Fiszbein and Schady, 2009). In 2016, 63 low- and middle-income countries had at least one CCT program, up from 2 countries in 1997 (Bastagli et al., 2016). CCTs aim to both alleviate current poverty by directing transfers to poor households as well as reduce future poverty by tying access of transfers to investments in children’s human capital. However, it is argued that these two aims can be at odds with one another as low-income households may find the conditions too costly to comply with and thus be excluded from receiving aid (Baird et al., 2011, Freeland, 2007). Unconditional cash transfers (UCTs), cash transfers directed to poor households but with “no strings attached”, are therefore thought to be superior at alleviating current poverty.

This paper argues that there exists an unexplored targeting benefit of imposing conditions to send children to school on cash transfers.1 The central idea behind this benefit is that sending a child to school is a lumpy investment where the opportunity cost of this investment is forgone child income. CCTs are beneficial from a targeting perspective because they direct money to the set of households who forgo a large amount of child income. We argue that this benefit mitigates the cost of excluding those households who are too poor to comply with the conditions. Thus, we argue that there exists a targeting trade-off when choosing how to allocate a budget between a CCT and a UCT, and that it may, therefore, be optimal to allocate some of a budget to a CCT based on targeting grounds alone. The objective of this paper is to theoretically highlight and empirically quantify this targeting trade-off so as to ascertain the extent to which the targeting benefit is an important advantage CCTs can offer over UCTs.

To illustrate this targeting trade-off, consider a set of parents earning heterogeneous incomes facing the decision of whether to send their child to school. Parents trade-off higher household consumption today (if their child works) with improved future incomes for their child (if their child goes to school). All else equal, there will exist a parent with income ỹ who is just indifferent between sending their child to school or to work, and parents with income above this cutoff will choose to send their child to school while those below will not. Just above this cutoff, household consumption will discretely drop by the amount of the child’s potential earnings; this discrete drop in household consumption is illustrated in Fig. 1, where ychild denotes potential child income. Relative to a UCT, a CCT will exclude those households earning parental incomes below ỹ from receiving aid.2 However, a CCT will direct more money to those households forgoing child income, who potentially have lower consumption.3

The first goal of this paper is to develop a theoretical model that captures the targeting trade-off of CCTs versus UCTs. While we are not the first to investigate the costs versus benefits of imposing conditions on cash transfers (see, for example, Fiszbein and Schady, 2009, Baird et al., 2011, Baird et al., 2013, Benhassine et al., 2015), to the best of our knowledge, we are the first to analyze the CCT vs. UCT problem within an optimal redistribution framework. We consider a two-generation world in which households consist of a parent and a child and are heterogeneous with respect to parent income and child ability. Parents maximize household utility over the two generations by choosing whether to send their child to school or to work in the first generation. Schooling results in higher utility in the second generation but comes at the cost of a discrete loss of consumption in the first generation. We make the realistic assumption that parents cannot borrow across generations. We consider a utilitarian social planner whose objective is to maximize the sum of lifetime utility across a set of eligible households, where the set of eligible households has been predetermined (say via proxy-means testing or geographical targeting).4 The planner has a fixed budget to distribute to these households in the first generation and decides how to allocate this budget between a CCT versus a UCT. To focus solely on the targeting trade-off, we assume parents make education decisions at the socially optimal level, thereby abstracting from conventional motives to condition transfers; consequently, the planner’s sole objective is to transfer resources to the households that have the highest marginal utility of consumption in the first generation.5

The planner faces the following trade-off: by increasing the CCT, she increases the share of money received by the schooling households (i.e., the households who forgo child income). We refer to the welfare gain experienced by the schooling households as the targeting benefit. However, this comes at the cost of decreasing the UCT, which in turn decreases the share of money received by the non-schooling households (i.e., the households who have lower average parental income). We refer to the welfare loss experienced by the non-schooling households as the targeting cost. Because schooling households forgo child income, they may have higher average marginal utility of consumption relative to the non-schooling households. Our main result then is that it is possible for the targeting benefit to outweigh the targeting cost, meaning that it is optimal for the planner to allocate some or potentially all of her budget to a CCT based on targeting arguments alone. This result goes against the current consensus that CCTs are unambiguously worse than UCTs at distributing funds to those who value them the most.

One potential concern with our framework is that while the schooling households may have lower consumption in the first generation, by revealed preference, they have higher lifetime utility. Thus, CCTs will direct more money to households with higher lifetime utility. Our main result arises from the fact that parents cannot move resources across the two generations.6 Hence, when deciding how to best distribute a budget in the first generation, the planner is only concerned with directing money to those who value it the most in the first generation. When we extend our model to allow the planner to redistribute a budget in the second generation also, the concern that we on net give more money to higher lifetime utility households is mitigated because the children who go to school today earn more as adults, and, thus, are less likely to receive transfers as adults.7

The second goal of this paper is to investigate whether the empirical magnitude of the targeting benefit is large enough to warrant policy relevance. In a similar spirit to the Baily-Chetty unemployment insurance (UI) literature (Baily, 1978, Chetty, 2006a), we show that the targeting benefit relative to the targeting cost can be expressed in terms of the average marginal utility of consumption of the schooling households relative to the non-schooling households, the share of households sending their child to school, and the effect that raising the CCT has on the UCT via the budget constraint.8 Average marginal utilities can be estimated using consumption distributions for schooling and non-schooling households along with estimates of the curvature of utility over consumption taken from the literature. Moreover, we show that the budgetary effect that raising the CCT has on the UCT can be expressed in terms of two elasticities already popular in the cash transfer literature: the income effect of a UCT, which measures how the share of children in school changes with the UCT, and the price effect of a CCT, which measures how the share of children in school changes with the CCT. These behavioral elasticities allow one to infer how enrollment changes with the transfer schedule and, in turn, calculate how the UCT must change with the CCT so as to satisfy the budget constraint.

We then move to our empirical application where we estimate the targeting trade-off in the setting of Progresa, a large CCT program in rural Mexico that started in 1997. The largest component of Progresa was the cash transfer paid to mothers conditional on their school-age children attending school on a regular basis. These grants were substantial: for example, a mother received 255 pesos per month, or 44% of the typical male laborer’s monthly earnings in these rural communities, if her ninth grade daughter was enrolled in school (Schultz, 2004). Using this setting, we first estimate income and price effects. To identify price effects, we exploit the fact that the introduction of the CCTs was randomized at the locality level. To identify income effects, we use variation in transfers to younger siblings below the age of 12 years, as enrollment of children below the age of 12 is almost 100% (prior to receiving grants).9 Thus, transfers to these younger siblings can be viewed as unconditional transfers to the household. This novel identification strategy allows us to estimate these elasticities in the same setting using a reduced-form specification.10 Using detailed panel data from 1997 to 1999, we estimate income and price effects for secondary-school-aged children (children aged 12–15 years). We find income effects are 48% as large as price effects.

Using these elasticity estimates along with household consumption data, we evaluate the size of the targeting benefit relative to the targeting cost for households in Progresa villages with secondary-school-age children. Under the observed Progresa transfers, we find that this ratio is substantial: the targeting benefit is 79% as large as the targeting cost. We then calculate the share of the Progresa budget that should be allocated to a CCT over a UCT based solely on targeting grounds (i.e., we calculate the share that equates the targeting benefit to the targeting cost).11 We find that 33% of the Progresa budget should go to a CCT, indicating that the targeting benefit is a quantitatively important benefit of CCTs. This result arises because the schooling households have, on average, lower consumption relative to non-schooling households (in absence of any transfers). This is in turn a consequence of two factors. First, child incomes are large: teenage children who work report earning 80% as much as their fathers. Second, because Progresa was only offered to poor households in poor villages, there is limited parental income inequality among eligible households. Hence, allocating some of the budget to the CCT allows the planner to better target transfers to those who have higher marginal utility of consumption.

The rest of the paper proceeds as follows: Section 2 sets-up our theoretical framework and derives our main theoretical result, Section 3 derives the sufficient statistics needed to estimate the size of the targeting benefit relative to the targeting cost, Section 4 estimates the income and price effects for Progresa, Section 5 calculates the size of the targeting benefit relative to the targeting cost in the context of Progresa and estimates the optimal share of the Progresa budget to be allocated to a CCT based on the targeting trade-off. Finally, Section 6 concludes.

Section snippets

Theoretical framework

In this section we develop a theoretical framework to highlight the targeting trade-off that arises when comparing CCTs to UCTs.

Sufficient statistics for estimating the targeting trade-off

We now develop a way to calculate the size of the targeting benefit relative to the targeting cost from empirically observable objects (sufficient statistics). This method will allow us to determine the optimal CCT/UCT mix based solely on targeting grounds and, therefore, will be useful in determining whether the targeting benefit is a quantitatively important advantage of CCTs. From Eq. (1), we need four quantities: the average marginal utility of consumption for schooling households, ucc(1),

Estimating income and price effects for Progresa

The remainder of the paper will focus on determining the empirical importance of the targeting benefit in the context of Progresa, a large CCT program in rural Mexico. In this section, we will focus on estimating the income and price effects, which are necessary to evaluate the targeting trade-off. First, we briefly discuss the Progresa program. Second, we discuss our identification strategy, focusing on how we identify income effects from a pure CCT program. Finally, we estimate the income and

Quantifying the targeting trade-off for Progresa

We now quantify the targeting trade-off for Progresa households. Using data on consumption for schooling and non-schooling households, combined with our income and price effect estimates, we first evaluate the size of the targeting benefit relative to the targeting cost under the observed Progresa schedule. We then calculate the optimal CCT/UCT mix based solely on this targeting trade-off. Finally, towards understanding how the magnitude of the targeting benefit relates to the more studied

Conclusion

In this paper, we argue that there exists an unexplored targeting benefit of imposing conditions on cash transfers to send children to school: by imposing conditions, a planner can direct more money to those households who forgo a discrete loss of child income. We argue that this benefit mitigates the cost of excluding households who find it too costly to send their children to school. Within our theoretical framework, we show that a social planner faces a key trade-off: by increasing the share

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    We would like to thank the members of Katy’s dissertation committee, Raj Chetty, Pascaline Dupas, Melanie Morten, and Petra Persson, for their extremely helpful comments, guidance, and support on this project. We would also like to thank Arun Chandrasekhar, Marcel Fafchamps, Caroline Hoxby, Juan Rios, Meredith Startz, anonymous referees, and participants at various seminars at Stanford University and the World Bank for their useful comments and suggestions. Finally, we’d like to thank The Ric Weiland Graduate Fellowship in the Stanford School of Humanities and Sciences for financial support. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.

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