metadata: authors: 0: author: Rodriguez Castelan,Carlos
count: World
docna: 0: docna: Conditionality as targeting? : participation
            and distributional effects of conditional cash transfers
docty: Policy Research Working Paper
subtopic: Health Care Services Industry,Disability,Educational Sciences,Poverty Impact Evaluation,Poverty Monitoring & Analysis,Services & Transfers to Poor,Economic Assistance,Access of Poor to Social Services,Inequality,Poverty Assessment,Poverty Diagnostics,Poverty Lines,Small Area Estimation Poverty Mapping
teratopic: Poverty Reduction,Social Protections and Labor,Macroeconomics and Economic Growth
abstracts: cdata!: Conditional cash transfer programs,
            whereby transfers to households are conditional on school
            attendance or health checkups, have become a widespread
            policy tool. They are viewed as a means of immediate poverty
            alleviation through the cash payments, and as a foundation
            of long-term poverty reduction through the emphasis on human
            capital formation. Because targeted transfers are usually
            conditioned on the consumption of normal goods, richer
            eligible households are more likely to consume more
            educational and health care opportunities than poorer ones.
            Thus, the eligible poorest households may benefit least from
            conditional cash transfers even to the extent that they may
            not participate at all. If conditionality is conceptualized
            as a cost at the margin, it may be leading poor households
            to opt out. This paper proposes a framework to model
            household decision making on participation (or not) in cash
            transfer programs depending on whether a conditionality
            exists. The paper outlines the optimal size of the cash
            transfer such that a fixed government budget maximizes the
            poverty reduction. The paper also shows that unconditional
            cash transfers may be preferable over conditional cash
            transfers if a government has a sufficiently high degree of
            poverty aversion, that is, if, beyond the poverty headcount,
            the government cares about how poor the poor are or the
            distance of the poorest among the poor below the poverty
            line. This basic argument carries over from income poverty
            to education poverty. The framework can be useful in shaping
            the recent discussion on the merits of universal benefits
            over conditional transfers in reducing poverty.
repnme: repnme: Conditionality as targeting? :
            participation and distributional effects of conditional cash transfers
display_title: Conditionality as targeting :
            participation and distributional effects of conditional cash transfers
listing_relative_url: /research/2017/01/27088300/conditionality-targeting-participation-distributional-effects-conditional-cash-transfers
topicv3: Poverty m1326687 695,Poverty Measurement and Analysis m1326941 707,Education m1327048 470,Cash Transfers m1327437 1608,Health m1504661 3480
publishtoextweb_dt: 2017-01-12T00:00:00Z
historic_topic: Poverty Reduction,Social Protections and Labor,Macroeconomics and Economic Growth
no_of_pages: 42
author_keys: 0: author_key: 1180219
model_extractions: WPS7940 Policy Research Working Paper 7940 Conditionality as Targeting?

Participation and Distributional Effects of Conditional Cash Transfers _Carlos Rodríguez-Castelán_ Poverty and Equity Global Practice Group January 2017
Policy Research Working Paper 7940

# **Abstract**

Conditional cash transfer programs, whereby transfers to households are conditional on school attendance or health checkups, have become a widespread policy tool. They are viewed as a means of immediate poverty alleviation through the cash payments, and as a foundation of longterm poverty reduction through the emphasis on human capital formation. Because targeted transfers are usually conditioned on the consumption of normal goods, richer eligible households are more likely to consume more educational and health care opportunities than poorer ones. Thus, the eligible poorest households may benefit least from conditional cash transfers even to the extent that they may not participate at all. If conditionality is conceptualized as a cost at the margin, it may be leading poor households to opt out. This paper proposes a framework to model household decision making on participation (or not) in cash transfer programs depending on whether a conditionality exists. The paper outlines the optimal size of the cash transfer such that a fixed government budget maximizes the poverty reduction. The paper also shows that unconditional cash transfers may be preferable over conditional cash transfers if a government has a sufficiently high degree of poverty aversion, that is, if, beyond the poverty headcount, the government cares about how poor the poor are or the distance of the poorest among the poor below the poverty line. This basic argument carries over from income poverty to education poverty. The framework can be useful in shaping the recent discussion on the merits of universal benefits over conditional transfers in reducing poverty.

This paper is a product of the Poverty and Equity Global Practice Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at crodriguezc@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Conditionality as Targeting? Participation and Distributional Effects of Conditional Cash Transfers**

Carlos Rodríguez-Castelán<sup>‡</sup>

**JEL Classification:** H21, H31, H41, I32,

**Key words:** Cash Transfers, Provision of Welfare Programs, Poverty, Household decision making

> ‡ Senior Economist. World Bank. E-mail: crodriguezc@worldbank.org. The author is especially grateful to Ravi Kanbur for numerous discussions, revisions, and insightful comments. This version of the paper has benefited from comments by Margaret E. Grosh, Samantha Lach and Luis-Felipe Lopez-Calva. An earlier version of this paper under the title of “Participation of the Poorest and Distributional Effects of Conditional Cash Transfers” was presented at the 2011 American Economic Association Annual Meeting, and benefited from helpful comments and suggestions from Kaushik Basu, Peter Brummund, Joerg Ohmstedt, Eswar S. Prasad, Jeffrey T. Prince, Mario Ramirez Basora, David E. Sahn, Liliana Sousa, and Russell Toth, as well as seminar participants at the Brookings Institution, the International Food Policy Research Institute, and the Development Workshop at Cornell University. The findings, interpretations, and conclusions in this paper are entirely those of the author. They do not necessarily represent the views of the World Bank Group, its Executive Directors, or the countries they represent.
# **1. Introduction**

Recent evidence on the lack of a long-term impact of conditional cash transfer (CCT) programs represents an invitation to researchers to reopen the door on our understanding of the functioning of these schemes and the cases in which they may (or may not) operate most effectively. The objective of CCTs is usually twofold: immediate poverty alleviation through cash benefits and long-term poverty reduction through human capital formation. Programs such as _Prospera_ (formerly _Oportunidades_ ) in Mexico, _Bolsa Família_ in Brazil, and _Familias en Acción_ in Colombia transfer cash to households conditional on the fulfillment of certain requirements by the child and parents, notably, school enrollment and periodic health and nutrition checkups. An extensive body of literature evaluating CCT interventions has found significant positive effects of participation on household use of educational and health services, while concurrently reducing poverty and child labor.<sup>1</sup> CCTs are found to have reduced current consumption or income poverty significantly, though the evidence linking final outcomes in health and education (beyond increased enrollment and health visits), such as cognitive development and child height, is more split (Fiszbein and Schady 2009).

Notwithstanding this evidence, recent studies are beginning to cast doubt on how significant the benefits of CCTs are over the long term. Araujo, Bosch, and Schady (2016) look at the 10-year effects of Ecuador’s _Bono de Desarrollo Humano_ Program. Their findings suggest a modest increase in the probability that young women graduated from secondary school (2–3 percentage points); yet, they do not find evidence that the program’s cash transfers had an impact on attending tertiary education institutions or on the probability of working. In Cambodia, Filmer and Schady (2014) evaluate the medium-term impact of a scholarship program three years after it had ended. While they find an impact on completion rates (0.6 more years of schooling), they find no evidence of an effect of the program on test achievement, earnings, or employment or on the probability of teenage pregnancy or marriage. Evidence from Mexico is more mixed. Behrman et al. (2009) compare the effects of differential exposure to _Oportunidades_ on rural teenagers receiving transfers for 5.5 years relative to teenagers receiving them for 4.0 years. While the study finds 0.2 additional years of schooling among students in the treatment group (those with 1.5 years longer exposure); there is no evidence of an effect on achievement tests. The program is found to have a negative effect on labor market participation among boys.<sup>2</sup> Results also show a decline in migration rates among boys (6 percent less likely to migrate than the control group). Additional research on the subject based on nonexperimental evidence in Behrman, Parker and Todd

> 1 See, for example, Attanasio et al. (2005); Behrman, Sengupta, and Todd (2005); Bourguignon, Ferreira, and Leite (2003); Cardoso and Souza (2003); De Janvry and Sadoulet (2006); Glewwe and Olinto (2004); León and Younger (2007); Maluccio and Flores (2005); Schady and Araujo (2008); Schultz (2004); Todd and Wolpin (2006).

> 2 As discussed in the study, the effect of the program is ambiguous for the stage of the life cycle considered. The effect of schooling that substitutes for work appears to dominate the opposite effect, that is, once school is finished, the increase in human capital should lead to higher employment and wages.

2
(2011) indicates a decline in the rate of work among younger boys, no impact on the labor participation of older boys, and positive impacts of the program on work among older girls.

Other long term results are more encouraging for CCTs. For instance, Barham, Macours, and Maluccio (2014) look at Nicaragua’s _Red de Proteccion Social_ on educational attainment a decade after the program began. The study exploits the randomized phasing of the program to estimate the differential effect of the access of two treatment groups and considering individuals who had stopped receiving the transfer seven years earlier. It finds that boys who had received a transfer in early childhood (benefitting more intensely from the education transfer) had about 0.3 years more years of completed education, scored 0.2 standard deviations higher, and showed higher earnings from seasonal migration reflected in a 10–30 percent higher monthly off-farm income relative to the late treatment group. To assess the concern that CCTs may discourage work, Banerjee et al. (2015) reanalyze the results of randomized assessments of seven CCTs worldwide to study their effect on labor supply. Their analysis finds no systematic evidence that there is an undesirable effect on the propensity to work nor on the number of hours worked. Moreover, Banerjee et al. (2016) find proof of long-term (and growing) effects of an antipoverty program that includes an asset transfer in West Bengal, India, based on data from three survey waves. Over five years after having stopped receiving benefits, according to the study, households present increased consumption (25 percent), higher food security, more assets, higher earnings, and more financial stability than the control group. Mental and physical health indicators also show an improvement relative to nonbeneficiaries.

A related though different question to that of long-term impact is how efficient CCTs are in comparison with other unconditional programs. While this area has yet to be more profoundly studied, recent empirical research has started to shed some light. Baird et al. (2013) analyze data from 35 studies in 75 reports to compare the effectiveness of CCTs relative to UCTs in terms of schooling outcomes. Their review suggests that both CCTs and unconditional cash transfers (UCTs) increase the probability of enrollment and attendance, though the effects on test scores are moderate at best. Differentiating between intensity of conditioning, their analysis indicates that interventions that are explicitly conditional and monitor and penalize noncompliance have a larger impact than programs with no conditions or that have some conditions with minimum enforcement and monitoring. Özler, Baird, and McIntosh (2016) look at the sustained (medium-term) effects of a two-year CCT program compared with a UCT program among young women and adolescent girls in Malawi.<sup>3</sup> The study finds declines in HIV prevalence, teenage pregnancy and early marriage among the UCT group, unlike the CCT group, however these effects dissipated after the cessation of the unconditional grants. Conditionality, they conclude, could be limiting the social protection aspect of CCTs, even if it appears to be more effective in achieving behavioral change. The study also finds that children born to UCT beneficiaries

> 3 While the conditional transfer is based on attendance, recipients only need to show up to obtain the unconditional one.

3
during the program had higher height-for-age z-scores at follow-up. This study also concludes that although CCTs offered to out-of-school females at baseline produced an increase in educational achievement and sustained reduction in the total number of births, it caused no gains in health, labor market outcomes and empowerment. On the basis of a large randomized experiment in Morocco, Benhassine et al. (2015) find that a small UCT, explicitly labeled to be used for education, had a substantial effect on school participation, but that adding conditionality led to (small) negative effects. A “nudge,” the authors argue, may be enough to encourage human capital investment without the need for conditionality, which can lead to exclusion, while the lower administrative costs of UCTs make them more cost-effective than conditional ones. In a different kind of program, <mark>Dutta et al. (2014) look at the conditionality within India’s 2005 National Rural Employment Guarantee Act, which promises minimum wage employment to all rural households. The study finds that one of the reasons the program could be falling short of its potential on poverty reduction in Bihar (in addition to unmet demand for work) is that participation in the scheme is “far from costless” for workers. Individuals report a trade-off whereby they have to let go of other income-generating activities to participate in the scheme’s work.</mark> <mark>From the economic theory perspective any “condition” represents a constraint to both individual behavior and social welfare.</mark> CCTs make monetary benefits conditional on the consumption of normal goods, which implies program-eligible richer households are more likely to make use of more education and health services than poorer households. <mark>If the social planner chooses a costly condition to receive a cash transfer, the poorest eligible households may opt out of the program because they might face more difficulty meeting such a condition relative to the less poor eligible households. T</mark> he poorest households, in this way, may benefit least from CCTs, even potentially resulting in the poorest not participating at all.

This paper examines the extent to which household income plays a role in a family’s decision to participate in a CCT program. Knowledge of the nature of the household’s decision to enroll in CCTs can have implications for public policy. Particularly, a better understanding of the determinants of CCT enrollment could help increase participation rates among the poorest households, thereby boosting the effectiveness of public spending and improving the progressivity of CCTs.

The paper presents a partial equilibrium model to analyze the decisions of the poorest households to participate in CCT programs.<sup>4</sup> Following the optimal income tax literature and previous studies on household decisions to enroll in CCT programs, the paper assumes that the income distribution in a given economy already captures the difference in labor productivity across all households.<sup>5</sup> Furthermore, the analysis assumes the

> 4 Taking the overall transfer budget as given.

> 5 See Akerlof (1978), Arrow (1971), Besley and Coate (1991), Mirrless (1971), Stiglitz (1982). On dropouts in CCT interventions, see Alvarez, Devoto, and Winters (2008); on food stamp schemes, see Clarkson (1976); and on housing allowance programs, see Cronin (1982), Kennedy and MacMillian (1979).

4
government can identify each household’s income level, such that there is a critical income level at which eligible households are indifferent whether to participate or not participate in CCT programs to attain the socially optimal quantity condition. In particular, any household with an income level that is strictly less than such a critical income level will not enroll in the program.

To investigate the budgetary efficiencies underlying the analysis, this paper follows the notion of a cash benefit known as “guaranteed minimum income” to propose an optimal design for a CCT program.<sup>6</sup> The analysis shows that, if the government can compensate only what is needed to persuade each household to demand exactly the socially optimal quantity of the conditioned good (say, education), all households would participate in the program. The spending inefficiency in such a scenario would be lower with respect to an intervention contemplating a flat monetary transfer to all households, though such an optimal intervention has key shortcomings, not the least of which would be the administrative complexities in execution.

Could UCTs be superior to CCTs if the objective of the government is to minimize income poverty measures given a fixed budget? In the last section of the analysis, this paper identifies conditions under which CCTs dominate UCTs and vice-versa.<sup>7</sup> Specifically, it shows that UCTs could be preferred over CCTs if a government has a sufficiently high degree of poverty aversion, that is, if beyond the poverty headcount, it cares about how poor the poor are or how far away from the poverty line the poorest among the poor are living and, thus, about the distributional effects of CCTs on these indicators. On the other hand, it could be argued that the ultimate objective of CCT programs is not only short-term poverty alleviation but also the long-term benefit provided by increased consumption of a particular merit good, such as education. In this sense, the paper shows that the analysis and results carry over broadly for “education poverty.” The remainder of this paper is organized as follows. Section 2 presents a brief literature review of studies analyzing household decisions to participate in poverty reduction programs. Section 3 develops a model of household decision making to define an optimal cash transfer scheme such that a fixed government budget maximizes poverty reduction. This section also identifies the conditions under which conditional transfer schemes dominate unconditional ones and vice-versa, considering poverty measures that account for the intensity and severity of poverty. Finally, section 4 discusses policy ideas related to the dialogue on universal benefits and offers concluding remarks.

> 6 This analysis is similar to the one presented by de Janvry and Sadoulet (2006), although their analysis focuses on maximizing the gain in enrollment over the population instead of maximizing poverty reduction.

> 7 The idea of making meaningful comparisons among redistributive schemes has been noted previously. Blackorby and Donaldson (1988), for example, analyze Pareto efficiency under incomplete information for cash and in-kind transfers. Besley and Kanbur (1988) compare the poverty alleviation effects of marginal and inframarginal subsidies. Besley and Coate (1992) analyze incentive arguments to compare workfare and welfare programs to alleviate poverty. Currie and Gahvari (2008) contrast transfers in-cash and in-kind, concluding that paternalism and interdependent preferences are leading explanations for the existence of in-kind transfer programs. Cunha (2014) compares measured consumption and health outcomes under both in-kind food and in-cash transfers.

5
# **2. Literature review**

Studies on the determinants of participation in antipoverty programs have typically focused on public works programs. There is strong empirical evidence confirming a negative relationship between household wealth and participation in these programs (see, for example, Chirwa, Zgovu, and Mvula 2002; Gaiha 1996; Jalan and Ravallion 1999). But this negative association is driven by the design of the workfare programs, which were aimed at facilitating the self-selection of unemployed workers from usually poorer families.

More recently, a number of empirical studies have argued that poverty is associated with a higher probability of participating in CCTs. Heinrich (2007) presents evidence of the positive effects of Argentina’s _Becas Estudiantiles_ CCT program on student outcomes. In the first-stage regression of this paper, the author finds that students in households with a per capita income below a certain threshold (Arg$45 per month) were significantly more likely to participate. However, after controlling for an index of basic needs, the author finds that students in households with _lower_ per capita incomes were less likely to participate in the CCT program, a result that is in line with the framework outlined in this paper.<sup>8</sup> In a related study, Oosterbeek, Ponce, and Schady (2008) analyze the impact of Ecuador’s _Bono de Desarrolo Humano_ CCT program on school enrollment. They report the results of a regression of actual treatment status on background characteristics and find that poorer people are more likely to receive the transfer. These authors incorporate a third-degree polynomial of the poverty index in the children’s outcome estimation, but they only use the linear poverty index in the regression of actual treatment.

Two studies using the Urban Evaluation Survey (Encelurb) of Mexico’s _Oportunidades_ CCT program investigate the extent to which the urban component of _Oportunidades_ affects children’s outcomes and household consumption. Angelucci and Attanasio (2009) estimate a linear probability model of program participation among eligible households in treatment areas that incorporates second-degree polynomials for the poverty level as well as household income and consumption variables. They find that a household in the 75th percentile of the poverty distribution is 69 percent more likely to be a program participant than a household in the 25th percentile. They also conclude that participation is inversely related to both consumption and income. In addition to data on household income, consumption, and poverty level, their model includes information on transitory shocks and the local availability of schools and health centers. However, their model has some data limitations because it does not include key determinants of household decisions to participate in _Oportunidades_ , such as proxies for the relative price of schooling, parental preferences, and the opportunity costs of participating. Although their results do not directly support the outline presented in this paper, they conclude

> 8 Heinrich (2007) constructed an index of need using 20 measures from base data that include: dependents, household head occupation, whether household head is pregnant, type of home/tenancy/living conditions, distance to school, years of education of all household members, student hours worked outside/inside home, student age-grade difference, illness or disability, and household income.

6
that the observed low participation rate in the urban component of _Oportunidades_ may derive from self-selection caused by both insufficient information and inadequate financial incentives and that “further research to estimate the relative importance of these determinants is needed.” Finally, it is unclear why their participation model includes in the same regression measures of poverty level, food and nonfood consumption and income, instead of estimating different models using each of these measures of household well-being.

In the other study that uses the urban component of _Oportunidades_ , Behrman et al. (2012) estimate a first-stage discrete choice model of participation. Their results show that key correlates of poverty, such as dirt floor in the home and walls or ceilings made of provisional materials or the need for certain assets, increase the probability of participation in _Oportunidades_ . However, besides having access to a rich set of household and community characteristics, their model neither concentrates the information into one sole poverty index nor incorporates any second- or third-degree polynomials of household wealth. In addition, their participation model does not control for the costs of schooling and school and teacher quality variables.

Closer to the model outlined in this paper are the results of Alvarez, Devoto, and Winters (2008) and González-Flores, Heracleous, and Winters (2012) who, using discrete duration models, show a u-shaped relationship between the probability of dropping out of _Oportunidades_ and a poverty index score ( _puntaje_ ). Alvarez, Devoto, and Winters (2008) find that the likelihood that a household will leave _Oportunidades_ in rural areas is the highest among relatively wealthier recipients; it declines at diminishing rates as wealth decreases, and it increases again at the poorer end of the distribution. Correspondingly, González-Flores, Heracleous, and Winters (2012) study the determinants of the probability of dropping out from _Oportunidades_ in urban areas. In line with the framework outlined in this paper, they show that the poorest recipients, those below the 70th percentile of the poverty index score distribution, are more likely to drop out.

The analysis in this paper contributes to the literature by providing a formal framework to model the decision of households to participate in cash transfer programs contingent on whether there is a conditionality on the consumption of normal goods (typically, education and health) to receive the transfer. This paper also outlines an optimal cash transfer scheme if the government has a fixed budget and a poverty alleviation goal. Furthermore, this paper also outlines cases where, according to a government’s degree of aversion to poverty— if, beyond the poverty headcount, it cares about the depth of poverty and the distribution of poverty among the poor, unconditional cash transfers could be superior to conditional ones and vice-versa. As discussed in more detail in section 4, this framework can be helpful in framing the growing dialogue on universal benefit approaches relative to conditional transfers.

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# **3. A simple model to understand the distributional effects of cash transfers**

To investigate the distributional effects of cash transfers and their broader policy implications, this section proposes a model representing household decision making on participation in cash transfer programs. It then describes a simple model to outline the characteristics of an optimal transfer scheme using a fixed government budget. Finally, it presents conditions under which CCTs dominate UCTs and vice-versa on the basis of several commonly used poverty measures that take into account the intensity and severity of poverty.

# **3.1 The structure of household decision making**

# **The benchmark case**

Before developing the model, this section illustrates the potential drawbacks of the conditionality of cash transfers in terms of participation in these schemes if the condition is assigned to a normal good. Figure 1 depicts the impact of a CCT program in any given household. It assumes that a household can consume two goods,<sup>_x_</sup> 1<sup>(education) and</sup><sup>_x_</sup> 2<sup>(composite good). The household’s budget constraint prior to the</sup> implementation of the CCT program is represented by line AB, while the after-CCT program budget constraint is characterized by ACDE. Under this new budget constraint, if a household consumes at least a quantity<sup>_~~x~~_</sup> 1 of the good<sup>_x_</sup> 1<sup>, it receives a positive transfer, otherwise such a household does not receive the monetary</sup> transfer and remains on its original budget constraint.<sup>9</sup> This benchmark case also assumes that the household is a rational utility maximizer and, so, accepts a CCT if and only if it is made better off than it would be if it rejects the offer. The household’s preferences can be represented by a concave utility function _U_  _x_ 1<sup>,</sup><sup>_x_</sup> 2  , which also strictly increases in<sup>_x_</sup> _i_<sup>for</sup> _i_   2,1 . It also assumes heterogeneous preferences such that various types of households can be identified with different sets of indifference curves.

> 9 In the vast majority of the currently implemented CCT programs, the condition<sup>_~~x~~_</sup> 1<sup>on schooling requires the child to</sup> attend school a minimum of 85 percent of the time.

8
<!-- Start of picture text --> X2<br>Type Ill Household<br>A<br>\ ‘ Type II Household<br>ik AN . Zo Type | household<br>cK o77¥-<br>|<br>X2(II1)=X2+(II1) Xa(ll) X1 Xz2(Il) Xa(l) X22(I) B E Xi<br><!-- End of picture text -->
private optimal of the households.<sup>10</sup> In particular, some studies associate no participation or dropouts from CCT programs with weak preferences for the conditioned good.<sup>11</sup> However, a problem in estimating the reduced form of this benchmark case is the validity of the assumption that no-participation in the CCT program is a function of the underlying difference in the preferences of the targeted households; and, although this is a plausible explanation, the preferences of households that are eligible to receive the cash transfer (poor households) may in reality be quite similar within the cohort. In contrast, the approach proposed here assumes that no-participation in CCTs is a function of the income distribution within the targeted group.

In the partial equilibrium analysis, first, let us assume that the income distribution in the economy already captures the difference in labor productivity across all households. In addition, such a cumulative distribution function of household income, _F_  _y_ , is induced uniquely by an underlying asset distribution  _F_  _A_ =  0 _f_  _t dt_ .<sup>12</sup> Therefore, the economy’s income distribution _F_  _y_ lies between [,0 _~~y~~_ ] where _~~y~~_ represents the income of the richest household. Let<sup>_z_</sup> _y_<sup>be the poverty line induced from an implicit eligibility</sup> line _z A_ in the asset space, such that all those households with _yi_  _z y_ are eligible to participate in the CCT program.<sup>13</sup> Second, assume that all households share the same concave utility function _U_  _x_ 1<sup>,</sup><sup>_x_</sup> 2  that is strictly increasing in<sup>_x_</sup> _i_<sup>for</sup> _i_   2,1 .

From these assumptions, one can identify three cases among those households eligible for the CCT program. Case 1, illustrated in figure 2, includes all those households with a sufficiently large income such that their demand for good<sup>_x_</sup> 1<sup>prior to the implementation of the program was higher than the condition</sup><sup>_~~x~~_</sup> 1<sup>, and</sup> this demand increases after the cash transfer program is introduced. In particular, the pretransfer income threshold associated with the consumption of the socially optimal condition<sup>_~~x~~_</sup> 1<sup>can be defined as~</sup><sup>_y_. Therefore,</sup> ~ if the household’s income level<sup>_y_</sup> _i_<sup>lies between</sup> _y_  _yi_  _z y_ , then the CCT program has an inframarginal effect on household behavior. In contrast, figure 3 describes the case for those households that belong to an

> 10 The true private optimal is defined counterfactually by the absence of misguided beliefs, intrahousehold principalagent problems, or hyperbolic discounting.

> 11 Among some of the explanations of weak preferences for the conditioned good are (a) incomplete information,

> (b) imperfect and persistent private information about the nature of certain investments or about the expected returns, (c) conflicts of interest within the household that may result in incomplete altruism (parental decisions that are not fully consistent with what the child would have chosen herself, if fully rational), and (d) the unreasonably high opportunity costs of conditionality.

> 12 Most CCT programs base their eligibility criteria on data on household assets (see Sahn and Stifel 2003).

> 13 For instance, according to the general rules of operation of _Opordunidades,_ besides the presence of a child of school age in the household, eligibility depends on a cutoff value of a poverty index based on an asset valuation, so the eligibility line will be the same as the poverty line.

10
<!-- Start of picture text --> X2<br>A<br>D<br>= DN<br>Xi: Xi Xi: B E Xi<br><!-- End of picture text --> <!-- Start of picture text --> X2<br>A<br>D<br>Xi Xi B E Xi<br><!-- End of picture text -->
Next, this paper describes the basic household utility maximization problem when a CCT program is introduced. First, it assumes that the size of the cash transfer _t_ is exogenous to the model; then, in section 3.4, it solves for the equilibrium size of the monetary transfer given a fixed government budget.

# **The household model parameters**

If utility maximization holds, a household must participate in the CCT program if the utility associated with receiving the cash transfer, minus the cost of fulfilling the condition, is greater than the utility derived from nonparticipation. To help in providing a discrete dependent variable model, let us consider a single period model of a parent’s investment in education. For the purposes of this study, consider a representative child and so ignore issues of intrahousehold inequality in education. Parents are treated as individuals in that they are assumed to maximize a single utility function and face a budget constraint based on their joint income. The preferences of the parents in household _i_ are represented by a utility function, as follows:

> where _U_ (  ) is a quasi-concave and continuous function representing a strongly monotonic preference relation defined on the consumption of the bundle ( _xi_ 1,<sup>_x_</sup> _i_ 2 ) , so that<sup>_x_</sup> _i_ 1<sup>and</sup><sup>_x_</sup> _i_ 2<sup>are normal goods and denote the</sup> demand for schooling and the consumption of a composite good, respectively. The parameters<sup>_a_</sup> _i_ 1<sup>and</sup><sup>_a_</sup> _i_ 2 represent the parents’ preferences for schooling and all other goods.

The parents maximize _Ui_ subject to the budget constraint, as follows: where<sup>_y_</sup> _i_<sup>denotes household</sup><sup>_i_’s income,</sup><sup>_p_</sup> 1<sup>represents the cost of schooling, and</sup> _p_ 2 is the price of the composite good. Assuming an interior optimum, combining the first-order conditions leaves Equation (3) establishes that household _i_ ’s marginal rate of substitution between schooling and the composite good must be equal to the relative price of schooling, _p_ .

13
* After solving for household _i_ ’s demand for schooling, one can obtain a function<sup>_x_</sup> _i_ 1<sup>that is increasing</sup> in income and parents’ preferences and decreasing in the relative price of schooling, as follows:

Now assume that household _i_ is offered a cash transfer _ti_ , conditional upon consuming a schooling quantity greater than or equal to<sup>_~~x~~_</sup> 1<sup>(determined by the government, and usually requiring a monthly attendance</sup> rate of 85 percent of school days). The parents maximize equation _Ui_ subject to a new budget constraint, as follows: So, if household _i_ ’s demand for schooling exceeds the minimum required by the CCT program rules, the new demand for schooling will be an increasing function of the transfer, as follows: Thus, the decision of the parents in household _i_ to send their child to school in response to the conditional transfer depends on the utility derived from participation. Parents in household _i_ choose to enroll in the CCT program if the difference between the utility of participation and nonparticipation, defined as <sup>_V_</sup> _i_ * , is greater than zero.<sup>14</sup> This difference depends on the pretransfer income,<sup>_y_</sup> _i_<sup>, the expected cash</sup> transfer, _ti_ , the relative price of schooling,<sup>_p_</sup> _i_<sup>, and other characteristics that might independently affect</sup> participation,<sup>_X_</sup> _i_<sup>(for example, economic status and parental preferences). Thus</sup>

> 14 Where *

> <sup>_V_</sup> _i_<sup>is a continuous but unobservable response variable often defined in the literature as a latent utility</sup> function.

14
where <sup>_V_</sup> _i_ * is not directly observed, and one only observes the final decision of participation,<sup>_V_</sup> _i_<sup>, which is an</sup> indicator variable equal to 1 if the household participates in the CCT program and zero if it does not, therefore: Assume that the utility of the parents in household _i_ discussed above is represented by a log-linear utility function. Then, the expenditure on schooling if the household demands an amount of education that is * greater, or equal to, the CCT schooling condition<sup>_~~x~~_</sup> 1<sup>is</sup> _xi_ 1<sup></sup> ( _a_ 1 _yi_ /) _p_ 1 , that is, a constant fraction of wealth given any cost of schooling. The expenditure in schooling if the condition is met becomes * _xi_ 1  _a_ 1  ( _yi_  _t_ /) _p_ 1 , that is, a constant proportion of the income, plus the flat transfer for any cost of schooling.

Following King (1983), one can solve for the equivalent income function of the CCT scheme to identify the threshold value that defines whether or not the parental demand for schooling exceeds the CCT schooling condition so that the cash transfer is provided (or not). First, normalize to 1 the cost of schooling; the price of good<sup>_x_</sup> 2<sup>is then defined as</sup><sup>_p_. Compare the indirect utility functions of the expenditure minimizing commodity</sup> bundle that provides the same level of utility as the utility received from the subsidized commodity bundle, as follows: _E_ where<sup>_y_</sup> _i_<sup>denotes equivalent income. Equalizing (10) and (11) gives way to the equivalent income function of</sup> household _i_ , which is the value of income at which the CCT schooling condition generates the same utility as the actual income level, as follows: 15
# **The threshold value of income that determines the participation decision of the poor**

Consider the nonparticipating choice as the reference point for the definition of the threshold value of wealth, ˆ _y_ , in terms of equivalent income, as follows: Because the demand for schooling at the critical value of income is precisely the demand for schooling _E_ at the CCT schooling condition, plugging _~~x~~_ 1<sup></sup> _a_ 1<sup>_y_</sup> _i_ into (12) generates the threshold level of income that represents the cutoff between participation and nonparticipation in the CCT, as follows: Then, household _i_ ’s demand for schooling in terms of the threshold level of income is Figure 5 depicts the Engel curve of schooling (<sup>_x_</sup> 1<sup>) for all households eligible to enroll in a CCT</sup> program. The relevant eligibility line is assumed to be equivalent to the poverty line<sup>_z_</sup> _y_<sup>, so that the Engel curve</sup> is restricted to the interval of the income distribution _F_  _y_ that lies between <sup>,0</sup><sup>_z_</sup> _y_  .<sup>15</sup> Also, figure 5 portrays

> 15The eligibility line<sup>_z_</sup> _y_<sup>defined over the income space is induced from an implicit eligibility line</sup> _z A_ defined in the asset distribution. Most of the screening mechanisms of CCT programs give an important weight in their eligibility criteria to indicators derived by factor analysis on household assets. According to Sahn and Stifel (2003), such asset-based indicators are considered valid predictors of poverty and represent an alternative to the standard use of expenditures in

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both the pretransfer income associated with the CCT schooling condition,<sup>~</sup> _y_ , and the threshold level of income, _y_ ˆ . Thus, a poor household _i_ with an income level greater or equal to the critical value of income will participate in the program and will move from its original Engel curve to a higher curve.

defining well-being. This is particularly applicable to poor regions where there is limited capacity to collect consumption, expenditure, and price data.

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<!-- Start of picture text --> ;<br>y V zy y<br><!-- End of picture text --> f f ~~_—~~
where _q_ is the number of poor households, and _I_ is the total number of households in the economy. Moreover, using the threshold condition from (14) shows that the participation rate in the CCT program among eligible poor households in the economy is defined as follows: ˆ where _r_ is the number of poor households with income greater than the critical value of income, _y_ .

ˆ Because both _Q_ 0 and  _f_  _y_ /  _~~x~~_ 1 are continuous in _y_ and<sup>_~~x~~_</sup> 1<sup>and because both</sup> _y_  ( _x_ 1 / _a_ 1 )  _t_ and<sup>_z_</sup> _y_<sup>are continuous in</sup><sup>_~~x~~_</sup> 1<sup>, both have continuous derivatives for</sup> 0  _~~x~~_ 1  _a_ 1 _t_ . Then, using the Leibniz integral rule for 0  _~~x~~_ 1  _a_ 1 _t_ , gives because  _Q_ 0 /  _y_ ˆ  0 and _a_ 1<sup></sup> 0 . This result implies that, given a condition on the consumption of a normal good (education) and assuming a fixed budget, the government has to impose a sufficiently low CCT schooling condition to grant the transfer to increase the participation rates of the poorest households.

# **3.2 The government’s budget constraint**

In the previous section, two interesting parameters were incorporated into the household decision-making problem: (a) a socially optimal quantity of good<sup>_x_</sup> 1<sup>, defined as</sup><sup>_~~x~~_</sup> 1<sup>, and (b) a poverty line</sup><sup>_z_</sup> _y_<sup>defined by income,</sup> such that households with an income _yi_  _z y_ are eligible to participate in the CCT program. Next, assume that the government has a fixed budget  that is entirely allocated to the CCT program. Given household preferences, a share _B_ 1  _a_ 1   of the government’s budget would be allocated to consume the conditioned good<sup>_x_</sup> 1<sup>, while the complement</sup> _B_ 2    _B_ 1  _a_ 2   is spent by households to consume good<sup>_x_</sup> 2<sup>.</sup> 19
<!-- Start of picture text --> y‘<br>y+t<br>t=%Xi_-—<£ .<br>a ;<br>Y=0 Zy y<br><!-- End of picture text -->
# **3.3. The optimal conditional cash transfer scheme**

A fixed budget is a realistic assumption for those developing countries that have implemented CCT programs because their available fiscal resources are limited and have a high opportunity cost. In particular, the opportunity cost of increasing the available budget for transfer interventions would deteriorate public investment in other programs, which are also essential for economic growth (such as education, health care, employment, infrastructure, and sustainable development). Given modest real increases in poverty reduction funds in developing countries, an optimal CCT scheme aimed at minimizing poverty, subject to a fixed budget and to the attainment of the socially optimal quantity of the conditioned good, would be a powerful tool for policy makers.

Following the notion of a guaranteed minimum income, first used in England in 1795 (Salanié 2002), to design an optimal CCT scheme, the policy maker would like to act as a discriminatory monopsonist. Consider the extreme case in which the policy maker can make a separate bargain with all eligible households, compensating them only with what is needed to persuade each to accept the transfer and demand exactly the socially optimal quantity _~~x~~_ of the conditioned good (perfect discriminatory monopsonist). In the case of the proportional expenditure system, the optimal CCTs schedule _t_<sup>*</sup> can be described as follows:

* where the optimal transfer<sup>_t_</sup> _i_<sup>, also defined as a function of each household</sup><sup>_i_equivalent income</sup> max <sup></sup> ,0 _~~x~~_ <u>1</u>  _y E_ <sup></sup> if _xi_ 1  _~~x~~_ 1 , represents the difference in terms of money between the socially optimal  _a_ 1  quantity<sup>_~~x~~_</sup> 1<sup>and each household’s current demand of the conditioned good</sup><sup>_x_</sup> 1<sup>.</sup>

From  20  , the budgetary cost  * of the optimal CCTs schedule _t_<sup>*</sup> is given as follows: 21
where _J_ is the number of households that have a current demand of the conditioned good _x_ 1 below the socially optimal quantity<sup>_~~x~~_</sup> 1<sup>and where</sup> <sup></sup> _~~x~~_ <u>1</u>  _~~y~~ E_ <sup></sup> is the following:  _a_ 1  the mean income gap in terms of equivalent income to attain the socially optimal condition<sup>_~~x~~_</sup> 1<sup>.</sup> Alternatively, from (16), the budgetary cost of the flat CCTs schedule _t_ is where _I_ is the number of households that have an equivalent income above the critical value of income _y_ ˆ  _~~x~~_ 1 , but lower than the poverty line<sup>_z_</sup> _y_<sup>, and</sup><sup>_t_is the flat cash transfer.</sup>

* Whether the budgetary cost of the optimal CCTs schedule _t_ described in  23  is greater or less than the budgetary cost of the flat CCTs schedule _t_ from  25  will depend on the size of the flat transfer chosen by the policy maker and the relative position of the poverty line with respect to the monetary value of the condition<sup>_~~x~~_</sup> 1<sup>. Up to this point, this paper has taken the size of the flat transfer</sup><sup>_t_as exogenously given, but it</sup>

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<!-- Start of picture text --> Xi |<br>Engel curve under the -?<br>flat CCTs program 7 -<br>Engel curve under the »* -<br>optimal CCTs scheme ” ”<br>~<br>“<br>es “* | a<br>- -<br>”<br>-<br>ca<br>XG , - ” - o - Se<br>at<br>0<br>“yay Zy y<br><!-- End of picture text -->
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Moreover, assuming the policy maker chooses a poverty line and a socially optimal quantity such that that is, if the size of the flat transfer is greater than the poverty line, multiplied by a factor that is less than one (that is, 1/ 2 ), then the budgetary cost of the flat CCT program will be greater than the budgetary cost of the optimal CCT program.

In sum, if the policy maker is able to discriminate between two or more groups of households, total participation in the CCT program will be greater, while spending inefficiency may be lower in comparison with an intervention with a flat monetary transfer to all households. Greater distributional impact is also to be expected under the optimal CCT scheme. The main shortcoming of the optimal intervention, however, lies in the manifest administrative difficulty in field execution. This is mainly because of asymmetries in the collection of data on household income and expenditures and because of the complexity of perfect discrimination in reality. In contrast, as proven by several empirical studies, flat CCT programs are much easier to implement. Also, given a fixed budget, it may be difficult to incorporate the poorest of the poor into the optimal program because they are precisely the households that will require a larger than average transfer. Finally, as noted for the guaranteed minimum income scheme, this type of optimal intervention may have large disincentive effects on labor supply and might encourage recipients to evade the system by pursuing informal jobs or by understating their income and expenditures. Taking into account these critiques to the optimal CCT scheme, this paper discusses alternative poverty alleviation instruments below based on third-degree discrimination (that is, whereby discrimination is possible between groups of households (poor and extreme poor, or urban and rural), but, within each cohort, the transfer is equal).

# **3.4 The equilibrium transfer size**

Up to this point, the size of the transfer has been treated as exogenous. However, given a fixed budget, the equilibrium transfer size would depend on the total number of beneficiary families. It is thus a share of the threshold value of income, which is a function of the transfer size.

Before implementing a standard CCT scheme, the policy maker must choose a poverty line,<sup>_z_</sup> _y_<sup>, a CCT</sup> schooling condition,<sup>_~~x~~_</sup> 1<sup>, and a fixed budget to operate the program,, which is characterized by the triple</sup> 25
 _z y_ ,<sup>_~~x~~_</sup> 1,  that uniquely determines the threshold value of income and the participation rate in the CCT program.<sup>17</sup> Let a cash transfer _t_  _z y_ , _y_ ,ˆ  be a function of the critical value of income defined in (14), and, conversely, define the threshold level of income, _y_ ˆ  _~~x~~_ 1, _t_  , as a function of the cash transfer of size _t_ . Then, _t_  _z y_ , _y_ ,ˆ  should be treated as a fixed amount equal to  , such that (14) becomes For tractability, consider a uniform income distribution for all eligible poor households on the interval ˆ [,0<sup>_z_</sup> _y_ ], with _F_ ( _y_ )ˆ   _y_ /<sup>_z_</sup> _y_  and _F_ (<sup>_z_</sup> _y_ )  1. Combining both _F_ ( _y_ )ˆ and _F_ (<sup>_z_</sup> _y_ ) with a fixed budget  , the number of poor households _q_ , and the threshold value of income defined in (26), it is possible to solve for  : ˆ Thus, the equilibrium threshold value of income, _y_ , is obtained by substituting the  that solves (27) into (26), and, subsequently, the equilibrium transfer size is From (28), the following comparative static results are calculated:

> 17 It is assumed that the government’s budget  has an upper bound at ( _~~x~~_ 1  _z y_ ) / _a_ 1 and a lower bound at zero; otherwise, the problem becomes trivial. This implies that the cash transfer cannot exceed an amount _~~x~~_ 1<sup>/</sup><sup>_a_</sup> 1 ; otherwise, all poor households will participate in the program and would no longer be under the poverty line.

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Holding everything else constant, the relationship in (29) predicts a decline in the equilibrium size of the transfer as the government expands the eligibility criteria for the program. The logic behind this result is that a larger pool of potential recipients will reduce the average size of the subsidy, given a fixed budget. The result from (30) implies an increase in the equilibrium transfer size as the government chooses a higher CCT schooling condition to grant the subsidy. It is reasonable to assume that, given a fixed budget, a greater number of eligible poor households would fall short of the mandatory education requirement if the policy maker raises the CCT schooling condition. Because schooling is a normal good, the average transfer size will be larger among those poor households still demanding a quantity of schooling greater than the CCT schooling condition. Finally, as expected, the association in (31) shows that the equilibrium transfer size is an increasing function of government spending.

# **Measuring poverty**

Next, we follow the Foster-Greer-Thorbecke (1984) index (FGT index), which consists of a class of poverty measures that satisfy both the monotonicity and transfer axioms proposed by Sen (1976) and the decomposability property, to conduct meaningful comparisons between a CCT program and a UCT scheme. The FGT index (also known as the<sup>_P_</sup> <sup>measure) can aggregate information on poor households below certain</sup> income threshold conditions. It also represents several commonly used poverty metrics that take into account the intensity and severity of poverty, and it has the property of subgroup decomposability.

The FGT index estimates the weighted sum of the poverty gap ratios of a group of observations under an arbitrary poverty line and includes a parameter  that measures the sensitivity of the income distribution within those observations. Assuming a continuous income distribution that lies between  ,0  , the FGT index can be represented as 27
The FGT index represented in (32) groups several commonly used poverty indicators as special cases. In particular, if   0 , this index becomes the headcount ratio. This metric represents the number of households under the poverty line, although it fails to capture the extent to which each household income falls below the poverty line. If   1, the index becomes the income gap ratio for the mean poor income. This ratio measures the shortfall of poor households, on average, with respect to the poverty line. However, the income gap ratio is not sensitive to the distribution of incomes among the poor. If   2 , the FGT index becomes the square income gap ratio. This index computes the severity of poverty more accurately because it represents the square income gap ratio for the mean poor income. In this form, the index incorporates information on both poverty and income inequality among poor households. Higher order classes of poverty indicators can be derived as  becomes larger. Finally, as    , the FGT family of poverty measures tends to a Rawlsian social welfare function, that is, the index depends only on the welfare of the poorest household in the population.

# **3.5 Conditional versus unconditional cash transfers**

To conduct the comparison of the distributional effects for different levels of poverty aversion of a CCT program with respect to a UCT intervention, we focus on schooling as the conditioned good. Particularly, we * are interested in calculating the optimal conditioning of schooling,<sup>_~~x~~_</sup> 1<sup>, that minimizes the</sup><sup>_P_</sup> <sup>measure, subject</sup> to a fixed budget of size  and the equilibrium transfer size defined in (28). This is to address the question about whether UCTs may be superior to CCTs if the objective of the government is to minimize income poverty for different measures of aversion to the severity of poverty (that is, for different values of parameter   0 ).

Consider the problem 28
_E_ where _z_ is the poverty line in the equivalent income space.

> If   0 and there is a uniform distribution of income among all eligible poor households on the interval [,0<sup>_z_</sup> _y_ ], such that _F_ ( _z y_  _t_<sup>ˆ</sup> )   _z y_  _t_<sup>ˆ</sup> / _z y_  , the problem (33) becomes

Taking the derivative of the poverty headcount ratio with respect to the CCT schooling condition yields Partially differentiating the equilibrium transfer size with respect to the CCT schooling condition yields Combining (35) and (36), the optimal CCT schooling condition that minimizes the poverty headcount ratio,<sup>_P_</sup> 0<sup>, is</sup> For comparison, consider a UCT scheme that transfers a cash benefit of size _m_ to all eligible poor households. Given (37), we can compare the effect on the poverty headcount ratio of CCTs with respect to UCTs, as follows: 29
f f <!-- Start of picture text --> y* (equivalent income)<br>y+t<br>Zz Roee Z ay_<br><!-- End of picture text --> <!-- Start of picture text --> m<br>Y-- X -t Zy (poverty line) — Y (income)<br>@a<br><!-- End of picture text -->
Taking the derivative of the poverty income gap ratio with respect to the CCT schooling condition yields By substituting the equilibrium transfer described in (28) and the partial derivative of the equilibrium transfer with respect to the CCT condition of schooling in (36) into expression (40), the optimal CCT schooling condition that minimizes _P_ 1 becomes From (41), the threshold value of income that determines participation is equal to zero at the optimal education condition, which implies that a CCT program is equivalent to a UCT scheme, and thus their * ˆ corresponding transfer sizes are equivalent (that is, _t_  _m_ ). Moreover, the condition _~~x~~_ 1<sup></sup> _a_ 1 _t_ is not binding because public schooling is assumed to be a normal good and all eligible poor families receiving the transfer attain or exceed such a condition (that is, poor families allocate a fraction 0  _a_ 1<sup></sup> 1 to spending in education). In terms of the poverty income gap ratio, if the policy maker sets a condition of schooling strictly greater than the proportion _a_ 1 of the cash transfer, the reduction of the poverty income gap ratio will always be larger under a UCT scheme ( _P_ ,1 _UCT_ ) relative to a CCT intervention ( _P_ ,1 _CCT_ ). In general, if the government’s objective is to minimize the poverty income gap ratio (that is,   1 ), then UCTs would dominate CCTs.

As illustrated in figure 10. the government’s budget that is not used effectively to achieve the schooling ˆ condition under CCTs is defined by the area of the triangle  _t_<sup>ˆ</sup> / 2  _z y_   _~~x~~_ 1 / _a_ 1   _t_  , and correspondingly, under a UCT scheme, it is characterized by the area  _m_ / 2  _zy_   _~~x~~_ 1<sup>/</sup> _a_ 1   _m_  . Then, because _t_  _m_ , it is better in this particular setting to transfer cash unconditionally.

> In general, the result for   1 holds true for any   1 , that is, UCTs would be preferred over CCTs if a government’s poverty aversion is sufficiently high. Moreover, these basic arguments carry over from income poverty to education poverty (see the appendix). In particular, figures A.1 and A.2 show that UCTs would also be preferable with a sufficiently high degree of education poverty aversion (<sup>_P_</sup> <sup>for</sup>   1 ), that is, if the policy maker’s objective is to minimize measures of education expenditure (and schooling) poverty that are more distributionally sensitive than the headcount ratio, a UCT program should be implemented.

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<!-- Start of picture text --> y‘ (equivalent income)<br>yt<br>y+m<br>Zz 2 we | | pal Y<br><!-- End of picture text -->

<!-- Start of picture text --> m<br>y- z, -t y- z-mM Zy Y (income)<br><!-- End of picture text -->
Furthermore, this paper studies the potential distributional effects (participation rates among the eligible poor population) of CCTs relative to UCTs by means of setting up a government fixed budget problem for different degrees of poverty aversion. Comparing the distributional effect of a CCT program with respect to an unconditional one shows that the latter would be favored over CCTs under a sufficiently high degree of poverty aversion, that is, if beyond the headcount ratio, the governments care about the depth of poverty (the income gap ratio), and, in general, any measure of poverty that is more distributionally sensitive (that is, for any   1 in the FGT index), UCTs will be preferred over conditional transfers. This paper also shows how these basic arguments carry over from income poverty to education poverty.

There is ample margin for further research. The analysis here has been restricted to a proportional expenditure system with homogeneous preferences. It would be useful to extend it to include general functional forms for household utility functions and heterogeneous preferences. Also, in addition to UCTs, CCTs could be compared with other, alternative redistributive interventions such as in-kind transfers or workfare programs. Finally, further research could include general equilibrium analysis, which allows a solution of the optimal income tax system that minimizes income poverty, conditional on the consumption of a minimum level of the conditioned good. A first step to achieve this is to relax the assumption that the income distribution in the economy already captures the difference in labor productivity across households.

The analysis in this paper calls for a more nuanced assessment of CCTs, beyond the mere comparison with UCT programs. Indeed, the conditional-unconditional continuum described by Özler, in this way, can be framed more broadly within the growing discussion on the virtues of universal benefits approaches.<sup>19</sup> In fact, the idea of a universal basic income based on citizenship has been making inroads on policy discussions in both developing and developed countries.

For instance, in June 2016, Switzerland voted on a proposal to guarantee a universal basic income of Sw F 2,500 monthly for every adult citizen and long-term resident.<sup>20</sup> The proposal met with concerns—about budgetary issues, labor market disincentives, and the undue attraction of immigration—and was ultimately defeated in referendum by an overwhelming majority. Nevertheless, other developed economies, including Canada, Finland, and the Netherlands, appear undeterred and are conducting experimental trials. In the Netherlands, for instance, the city of Utrecht is planning a two-year pilot project. The monthly transfer of €960

> 19 See Berk Özler’s July/2013 blog post discussion on the continuum of CCTs/UCTs considering the dimensions of the - announcement, monitoring, and enforcement of programs: <u>http://blogs.worldbank.org/impactevaluations/defining conditional-cash-transfer-programs-unconditional-mess.</u>

> 20 http://www.bbc.com/news/world-europe-36454060.

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for Dutch citizens already receiving government benefits would allow individuals to dedicate more time to education, care, and volunteering, and to have a more flexible work schedule.<sup>21</sup> Universal benefit schemes are also increasingly being considered in developing countries, particularly comparing their effectiveness with that of conditioned and targeted transfers. A series of pilot initiatives on UCTs in India’s Madhya Pradesh, led by the United Nations Children’s Fund, in partnership with the Self Employed Women’s Association, found positive results in such a scheme (SEWA Bharat and UNICEF 2014). The cash payment was given out monthly with no strings attached. The study shows that the transfer led to increased spending on nutrition, health care, education, and productive assets. Moreover, the benefits of the transfer appear to build on one another, for example, increased schooling led to a reduction in child labor, and so on.

In a further step, several scholars have recently discussed the idea of an unconditional, universal income for all citizens in India. In a July 2016 blog post, Debraj Ray discusses the pros (eliminating leaks because of corruption, mistargeting, providing individuals with the liberty to make decisions about how to spend their money) and cons (the magnitude of such a commitment, the question of indexing to the appropriate prices, the effects of such a setup on long-term inequality) of a universal cash transfer that would substitute for the Indian system of multiple transfers.<sup>22</sup> Instead, he proposes a universal basic share of the country’s GDP, which would allow starting small, would do away with indexing, and would provide the incentives for everyone to share in the prosperity of the country, as well as to demand better tax collection. Other scholars, such as Abhijit Banerjee, Pranab Bardhan, Maitreesh Ghatak, Kalle Moene, and T. N. Srinivasan have also joined in on the discussion of universal benefits schemes in India.<sup>23</sup> Questioning the view that careful targeting is always better, Martin Ravallion has also recently discussed the advantages of a basic income guarantee, which might be more cost-effective in reducing poverty than a program such as India’s <mark>National Rural Employment Guarantee</mark> scheme.<sup>24</sup> While evidence is incipient, this discussion is a reminder of the wide array of instruments available to policy makers, certainly including, but not limited to CCTs. Depending on the policy objective, different options, including cash transfers with no strings attached, may be more suitable. Given scarce resources, the quest to find the most effective way to reach the poor, including the poorest among the poor, is far from over.

> 21 See http://borgenproject.org/netherlands-universal-benefits/ and http://www.theatlantic.com/business/archive/2016/06/netherlands-utrecht-universal-basic-incomeexperiment/487883/.

> 22 http://debrajray.blogspot.in/2016/07/the-universal-basic-share.html.

> 23 See Ideas for India’s e-symposium on universal basic income, featuring essays by these economists: http://basicincome.org/news/2016/11/ideas-india-e-symposium-idea-universal-basic-income-indian-context/.

> 24 http://www.cgdev.org/blog/time-big-idea-developing-world.

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