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Conditional cash transfer programs for child human capital development:Lessons derived from experience in Mexico and Brazil1

byAlain de Janvry and Elisabeth SadouletUniversity of California at Berkeley and

World Bank Development Economics Research Group

Abstract

This paper addresses three questions commonly raised about conditional cash transfer (CCT) programs forchild human capital development: (1) When to use the CCT approach? (2) How to increase the efficiencyof the approach? (3) How to learn more from implementation of the approach to improve its use inalternative contexts? We use lessons derived from the Oportunidades experience in Mexico and the BolsaEscola program in Brazil to propose answers to these questions. Answers suggest that the approach ishighly efficient in inducing a change in behavior among parents toward child human capital developmentwhen the objective is not extreme poverty reduction. They also show that considerable efficiency gains canbe achieved through better targeting and calibration of transfers toward children at risk of not going toschool without a CCT, better understanding of heterogeneity of responses to design complementary supply-side interventions in particular according to parents’ educational levels and distance to school, use of theapproach as a safety net to reduce vulnerability of child human capital to shocks, and introduction of moreeffective social accountability mechanisms between providers and stakeholders. There exists, however, ahuge deficit in learning from past experiences and in experimenting with alternative ways of implementingCCT programs while the approach is being extended to new country contexts quite different from the oneswhere experience has been derived.

I. Introduction

Conditional cash transfers (CCTs) are now widely used as an approach in socialassistance programs (Rawlings and Rubio, 2005). Their distinguishing feature is that they imposea behavioral condition on transfer recipients. The condition typically sets minimum requirementson beneficiaries’ attention to the education, health, and nutrition of their children. Forbeneficiaries that would have met the behavioral condition without the transfer, the program isequivalent to a pure cash transfer that reduces poverty immediately, but does not induce a changein child welfare else than through the income effect of the transfer. For those that would not havemet the condition without the transfer, receiving the transfer requires a change in behavior. Inthis case, the condition acts as a price subsidy on the conditional service. If the price effect ismore powerful than the income effect from the transfer in inducing a change in behavior, theconditional cash transfer can then have a double benefit: it not only creates an immediate declinein poverty among recipients if the transfer is larger than the cost of the condition, but it alsoinduces a gain in the educational, health, and nutritional achievements of beneficiaries’ children,thus potentially helping reduce future poverty levels.

Not unsurprisingly, these programs implemented at a large scale in several middle-income countries have had reasonable success in meeting their basic objectives, namely reducingpoverty (with annual budgets of $2.6 billion in Mexico and $700 million in Brazil), increasingeducational achievements (Schultz, 2004), improving child and maternal health (Gertler, 2004),and reducing malnutrition (Hoddinott and Skoufias, 2003). Other verified impacts from the CCTare linkage effects on the local economy (Coady and Harris, 2001), multiplier effects of transfersthrough self-investment (Gertler, Martinez, and Rubio, 2005), spill-over effects on the

1 Paper for presentation at the GRADE 25th anniversary Conference, “Investigación, Politicas y Desarrollo”,Lima, November 15-17, 2005. Corresponding author’s address: alain@are.berkeley.edu.

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educational achievements of the non-poor (Bobonis and Finan, 2005), and a reduction in childlabor (Reference #42). Impact on learning, as imperfectly measured by the progress rate fromgrade to grade, are not significant in spite of the requirement on school attendance (Reference#1). This may be due to the fact that the CCT attracts to school children with low taste or abilityfor school, and that increased school enrollment crowds-out the supply side of education.

CCT programs that started mainly in middle-income countries such as Mexico, Brazil,Turkey, Chile, Colombia, Ecuador, Jamaica, Honduras, Panama, and South Africa are nowspreading to low-income countries such as Nicaragua, Burkina Faso, Lesotho, Cambodia,Pakistan, and Bangladesh. A number of other countries, typically poor ones especially in Africa,are currently looking at these successes and considering adoption of this approach. There are,however, several questions that need to be answered in deciding whether to use the CCTapproach or not and how. The questions debated revolve around three issues: (1) When to usethe CCT approach? (2) How to increase the efficiency of the approach? (3) How to learn morefrom implementations of the approach to improve its use in alternative contexts? In what follows,we discuss these three issues based on current experiences that provide useful, thoughincomplete, lessons. We do this by using principally results from the research we did onProgresa/Oportunidades in Mexico and on Bolsa Escola/Bolsa Familia in Brazil for this paper andin References #1 to #5 in the bibliography.

II. When to use the CCT approach?

2.1. When the program’s objective function includes changing beneficiary behavior

In considering a CCT approach, two contrasted interpretations of objectives areimmediately apparent. In the first, the transfers have the principal objective of reducing currentpoverty. The position is that “even a small amount of cash in the hands of a poor mother can dowonders” (IFAD project officer). In this case, the transfer should be unconditional. In spite ofthis, imposing a condition on behavior may be necessary to secure the political acceptability of atransfer program. This is because taxpayers and donors may agree to fund a transfer program, butonly if the recipients display socially acceptable behavior: they are required to work in workfareprograms such as Trabajar in Argentina or to send their children to school and health visits inprograms such as Oportunidades and Bolsa Escola. Imposing such conditions on behavior maywell be welfare reducing for both recipients and society (compared to an unconditional cashtransfer), but it is second-best welfare enhancing compared to no program or to a program with asmaller budget due to low political acceptability. Implementation requires targeting on poverty,irrespective of whether the selected beneficiaries would have met the condition without a transfer.This position in favor of unconditional CT tends to be preferred in contexts where poverty isextreme and where the objective of the transfer is securing immediate survival. If a condition isimposed on the behavior of recipients for program legitimation purposes, it should minimize thewelfare loss on recipients compared to an unconditional cash transfer.

In a second interpretation, the CCT approach is seen as an instrument to increase thehuman capital of the children of the poor. To meet this objective, the transfers would need to betargeted and calibrated for maximum impact of the program on human capital development. Forthe educational objective, this requires identifying children who are most at risk of not going toschool without a transfer, and who have the largest response per unit of transfer. We return

2 Papers on Oportunidades and Bolsa Escola authored by us and collaborators are referred to as References#1 to #5.

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below to the optimal design of a CCT program when maximizing the effect of the conditionalityon changing the behavior of recipients is the objective.

Countries that consider introducing a CCT, where the condition is on child human capitaldevelopment, need to have clear what objective is being pursued. The optimum targeting andcalibration of transfers offered to poor households will differ according to the objective beingpursued. Eliminating a potential confusion in objectives is thus a pre-condition for implementingan efficient CCT program.

2.2. When constraining behavior is justified to create a private or social efficiency gain

A CCT transforms the positive income effect of a cash transfer (CT) into a negative userfee on the service that is imposed as a condition. Conditionalities can thus be used when theincome effect of a transfer is insufficient to induce the action required by the condition. Clearly,if the action is met without the transfer, or as a consequence of the transfer alone, imposing acondition is useless and administratively costly for no benefit on behavior.

It is well known from basic principles of welfare economics that, in a first best world,cash transfers without any conditions attached will maximize the welfare gains achieved byrecipients. Imposing a condition thus needs to be carefully rationalized. There are three sourcesof failures in household decision-making that justify imposing a conditionality on transfers. 3

i) Protecting people against themselves: Child win - Household winThere are situations where public intervention is meant to help protect people against

their own choices. This is the case when uneducated parents may not be informed about the valueof education, especially outside the community, or when the future value of education isunderestimated by households based on the current assessment of the value of education. Thismay also be the case when there is bounded rationality such as procrastination in decision-making. Finally, programs for child human capital development may assemble complementaryinterventions in education, health, and nutrition in a complex fashion that is beyond theunderstanding and implementation capacity of poor parents. Under these conditions, imposingconditionalities on transfers may well be doubly welfare enhancing: it will increase the welfareof the child (who receives the right amount of schooling and other elements of human capitaldevelopment) and of parents (who will benefit from the right level of child human capitaldevelopment). The CCT approach is in this case an instrument to secure the first best.

Lack of information about returns to education in marginal rural communities is starklyillustrated in Figure 1.

3 We do not consider here the use of conditionalities to induce self-selection in targeting, for example inworkfare programs. This is discussed in Das, Do, and Özler (2005).

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0

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Primary Secondary 1 Secondary 2 Secondary 3 Higher thansecondary 3

Migration

Ag. wage

Non-ag. wage

Self-employed

Life time earnings (pesos/month))

Figure 1. Returns to education in four activities for children in marginal rural communities.Progresa data. (Source: Reference #1)

The present value of lifetime earnings4 in activities within the marginal community(agricultural wage employment, self-employment in agriculture or micro-enterprises, and non-agricultural wage employment) do not increase with educational levels. In these communities,returns to education are very low, deterring private investment in education. By contrast, returnsto education are high outside the community. If parents are only informed about local returns,they will under-invest in education. Informing parents about the gains from migration is thusnecessary to induce investment in education. Alternatively, a CCT is a way of inducing parents’behavior toward child education that corresponds to the true returns from migration, includingthrough migration outside the marginal rural community.

ii) Discrepancy between child and parent optima: Child win - Household lossThis is the case when a decision by a parent may hurt the interest of a child who has no

option in responding. Parents may under-invest in education because they have a higher discountrate than their children, at a private cost to them (Baland and Robinson, 2000). This also happenswhen intra-household bargaining with unequal power between genders may lead to resourceallocation that is sub-optimum for children in terms of investment in their human capital. This isthe case if the mother, who represents the child’s interest, does not have bargaining power in thehousehold to defend the child’s welfare. Cash transfers to such households should be conditionalto induce them to adapt their behavior to the interests of their children. The CCT approach is inthis case to maximize child welfare, at the cost of a loss for the members of the household whosechoices are altered by the conditionality relative to an unconditional CT. No absolute loss isincurred since participation is voluntary.

iii) Discrepancy between private and individual optima: Social win - Household lossIt is well known that there are large positive externalities from private investments in

education and health, resulting in under-investment relative to social optimum (see in particularCurrie and Moretti, 2003, and Milligan, Moretti, and Oreopoulos, 2004). In this case, a price

4 The present value of lifetime earnings is calculated as the discounted sum of income received by people ofsame education and same gender of different ages in the year of the survey. It captures the perceivedpresent value of lifetime earnings as if currently observed incomes applied to the future.

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subsidy is needed to increase private investment to the social optimum, If households have apositive utility for education, a price subsidy that reduces the cost of education would besufficient. If households have a negative utility for education, the price subsidy needs to be largerthat the cost, resulting in a positive net CCT.

Another situation of positive externality is when there is a collective action problem inseeking information, such as in learning-by-doing and demonstrating to others the value oflessons learned (Foster and Rosenzweig, 1995). In this case, the positive externality achieved bydemonstration induces individual under-investment in seeking to generate information, about thevalue of education for their children in particular.

Finally, the creation of future poor with high social costs (measured as an opportunitycost for society or as a direct welfare cost) due to parents’ failure to educate justifies a CCT toreconcile private behavior and social optimum. In this case, the social cost of future poverty ishigher than the private cost. The social objective in using a CCT approach is then educationtoday at a minimum public cost, versus a high future social cost.

The CCT approach is in these cases to maximize social welfare, at the cost of a loss forthe household relative to a CT. Because program participation is always voluntary, no absoluteloss needs to be incurred by the household.

Imposing a constraint on behavior in using scarce cash in the hands of a poor mother thusrequires careful consideration. The conditionality needs to be justifiable on the basis of one ofthese three arguments: imperfect information by parents, discrepancy between parent and childoptima, and market failures due to the positive spillovers created by investments in child humancapital. When these effects are expected to be large, a CCT approach is justified.

2.3. When the cost of altering behavior is much lower through a price than an income effect

We have four sources of evidence to measure the relative magnitudes of the impact of aCT versus a CCT on educational response.

The first is from the vast literature on empirical analyses of demand for education. Eventhough results vary by context, they indicate that income elasticities of education are notably lowamong the poor and frequently insignificant. In their review of 42 studies covering 21 countries,Behrman and Knowles (1999) find that this relation is insignificant in 40% of the cases. Purecash transfers such as initiation of the South Africa pension system have been observed toincrease child schooling, but this effect is small (Edmonds, 2005). This is what has motivated theuse of conditional transfers.

The second argument on the relative impact of CCT versus CT in increasing schoolenrollment derives from theory. The sketch of a standard school choice model is as follows.Consider a household at time t with a single child and with period utility u which is an increasingfunction of consumption Ct and of the binary enrollment status St of the child, and a decreasingfunction of his binary work status Wt. With a rate of time preference ρ , the household’s optimalchoice of schooling, child work, and consumption is the solution to the maximization of thediscounted value Ut of expected utility at t over an infinite time horizon,

Ut =

11+ρ( )s

Etu Ct+s ,St+s ,Wt+s( )s=0

∞∑ ,

under the contemporary budget constraint:

Ct + pSt =Yt +wWt ,

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where p is the child’s specific cost or opportunity cost of schooling, w the wage he would secureon the labor market, and Yt the household’s autonomous income. In this model, we assume notime constraint, allowing the possibility for the child to both enroll in school and work, if hechooses to. This is based on the observation that the school day is short (usually half-day) andthat some children combine school and work. The opportunity cost of going to school is thus notnecessarily equal to the wage.

Add to this budget constraint a non-conditional cash transfer T nc and a conditional cashtransfer T c . The non-conditional cash transfer simply raises the household income, while aconditional cash transfer only applies if the child is enrolled. The budget constraint becomes:

Ct + pSt =Yt +wWt +T nc +T cSt .Given w and p, the joint choice of schooling and work is as follows:

St =1 p≤ p∗ Yt +T nc ,T c ,w( )⎡

⎣⎢⎤⎦⎥

Wt =1 w>w∗ Yt +T nc ,T c , p( )⎡

⎣⎢⎤⎦⎥

meaning that the child enrolls in school if his opportunity cost of school is lower than a thresholdvalue p

∗ , and works if the wage offer is higher than the threshold value w∗ . The relative effectsof the conditional and non-conditional cash transfers derive from their influence on thethresholds. Solving the model shows that:

dp∗

dT nc =uc Yt +T nc− p∗,1,Wt( )−uc Yt +T nc , 0,Wt( )

uc Yt +T nc− p∗,1,Wt( )<1

and

dp∗

dT c =uc Yt +T nc− p∗,1,Wt( )uc Yt +T nc− p∗,1,Wt( )

=1

where uc represents the marginal utility of income.The numerator in the first expression exhibits the difference in marginal utility of income

when the child is enrolled and not enrolled. As school has a cost or opportunity cost, thehousehold is poorer when the child is enrolled, and hence its marginal utility of income is higher

than when the child is not in school. This difference is therefore positive, and hence

dp∗

dT nc is

positive, meaning that the non-conditional cash transfer increases schooling by raising thethreshold value p

∗ under which the child enrolls. Note, however, that the difference is likelysmall, and hence the effect of the non-conditional cash transfer small. By contrast, in theexpression for the conditional cash transfer, the numerator is simply the marginal utility of

income, and the ratio

dp∗

dT c is equal to 1. The conditional cash transfer is equivalent to a one to

one decrease in the price of school. The effect of the conditional cash transfer is thus a strongprice effect, while that of the non-conditional cash transfer is a diluted income effect.

The order of magnitude of the impact of a CCT compared to a CT can be approximatedas follows. The difference in marginal utility of income is approximately equal to the differencein interest rates at which you will be willing to borrow for consumption. If the cost of schoolingimpoverishes the household to a point that its marginal utility of income increases from 1.20 to1.30 (i.e., it is willing to borrow at 30% rather than 20% just for the effect of the school price),

then

dp∗

dT nc =1−1.201.30

=.101.30

= .08 . An $8 conditional cash transfer has the same schooling

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effect as a $100 non-conditional cash transfer. The CCT effect would thus be some 13 timeslarger than the CT effect.

The third is from ex-ante simulations deriving from observed changes in schoolenrollment choices made by children who work in response to wage changes. This allowsBourguignon, Ferreira, and Leite (2003) to predict that an unconditional cash transfer would haveno effect on school attendance among the poor compared to a 5.6% increase through a priceeffect. The effect is large among poor households, as 58% of the 10-15 years old not in schoolwould enroll in response to the CCT. For Africa, Kakwani, Veras, and Son (2005) show that cashtransfers would buy very little in increased school attendance, recommending against their usebased on cost considerations. They consequently suggest using CCT instead, but do not provideresults of expected impacts due to insufficient information on income from child labor.

Finally, we can use the ex-post Progresa effect to measure the impact of an unconditionalversus a conditional cash transfer effect on schooling decisions (Reference #3). Here, theschooling decision is entry into secondary school for children who are graduating from primaryschool in poor rural communities. The CCT is exogenous through the randomized experiment.The CT (household total expenditure) is not a controlled experiment. While this estimate thussuffers from some endogeneity, stability of the estimated coefficients to introduction of a verylarge number of child, household, community, and state variables gives confidence that anyendogeneity bias would be very small. Results in Table 1 show that, using the regression will allcontrols, a dollar of CCT is about 16 times more effective on education than a dollar of CT.

Linear probability model of enrollment in secondary school Mean (1) (2) (3)

CCT: Treatment community (dummy, 1=US$200/year) 0.718 0.130** 0.127** 0.130**(0.019) (0.020) (0.020)

CT: Household total expenditure (US$100/year) 8.055 0.003* 0.004*(0.002) (0.002)

Control variables Child, household, and community characteristics (31 variables) Yes State of residence (6 variables) Yes

CCT/CT effect on enrollment 21.2 16.3

* significant at 5%; ** significant at 1%

Table 1. Relative effectiveness of a CCT vs. a CT in inducing a change in behavior toward childschooling. Progresa data.

We can thus conclude that, once the decision has been made that imposing a condition onbehavior is acceptable, it is quite evident that a CCT is considerably more effective than anunconditional CT transfer in altering behavior toward schooling. Poor countries, like in Sub-Saharan Africa, that could not afford to increase educational achievements via CTs (Kakwani,Veras, and Son, 2005) may well be able to do this via CCTs if they are able to implement theapproach.

2.4. When reducing current extreme poverty is not the objective

An argument that is frequently made by those who advocate using a CCT withconditionality on child human capital development as an instrument for poverty reduction is that

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it is effective in targeting poverty: poor people tend to have more children, and families withmore dependents tend to be poorer. As a consequence, having children of school age may be agood correlate of the depth of poverty. We can verify if this is true by analyzing the impact of thetransfers on poverty levels in the Progresa evaluation sample. This is done in Figures 2.1 and 2.2.In these figures, poverty is measured by per capita consumption expenditures in adult equivalent(in pesos/month). One can see in Figure 2.1 (where each point represents 4% of the householdsin the sample) that there is a higher percentage of poor than non-poor among beneficiaries, eventhough there are substantial leakages to the non-poor: of the households covered by the program,68% are poor and 32% non-poor. There is also a higher incidence of beneficiaries among poorerhouseholds (reaching a high of 80% among some of the poorest categories) than among less poor(reaching 47% by the poverty line) (line (1) in Figure 2.1). The total transfer is consequentlyreaching the poor more than the non-poor, and the poorer more than the less poor. On a perhousehold basis (line (2)), the transfer is slightly larger for poor beneficiaries ($300) than at thepoverty line ($250), reflecting the fact that they have more children. However, on a capita basis(line (3)), however, transfers are constant or regressive ($40 among the poorest increasing to $50by the poverty line). This is not surprising since the transfers are formula-based according to thenumber of children (with a cap), their grades, and gender.

The absolute income effect of the transfers is seen in Figure 2.2 that reports the averagetransfer for the whole population by income level (total expenditure per adult equivalent): thetransfer per adult equivalent does not benefit the very poor more than the less poor in the villagepopulation. As it is, targeting on the poor who qualify for the CCT is equivalent to a uniformdistribution of the transfers among the poor, as opposed to providing larger transfers to thepoorest of the poor.

0

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Total expenditure per adult equivalent (pesos/month)

Transfer (pesos/month)

POOR NON-POOR

(3) Transfer per capita(among beneficiaries)

(1) Percent beneficiaries

Percent beneficiaries

(Each point represents 4% of the households)

(2) Total transfer (among beneficiaries)

Figure 2.1. CCT by income level for Progresa beneficiaries

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(4) Expenditures + transfer (for all)

POOR

NON-POOR

Total expenditure + transfer (pesos/month)

Total expenditure per adult equivalent (pesos/month)

Figures 2.2. Impact on total expenditure of CCT to Progresa beneficiaries.(Source: Reference #2)

The conclusion is thus that using a CCT approach for current poverty reduction iseffective in reaching differentially more the poorer households, but that it does not result in largertransfers for the poorest relative to the less poor.

2.5. When the supply-side of the service is sufficiently in place

A demand-side program to enhance educational levels among the poor via CCTs willonly work if the supply-side of education is sufficiently in place. In the case of Oportunidades,communities without the minimum educational and health facilities were not included in theprogram. However, the difficult question of balance between demand-side and supply-sideinvestments has not been properly resolved. In the case of Oportunidades and Bolsa Escola, therehas been a notable deficit of experimentation on complementarities between supply-side anddemand-side investments. This issue cannot be fully resolved without proper experimentation.However, an approximate answer can be obtained by analyzing heterogeneity in responses toCCTs according to contexts with different qualities of supply.

In Figure 3, we use data from Progresa to analyze the decision to enter in secondaryschool according to distance to a school, a supply-side determinant, and the differential responseto a CCT according to distance. Households are ranked by distance to a secondary school. Thenon-parametric estimation is performed on 1,500 children, using a sliding window from lowest tohighest, dropping 100 kids each time at the lower end and adding 100 kids at the higher end. Inthe figure, we represent by a dotted line the proportion of children that quits school at entry intosecondary in control villages without Progresa (right axis). The dashed line is the impact of theCCT on enrollment in secondary (left axis). The plain line is the net effect of the impact ofdistance and the CCT on the proportion that quits.

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By distance to secondary school

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Distance to secondary school

Impact (left axis)

Proportion that quitswithout Progresa

(right axis)

Proportion that quits with Progresa

% of children Impact of Progresa % of childrenDistance to who quit on enrollment who quitsecondary school (km) without Progresa (% points) with Progresa0 to 1 23.5 5.9 17.61 to 3.5 37.4 13.9 23.5more than 3.5 46.7 8.7 38.1

Figure 3 (and data in figure). Heterogeneity of impact of a CCT on secondary school enrollment.Progresa data.

The data show that dropping out of school increases with distance to school in the controlvillages from 20% when there is a school in the village to 48% for children located at 4km of thenearest secondary school. Impact of the program is greatest for children located at some 3kilometers away from a school, declining afterwards. For children located at 3 km, the gain inenrollment due to the CCT is 15% out of 40% that would have quit. The remaining 25% drop outrate is about the same as that of children who live close to a school without the program. Thisindicates that the CCT basically compensated for the higher transportation costs for childrenliving 3 km away from a school. For them, a supply-side transportation subsidy wouldconsequently achieve the same gains as the demand-side price incentive. For children livingfurther away from a school, the demand-side intervention has very little impact. For thesechildren, a supply-side intervention would be necessary, either through a school transportationprogram or through construction of additional schools.

III. How to increase the efficiency of the CCT approach?

3.1. By targeting and calibrating transfers for maximum effect of the program on behavior

For Mexico, the educational problem in poor rural communities is starkly represented byFigure 4 that shows the continuation rate by grade across primary school and junior high school.The dotted line is for control communities, and the full line for treated communities.

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40

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100

P2 P3 P4 P5 P6 S1 S2 S3 S4

Continuation rate (%)

Primary school

Lower secondary school

Secondary 164%

Entering grade

PROGRESA INTERVENTION

Upper secondary

school43%

Progresa villages

Control villages

76%

Figure 4. Continuation rates in primary and junior high, Mexican rural communities(Source: Reference #3)

We see that CCTs for primary school essentially do not buy any change in behavior asmost children attend primary school without transfers. In fact, we calculate that the cost of usingCCT to induce more attendance in primary school is as high as $9,700/year/child as 97 childrenwho already go to school have to be paid for every one additional child induced to go to schoolby the CCT (Reference #2). The main problem is with entry into secondary school. We see that:

• 64% of the children who graduate from primary school would enter secondary schoolwithout a transfer (ineffective transfers or leakages).

• 12% enter as a consequence of the CCT (effective transfers).• 24% do not accept the offer, suggesting that it was insufficient or irrelevant to induce

enrollment (ineffective offer).

Using the experimental data from the Oportunidades program, we can predict the impactthat a given CCT has on the likelihood that a child will continue into secondary school byestimating a linear probability model of enrollment (Table 2). This is made possible by using (1)the data from a randomized treatment of 506 communities and (2) existence of a cap on the totaltransfer to a family, which implies that 26% of the children receive an effective transfer inferiorto the full amount, serving as a natural experiment on the level of the transfer. Results show thatthe CCT increased secondary school enrollment by 13% (treatment community effect). Largesteffects are found to be on children who combine the attributes of male, 14 years old, indigenous,and with no school in the community for whom the increase in enrollment is 23%.

HeterogenousMean impact

Treatment community (dummy) 0.72 0.130** -0.172 -0.159(0.019) (0.156) (0.156)

Conditional transfer*Treatment (US$100/year) 1.22 0.156* 0.095(0.080) (0.083)

Conditional transfer*Treatment * (Age –12) 1.24 0.016**(0.007)

Conditional transfer*Treatment * Father indigenous 0.42 0.028(0.019)

Conditional transfer*Treatment*No sec. school in village 0.95 0.037*(0.021)

Child, household, and community characteristics No Yes Yes* significant at 10%, ** significant at 5%.

Homogeneous impact

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Table 2. Linear probability model of enrollment in secondary school. Progresa data.(Source: Reference #3)

We use this equation to determine the targeting and calibration of CCT that maximizegains in educational achievement among the poor, under the overall constraint of the Progresabudget. The optimum transfer can then be either completely idiosyncratic, or function of areduced number of indicators that are easy to measure and verify by others, and that cannot bemanipulated by potential beneficiaries. The first solution gives an “optimal variable CCTscheme” while the simplified score system gives us an “implementable CCT scheme” (see Table2). In the implementable scheme, indicators used to determine the level of CCT offered to a childconsist in gender and birth order in the family, existence of a secondary school in the village anddistance to the school, and State of residency. Results from the current program compared to theoptimal and implementable schemes are shown in Table 3.

Universal uniform Optimal variable ImplementableNo program CCT scheme CCT scheme CCT scheme

63.2 75.7 81.1 79.4Efficiency gain over universal uniform CCT scheme (%) – 44 29

Eligibility among poor (%) 100 78 77Average transfer value (US$/year) 194 237 236Leakage to children that would go to school w/o a CCT (% of total budget) 83 65 75Cost per additional child enrolled (US$/year) 1151 802 889

Enrollment rate in secondary school, all children (%)

Table 3. Enrollment rates under alternative CCT schemes. Progresa data. (Source: Reference #3)

Results show that secondary school enrollment among children graduating from primaryschool rises from 63.2% in the control villages to 75.7% with Progresa’s universal (i.e., 100%eligibility among poor) uniform scheme, the much heralded 12.5 percentage points gain estimatedby others. This gain can be increased by another 5.4 percentage point under the optimal variablescheme, a 44 % efficiency gain over the uniform scheme. The implementable scheme reduces thisgain over Progresa to 3.7 percentage points, a 29% efficiency gain.

The targeted and calibrated schemes imply less than universal eligibility among the poor(78 and 77% for the two schemes analyzed, respectively) due to the need to make larger transfersto induce more up-take ($237/year and $236 as opposed to Progresa’s $194). The relativeefficiency of the schemes can be measured by calculating the percentage of total transfers that isineffective in inducing a change in behavior as children would have gone to school without thetransfer (i.e., leakage costs) and the complementary percentage that induces a change in behavior(effective transfers or direct costs). This is displayed in Figure 5. Targeting and calibrating foreffectiveness of the conditionality reduces leakages from 83% of the total budget to 65% underthe optimal scheme and 75% under the implementable scheme. Figure 5 shows how paymentsare shifted toward children with lower enrollment probability without a CCT, and how thesechildren receive larger transfers within the program’s overall budget constraint. An importantobservation, however, is that leakages remain high, even under the optimal scheme. This reflectsthe large informational rent due to adverse selection under imperfect information that is capturedby households who would send their children to school without a transfer. This informationalrent is the cost to be paid for imprecision in the program’s ability to predict school attendancewithout and with a CCT.

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300

350

400

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95

Direct costs

Efficiency leakage costs

In US$ 1000 per year

Enrollment probability without CCT program

Overall share = 83.2%

0

50

100

150

200

250

300

350

0.05 0.15 0.25 0.35 0.45 0.55 0.65 0.75 0.85 0.95

Direct costs

Efficiency leakage costs

In US$ 1000 per year

Enrollment probability without CCT program

Overall share = 64.9%

Figure 5a. Actual scheme with uniform CCT Figure 5b. Optimal scheme variable CCTFigure 5. Direct costs and leakages under the actual and optimal schemes (Source: Reference #3)

We thus conclude this analysis by observing that:(1) Important efficiency gains in raising school enrollment (a 29% to 44% gain over the currentscheme) can be achieved by targeting and calibrating CCT among the poor for maximum impactof the conditionality. Targeting is on children at risk of not going to school and with highresponse to transfers. The most important selection criteria are: absence of a secondary school inthe village, distance to school, state of residency, gender and rank of the child, and parentswithout education. By simulation, we can show that these efficiency gains are all the larger thatthe program’s budget constraint is more severe, requiring to be more selective among the poor.This makes this exercise all the more relevant in extending the CCT approach to low-incomecountries.(2) Selection criteria for an implementable scheme can be simple, public, with self-registration,and community verification. As opposed to a secret formula used for targeting in Oportunidades,Bolsa Escola, and other CCT programs (e.g., Chile Solidario), this allows households to haverecourse in claiming their rights if they feel that they have been unjustly mis-targeted. Recourseis in turn a fundamental attribute to secure greater accountability in service delivery.

3.2. By designing complementary interventions revealed by heterogeneity of impacts

The efficiency of CCT programs can be raised by designing complementary interventionstargeted at specific categories of children identified by analyzing the heterogeneity of responsesto a CCT offer. We can focus on heterogeneity in the magnitude of impacts across the treatedpopulation. We can also focus more specifically on the population of children that do not go toschool in spite of the offer of a CCT. we do both in what follows.

We explore first the role of heterogeneity in parents’ educational levels to determine theincidence of benefits across households to whom a CCT offer is made. To do this, we return to anon-parametric analysis of children who have graduated from primary school and are consideringentry into secondary school. Households are ranked the total number of years of education ofboth parents.

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By parents' total education

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0 2 4 6 8 10 12 140

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

Impact (left axis)

Proportion that quitswithout Progresa

(right axis)

Proportion that quitswith Progresa (right axis)

% of children Impact of Progresa % of childrenParents' total who quit on enrollment who quiteducation (years) without Progresa (% points) with Progresa1 to 4 41.8 2.7 39.14 to 6 35.9 9.1 26.86 to 9 31.3 13.8 17.4more than 9 24.6 16.9 7.7

Figure 6 (and data in Figure). Impact of a CCT on secondary school enrollment by parents’educational level

Results show that dropping out of school declines with parents’ educational level(proportion that quits without Progresa). The impact of the program is, however, also greatest forchildren with the most educated parents. Education thus begets education. The CCT largelysolves the educational problem for the children of poor parents with 9 years and more ofcombined education. However, it does not solve the educational problem of children with low-education parents, especially parents with less than four years of education: for these children, thegain from a CCT is basically zero.

We explore next the vexing issue of the remaining 24% children who qualify for a CCTand yet do not take the offer and do not go to school. Analyzing the heterogeneity of theirconditions can help target specific programs to them to raise program uptake. In Table 4, wecalculate the weighted average of the characteristics of the population of children that qualify forProgresa, with weights equal to the predicted probability that each child (1) will enroll withProgresa but not without, and (2) will not enroll even with the Progresa offer. The first categoryis what yields the 12% gain in enrollment due to the impact of Progresa on behavior in Figure 4,while the second category is the remaining 24% children who drop out of school in spite of theProgresa offer.

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Goes to school Does not go to schoolwith Progresa: even with Progresa:

Child, household, and community characteristics Average values Average values % difference Test of difference(1) (2) (2)/(1) p-value

Age 13.22 13.73 3.8 ***Father is literate (%) 61.0 53.1 -13.0 ***Father's education (years) 2.03 1.58 -22.2 ***Father is indigenous (%) 29.6 23.2 -21.6 ***Mother is literate (%) 58.4 52.0 -10.9 **Mother's education (years) 2.07 1.70 -17.9 ***Mother is indigenous (%) 31.7 25.4 -19.6 ***Number of children 11-19 years old 2.79 3.03 8.3 ***Number of agricultural workers in the household 1.33 1.47 10.8 **Number of unpaid family members in the household 0.39 0.49 26.8 *Household's maximum education (years) 4.67 4.24 -9.2 ***Potential transfer (US$100) 1.96 1.92 -2.3 ***Persons per room in dwelling 5.30 5.53 4.3 *Dwelling has water (%) 32.9 29.4 -10.9 *Queretaro (% of households in sample) 6.3 9.5 52.6 **Veracruz (% of households in sample) 21.6 18.2 -15.7 *No secondary school in the village (%) 83.9 90.3 7.6 ***Distance when there is no school (km) 3.25 3.52 8.1 **

*** significant at 1% level, ** 5% level, * 10% level.Table 4. Contrasted characteristics of children who go to school due to the CCT and children who do

not go to school in spite of the CCT offer

Results show that the remaining large uptake failure, given the current operational rulesof Progresa, is associated with several well recognizable child, household, and communitycharacteristics, most notable:

• Low parents’ and household’s education: Children with illiterate and low educationfathers and mothers, and with low maximum education in the household.

• Parents occupation that does not give value to education: Children of agriculturalworkers.

• Poverty: Children living in dwellings with no running water and overcrowding.• Access to school: Children who live in communities with no secondary school and at a

greater distance from a school.

Analysis of heterogeneity is important in helping define complementary interventions toincrease the efficiency of a CCT program where gains can be selectively achieved. Results ondifferential impact show the fundamental role of parents’ own education in the educationaloutcome of their children, even when a CCT program is available. Hence, there is strong pathdependency in education which is not eliminated by CCT. This suggests the need for specialassistance to children with uneducated parents, beyond mere access to a CCT. Results also showthat there are well identifiable household and community characteristics that suggestcomplementary supply-side interventions for differential assistance or greater access to schools.

3.3. By using the approach as a safety net for the human capital of children in vulnerablehouseholds

We start by observing that poor households in marginal communities are exposed tomany shocks, both individual (health, unemployment) and covariate (natural events). Responsesto shocks to shelter consumption include the sale of liquid assets, use of credit and insurance, andtaking children out of school to save on cost or send them to work. The problem with usingchildren as risk-coping instruments is that, once out of school, they are much less likely to return(Jacoby and Skoufias, 1997). Short-run responses to shocks thus have high long-term

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consequences on their educational achievements, creating a source of new poor. Important is thusto offer risk-coping instruments to parents that will protect child education from shocks.

We use the panel surveys in the Progresa randomized experiment, in which four roundshave information on exposure to shocks. The econometric specification for the school decisionis:

Sit = γ Sit−1 +αsit + βsitTi +θt + µi + εit

where Sit is enrollment in school (0/1) by child i in semester t , Sit-1 enrollment the previoussemester,

sit is a shock,

Ti the treatment (offer of a CCT), θt a period fixed effect, and µi a

child fixed effect. This fixed effect controls for the child’s idiosyncratic propensity to go toschool.

Children of Children ofDependent variable: Child at school Primary Secondary Non- agricultural non-ag.

school school Boys Girls Indigenous indigenous worker worker

State dependence Child at school last semester 0.057** 0.228** 0.099** 0.121** 0.088** 0.123** 0.086** 0.114**

Head of household unemployed -0.028** 0.001 -0.034** 0.002 -0.038** -0.006 -0.029* -0.010 * Progresa 0.023+ -0.009 0.020 0.002 0.029+ 0.002 0.042** 0.005

Head of household ill 0.010 -0.037* -0.007 -0.008 0.007 -0.015 -0.018 0.004 * Progresa -0.006 0.047* 0.021 0.001 -0.008 0.020+ 0.020 0.004

Natural disaster severity in locality -0.028** -0.013 -0.020 -0.050** -0.049** -0.013 -0.037** -0.024+ * Progresa 0.036** 0.021 0.024+ 0.057** 0.047** 0.024 0.041** 0.029+

+ significant at 10%; * significant at 5%; ** significant at 1%.All regressions include round and child fixed-effects. Linear probability model estimated with the Arellano-Bond estimator.

Table 5. Path dependency and vulnerability to shocks. Progresa data.(Source: Reference #4)

Results in Tables 5 show that:(1) Irreversibility is important: Short term absences from school have long term consequences: achild who misses one semester of school have 6% less chance of attending school the followingsemester in primary school and 23% in secondary school.(2) Idiosyncratic shocks due to unemployment and illness of the household head and covariateshocks due to natural disasters in the community induce children to leave school. The categoriesof children for whom assistance to school is most exposed to shocks are primary school students,indigenous children, and sons/daughters of farm workers.(3) Progresa fully protected child schooling from exposure to shocks.(4) Progresa did not protect children from working more when their household is hit by a shock.Since there is no conditionality on behavior toward work, this indicates that the net income effectof the shocks and the transfer is such that parents choose to increase the work contribution oftheir children as a risk-coping instrument. This implies that, for these children, school and workare compatible, and that parents derive a double benefit from children as risk-coping instruments:as a source of income by continuing to attend school, and thus receiving a CCT, and as a sourceof work when there is a shock.

While CCT programs targeted at the chronically poor are thus shown to be effective toprotect child schooling when parents are hit by a shock, the education of the children of manynon-poor households is also vulnerable to shocks. As such, they may be the source of future newpoor when they are taken out of school in response to a short-run shock. This source of new poorcan then partially erase the educational gains achieved in the population among chronic poor

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covered by the program. Recent studies on the origins of poverty have indeed emphasized therole of vulnerability as a source of poverty (UNDP, 2004). The Oportunidades results suggest apossible extension of coverage to non-poor vulnerable children when hit by a shock to avoiddetrimental long term consequences on their educational achievements. A program of CCTs usedas a safety net for child human capital would then require the following operational procedures:

1) Identify vulnerable children: predict which non-poor children are vulnerable to droppingout of school as a consequence of shocks. These are children whose parents do not haveaccess to sufficiently effective other risk-coping instruments (accumulated liquid assets,access to credit, possibility of calling on mutual insurance, coverage by safety net programs)that they risk taking their children out of school when hit by a shock.2) Use a community supervision committee to verify qualification of a child for incorporationin the CCT program when the household is hit by a shock.3) Design a pilot experiment to learn how to use 1) and 2) above to manage CCT as a safetynet for child education.

In the African context, an important source of shock is HIV/AIDS. CCT coverage could be usedto provide a safety net for child education among households affected by the disease.

3.4. By increasing transparency and accountability in implementation

While the Oportunidades program is implemented through centralized provision at thefederal level, implementation of the Bolsa Escola program is done through decentralization of theselection of beneficiaries and the enforcement of conditionalities to municipal governments. Asargued in the World Development Report 2004 (World Bank, 2004), effective decentralizedprovision of social services requires accountability of local providers (in this case electedmunicipal mayors) to stakeholders (in this case potential beneficiaries of the Bolsa Escolaprogram). There are two routes for this downward accountability: the “short route to socialaccountability” is via direct relations between clients and providers. In the case of Bolsa Escola,this is to be achieved by appointment of a municipal Bolsa Escola Social Council to whichstakeholders can appeal in claiming their rights. The “long route to social accountability” is viathe local electoral process, whereby stakeholders can reward or punish incumbent mayorialcandidates or incumbent parties in municipal elections. This is represented in Figure 7.

Federal government:Federal Bolsa Escola Program

Decentralized service provider:

Program implementation:Long route to social accountability Targeting: Beneficiary identification and selection

Monitoring and enforcement of conditionalities Accountability mechanisms

Bolsa Escola beneficiaries:Demands for downward Potential beneficiaries

accountability Actual beneficiaries

Program outcomes: Poverty reduction and human capital formation

Rules and budgets

Transparency (information)Short route to social accountability

Appeals to social council

Local political retributions

Municipal government

Municipal Bolsa Escola social council

Figure 7. Social accountability mechanisms in a decentralized CCT program: Bolsa Escola

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(Source: Reference #5)

Dependent variable: Mayor was reelected in 2004 (1) (2) (3)Bolsa Escola council exists 0.264 0.262 0.206

[0.133]+ [0.128]* [0.147]Public denouncement for Type II (inclusion) error -0.263 -0.25

[0.111]* [0.121]*Public denouncement for politics -0.003 -0.053

[0.131] [0.142]Public denouncement for Type I (exclusion) error 0.011 0.031

[0.119] [0.122]Registered beneficiaries in mayor's office 0.034

[0.131]Registered beneficiaris using home visits 0

[0.003]Registered beneficiaries with geographic priorization 0.132

[0.120]Misunderstood selection process 0

[0.115]Quota 0.016 0.013 0.011

[0.006]** [0.006]* [0.006]+

Mayor characteristics Y Y YMunicipal Characteristics Y Y YPolitical Characteristics Y Y YObservations 108 108 105R-squared 0.38 0.43 0.45

Table 6. Long route to downward accountability. Bolsa Escola data. (Source: Reference #5)

Results from a survey of 261 municipalities in four states of Brazil’s Northeast gave thefollowing results:

• Short route to social accountability: Social Councils, the instrument designed toinsure a short route to downward accountability, performed incompletely and in anuneven fashion across municipalities. We find that (a) many municipalities did not formthese councils despite federal requirements to do so; (b) even when social councilsexisted, they did not necessarily function properly as many did not meet regularly or werenot informed on who were the program beneficiaries; however, (c) in municipalitieswhere social councils existed, there was a positive impact on the quality ofimplementation of the program.

• Long route to social accountability: Results in Table 6 show that electoral rewardswere effective in providing a long route to downward accountability. Incumbent mayorswere more likely to be reelected as able intermediaries if their municipality had receiveda large quota of bolsas (in spite of their having no role in this as the municipal allocationis formula based and implemented by Brasilia), if they had put into place a Bolsa Escolacouncil, and if there were no public denouncements that they had allocated bolsas to non-qualifying households (inclusion “error”).

These results suggest that direct accountability mechanisms (short route) are potentiallyimportant but need to be reinforced. The institutional mechanisms to perform this function areoften not in place. And, when they are, they are frequently ineffective due to lack of informationand of authority to act by councils. Accountability mechanisms through the political process arelonger (with a four years political cycle in Brazil) and tend to be diluted over many issuescompeting for politicians’ attention. Even if the long route to social accountability performs, it isa poor substitute for effective short route instruments.

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IV. How to learn more from implementation of the CCT approach to improve its use inalternative contexts?

4.1. By linking impact evaluation and experimentation with a results-based approach

International development agencies and governments are placing greater emphasis on theneed to engage in program evaluation. This is done in response to both (1) demands for greaterupward accountability of service providers to sources of funding, and (2) introduction of systemsof results-based management to improve program efficiency. Results of impact analyses for thefirst purpose are largely a public good while results for the latter purpose are largely privategoods.

As a public good, impact evaluation will always be severely under-funded, in spite ofexhortations by academics and social planners that such investments can have handsome socialpayoffs. The main reason is the inescapable logic of free riding in the provision of public goods.

As a private good used for program improvement, impact evaluations are also severelyunder-funded, because they face resistance by project managers in using scarce project funds forimpact evaluation purposes. This is because results generally come too late for use by the project,and they are often not informative for program improvement. Hence, it is not surprising thatproject managers are not interested in paying the cost of evaluation. Even elected officials willoften say that they are not interested in funding project evaluation because their political time isshorter that the time span needed for evaluators to obtain results. The unfortunate consequence ofdelays in yielding results is that millions of dollars have been spent to pay the cost of evaluationof CCT projects, and yet that very little useful information for program improvement has beenderived from these evaluations. Probably the most important, and non-negligible, benefit hasbeen to raise the public visibility of successful projects, thus helping to secure their survivalacross electoral cycles, as exemplified by sustainability of the Progresa/Oportunidades program.

Three changes need to be made to internalize some of the benefits of evaluation in theproject, and hence create incentives for at least partial funding of the evaluation by the projectitself:

(1) Just-in-time delivery of resultsEvaluation has to be designed so that short-term results are available and delivered to

project managers while the project is still active. This requires caution that short run outcomesnot be confused with longer term outcomes. In some cases, achieving favorable early outcomesmay be at the cost of a worst performance in the longer run. However, there are carefully chosenshort-term indicators of impact that can usually be defined as elements of a logframe approach.And this is easier for some projects such as remedial education with rapid observable benefits oneducational performance than for other projects that aim at raising incomes or reducingenvironmental degradation.

(2) Evaluation as part of results-based managementImpact evaluation for accountability purposes needs to be done by impartial external

auditors. By contrast, impact evaluation for results-based management needs to be part of aparticipatory process leading to institutional change. For this, evaluation must be built in alearning process that engages members of the organization who contribute information onindicators of success and failure, and internalize results from impact analysis in the design andpractices of the organization. These two objectives are not incompatible, but they have rarelybeen implemented jointly. Doing so requires engaging both program personnel and externalauditors in the evaluation, and making sure that the accountability purpose is not being perverted

20 11/13/05

by the management function. Yet, success in managing evaluation in this fashion allows todeliver benefits to the organization, and hence to internalize part of the costs of the evaluation asa private good in the project’s operational budget.

(3) Experimenting with alternative optionsEvaluation of the current design of a project is not sufficient to identify opportunities for

improvement. For this, experimentation needs to be done on specific aspects of the program thatappear to be crucial on performance and that are derived from recognized knowledge gaps. ForCCT for human capital formation this would include such aspects as different targeting rules(secret, vs. transparent, vs. participatory), the calibration and graduation of transfers (as opposedto the current in/out rules with much arbitrariness around the cut-off boundary), the method ofdelivery (through the mother or not, using cash or smart cards, etc.), different types ofcomplementary programs (supply side, returns to education), and alternative accountabilitymechanisms (transparency, community participation, appeals mechanisms). Experiments shouldbe sustained only for as long as it takes to generate statistically significant outcomes. Results arethen internalized into the results-based management process.

4.2. By addressing unresolved questions such as transactions costs in different contexts

There are several other questions on CCTs that need to be answered and for whichadditional research on other programs needs to be made, particularly in the context of low-incomecountries. One issue that has been raised is how to reduce transactions costs in programimplementation. CCT programs require to implement the following three administrativefunctions:

i) Establishing and updating the list of eligible households.ii) Enforcing conditionality rules.iii) Delivering payments.Methodologies for program implementation are highly specific to context. Brazil uses

electronic debit cards to distribute the CCTs, Ecuador asks beneficiaries to withdraw paymentsfrom a bank, while Mexico uses queuing in front of a table covered with banknotes every othermonth. High transactions costs are mentioned as an issue of concern is introducing a CCTapproach in Sub-Saharan Africa (Kakwani, Veras, and Son, 2005). Much experimentation is leftto be done to identify the most efficient approach for each particular context, in particular whereadministrative capacity is weak and corruption high.

V. Conclusions

We used results derived from experience in Mexico and Brazil to ask the following threequestions: (1) When to use the CCT approach? (2) How to increase the efficiency of theapproach? (3) How to learn more from the approach to improve its use in alternative contexts?

Answers to the first question indicate that the CCT approach has considerable promiseunder many circumstances, but also that a shockingly large number of important questionsremains to be answered, in particular as use of the approach is being extended to more countriesand large sums are being committed to these programs. Compared to a CT approach, CCT is anenormously efficient way of using transfers to induce a change in parents’ behavior toward childhuman capital development, if this is an objective of the program and if imposing a constraint onbehavior is justified to achieve child, household, or social gains. We found that this justificationis generally there for programs that use cash transfers beyond the objective of immediate povertyreduction among very poor households. The efficiency gains in inducing school attendance may

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well be some 16 times larger per dollar received with a CCT compared to a CT. If the objectiveis income for assets, CCT is indeed an effective approach.

These programs can, however, be quite expensive and difficult to implement. Becausethere are large informational rents due to adverse selection in targeting, leakages of payments tochildren that would go to school without a transfer are large, equal to 84% of cost under thecurrent Progresa design, implying a cost of $1,151/year per additional child enrolled in secondaryschool. It is for this reason important not to be complacent with current designs, and to seek waysof raising their efficiency in reducing poverty and enhancing child human capital development. Itis also important not to elevate this approach to the rank of unqualified panacea, and to recognizeits limitations, specificity to context, and needs for complementary interventions. In particular,supply-side interventions such as school transportation beyond a certain distance and a greaterdensity of schools are necessary when CCTs are insufficient to induce a behavioral response.

In answer to the second question, we have explored several ways in which a moreefficient use of the approach can be made. This includes: (1) better targeting and calibration oftransfers for maximum effect of the conditionality on behavior by focusing on children at risk ofnot going to school and most responsive to a transfer, with potential large efficiency gains whenenrollment rates are low in the target population and there are severe budget constraints inincorporating all targeted households in the program; (2) better understanding of heterogeneity inthe incidence of benefits, in particular by parent’s educational levels, to design targetedcomplementary interventions; (3) use of the CCT approach as a safety net to reduce vulnerabilityto shocks of child human capital development, as short run use of children as risk-copinginstruments leads to long term losses of human capital (a child out of school for one semester insecondary school has 23% less chance of being at school the following semester), creating asource of new poor, while CCT can serve as effective insurance mechanisms for child humancapital; (4) better downward accountability systems to improve service delivery in CCTprograms, especially through greater transparency in targeting rules and through a more effective“short route to social accountability” between providers and stakeholders.

To achieve these efficiency gains, and in answer to the third question, more useful impactevaluations and experimentations need to be designed, not only for the purpose of ex-postaccountability but also to support a results-based management approach to program improvement.Implementing these sources of efficiency gains requires urgent investments in learning-by-experimenting for use of the CCT approach in different contexts. While progress has been madewith implementing rigorous impact analyses, the culture of experimentation is yet to enter CCTprograms. This is particularly necessary if the approach is to be implemented in poor countrycontexts, most particularly Sub-Saharan Africa, which are quite different from the middle-incomecountry contexts where experience has been gained. It is indeed notable that large sums are beinginvested in the approach while so little is being spent in seeking to learn from past experiencesand in designing learning experiments that can be embedded into results-based managementmethods.

References

Baland, Jean-Marie, and James Robinson. 2000. “Is Child Labor Inefficient?” Journal of PoliticalEconomy 108(4): 663-679.

Behrman, Jere, and James Knowles. 1999. “Household Income and Child Schooling in Vietnam.”World Bank Economic Review 13(2): 211-256.

Bobonis, Gustavo, and Frederico Finan. 2005. “Endogenous Social Interaction Effects in SchoolParticipation in Rural Mexico.” University of California at Berkeley.

22 11/13/05

Bourguignon, François, Francisco Ferreira, and Philippe Leite. 2003. “Conditional CashTransfers, Schooling, and Child Labor: Micro-Simulating Brazil's Bolsa Escola Program.”World Bank Economic Review 17(2): 229-54.

Coady, Dave, and Rebecca Lee Harris. 2001. “Evaluating Transfer Programs Within a GeneralEquilibrium Framework.” FCND Discussion Paper #110. Washington D.C.: InternationalFood Policy Research Institute.

Currie, Janet, and Enrico Moretti. 2003. “Mother’s Education and the IntergenerationalTransmission of Human Capital: Evidence from College Openings.” Quarterly Journal ofEconomics 118(4): 1495-1532.

Das, Jishnu, Quy-Toan Do, and Berk Özler. 2005. “Reassessing Conditional Cash TransferPrograms”. The World Bank Research Observer 20(1): 57-80.

Edmonds, Eric. 2005. “Child Labor and Schooling Responses to Anticipated Income in SouthAfrica.” Journal of Development Economics, forthcoming.

Foster, Andrew, and Mark Rosenzweig. 1995. “Learning by Doing and Learning from Others:Human Capital and Technical Change in Agriculture.” Journal of Political Economy 103(6):1176-1209.

Gertler, Paul, Sebastian Martinez, and Marta Rubio. 2005. “Investing Cash Transfers to RaiseLong Term Living Standards.” University of California at Berkeley.

Gertler, Paul. 2004. “Do Conditional Cash Transfers Improve Child Health? Evidence fromProgresa’s Control Randomized Experiment.” American Economic Review 94(2): 336-341.

Hoddinott, John, and Emmanuel Skoufias. 2004. “The Impact of Progresa on FoodConsumption.” Economic Development and Cultural Change 53(1): 37-62.

Jacoby, Hanan, and Emmanuel Skoufias. 1997. “Risk, Financial Markets, and Human Capital in aDeveloping Country.” Review of Economic Studies 64(3): 311-335.

Kakwani, Nanak, Fabio Veras, and Hyun Son. 2005. Conditional Cash Transfers in AfricanCountries. Working Paper No. 9, International Poverty Center, UNDP.

Milligan, Kevin, Enrico Moretti, and Philip Oreopoulos. 2004. “Does Education ImproveCitizenship? Evidence from the U.S. and the U.K.” Journal of Public Economics 88(9-10):1667-1695.

Parker, Susan, and Emmanuel Skoufias. 2004. “Labor Market Shocks and Their Impacts on Workand Schooling: Evidence from Urban Mexico”. Forthcoming in Journal of PopulationEconomics.

Rawlings, Laura, and Gloria Rubio. 2005. “Evaluating the Impact of Conditional Cash TransferPrograms.” The World Bank Research Observer 20(1): 29-55.

Reference #1: de Janvry, Alain, Frederico Finan, and Elisabeth Sadoulet. 2001. “Decomposingthe Channels of Influence of CCTs in a Structural Model of Educational Choice.” Universityof California at Berkeley, http://are.Berkeley.EDU/~sadoulet/.

Reference #2: de Janvry, Alain, and Elisabeth Sadoulet. 2003. “Dépasser Bono: Comment rendreplus efficiente l'aide au développement.” Revue d'économie du développement, 4(December):63-76.

Reference #3: de Janvry, Alain, and Elisabeth Sadoulet. 2005. “Making Conditional CashTransfer Programs More Efficient: Designing for Maximum Effect of the Conditionality.”World Bank Economic Review, forthcoming.

Reference #4: de Janvry, Alain, Frederico Finan, and Elisabeth Sadoulet. 2005. “Can conditionalcash transfer programs serve as safety nets in keeping children at school and from workingwhen exposed to shocks?” Journal of Development Economics, forthcoming.

Reference #5: de Janvry, Alain, Frederico Finan, Elisabeth Sadoulet, Donald Nelson, KathyLindert, Bénédicte de la Brière, and Peter Lanjouw. 2005. “Brazil’s Bolsa Escola Program:The Role of Local Governance in Decentralized Implementation.” DECRG, The World Bank.

Schultz, T. Paul. 2004. “School Subsidies for the Poor: Evaluating the Mexican Progresa PovertyProgram.” Journal of Development Economics 74(1): 199-250.

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UNDP. 2004. “Slipping Into Poverty: A Neglected Issue in Anti-Poverty Strategies”. One Pager,Brasilia: International Poverty Center.

World Bank. 2004. Making Services Work for Poor People. World Development Report 2004.Washington D.C.