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 The impact of a cash transfer program on cognitive achievement:   The Bono de Desarrollo Humano  of Ecuador  Juan Ponce Flacso, Ecuador  Arjun Singh Bedi International Institute of Social Studies, Erasmus University Rotterdam Ocotber 2010

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 The impact of a cash transfer program on cognitiveachievement:   The Bono de Desarrollo Humano

 of Ecuador

 Juan PonceFlacso, Ecuador

 Arjun Singh BediInternational Institute of Social Studies, Erasmus University Rotterdam

Ocotber 2010

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•   Throughout Latin America, conditional cash transfer (CCT)programs play an important role in social policy 

•  CCT programs started in the 1990s and aim to influence humancapital accumulation and serve as a means of breaking the inter-generational cycle of poverty 

•  Provide a cash transfer to a target group conditional on certain  actions

  Visits to health centres –   growth monitoring and nutritional supplements

 Enrol in school and attend school regularly 

Motivation and Introduction

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•   A number of CCT programs operate in Latin America and they have been systematically evaluated

•  On the education front, a majority of studies find that CCTprograms boost school enrolment and ensure regular schoolattendance

•   These are clearly the first steps to ensure higher educationalattainment and achievement

•  However, a focus on enrolment may not be enough to ensureaccumulation of adequate human capital

•  It is important to examine the effect of such programs oncognitive achievement

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•  Higher cognitive achievement as captured by testscores, are likely to ensure a longer duration in school

and are also correlated with labour market success  US data –   Murnane, Willet and Levy (1995); Jencks

and Phillips (1999); Rose (2006)

 Developing countries –     Alderman et al. (1996);Lavy   et al. (1997)

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•   Theoretically, such programs are likely to influence cognitiveachievement in several ways

•  Positive effects through•

 Increase/ensure regular attendance and this in turn is likely to

 translate into higher test scores•

 Increase household incomes, increased food consumption, betternutrition

 Reductions in child labour both in terms of the probability of 

 working and hours of work 

  There may also be negative effects

•  Increases in school enrolment may translate into congestedclassrooms

 If the program encourages less able students to enrol, then changesin student composition may lead to a decline in average test scores

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•  Studies evaluating the effect of CCT programs on cognitiveachievement are relatively scarce

•  Contribution of the paper is to evaluate the effect of theEcuadorian cash transfer program on students’  cognitiveachievement

•   We exploit the manner in which the program/Bono is allocatedand rely on a regression discontinuity design to identify theimpact of the program on second grade cognitive achievement

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CCT programs in Latin America

•  Started in Brazil in 1995, followed by Mexico in 1997,Honduras in 1998 and Nicaragua in 2000

•  Programs have been heavily evaluated along several

dimensions  School enrolment (Behrman, et al. 2005; Schultz, 2004;

Skoufias, 2000)

  Attendance (Maluccio  and Flores, 2004)

 Nutrition, illness (Skoufias, 2000; Maluccio  and Flores, 2004)

 Child work (Duryea and Morrison, 2004)

 Cognitive outcomes (Behrman, Sengupta  and Todd, 2000)for Mexico, find no effect on test scores

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Ecuador’s program

 BDH program was launched in 2003 and incorporated

two existing programs•  Main objective is to improve the formation of human

capital amongst poor families in Ecuador

•  Education and health component  Education component requires children from age 6-15 to

enrol in school and attend at least 90 percent of school days

 Health component focuses on children under 6•  Cash transfer of USD 15 per month per family 

  Targeted at families with average monthly expenditureof USD 100

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Ecuador’s program•  Selection of beneficiaries

 Program uses an individual targeting strategy 

 Participation is based on an index called Selben  (“Sel”ection  of “Ben”  ificiaries)

 Index is constructed on the basis of 27 variables (household

infrastructure, educational characteristics, assets) and takes values from 0 to 100

  Those scoring below 50.65 are eligible to receive benefits

 In 2004, the annual budget was USD 190 million, around 1percent of GDP and covered 1.1 million households or 40percent of the population

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Ecuador’s program•   Vos  et al. (2001) find a 5 percentage point increase in school

enrolment

•  Leon and Younger (2007) find small nutritional effects

•  Schady   and Araujo  (2006) report increases in school enrolmentin the age group 6-17 (about 10 percentage points) and reduction

in child work (about 17 percentage points)•  Ponce (2008) refines this finding 

 Effects are heterogeneous

 Restricted to children from the bottom quintile while for families close tothe cut off there are no enrolment effects

 Program beneficiaries around the neighbourhood of the eligibility cut off experience sharp increases in food (25 percent) and educational

expenditure (46 percent)

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Empirical strategy •   To isolate the effect of the BDH on students’  test score we begin

 with the following educational production function

•  Y i 

 -  outcome variable; S i 

 is the Selben  index ; T i 

 indicates receipt

of BDH

•  Program participation is not random and it is quite likely that thecoefficient on T i 

 is likely to be downward biased

ii

 j

i

 j

 jii uT S X Y 

    3

1

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•  If individuals were assigned to treatment solely  on thebasis of the assignment variable then it may be arguedthat the program allocation rule replicates randomassignment around the cut off point

•  In this case it is unlikely that program participation isdetermined so strictly 

•   There is a fair degree of “fuzziness”

•   Treatment status depends on the Selben  index but in astochastic manner

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•  Since we have a variable (an instrument, Z i  ) that is, the cut off point which determines treatment status

•   There is no reason to expect that this cut off point is correlated with u i 

•  Estimates based on (3) provide a local average treatment effect

)1(3

1

ii

 j

i

 j

 jii uT S X Y 

    

)2(

3

1

ii

 j

 ji jii w Z S X T 

   

)3(

3

1uT S X Y  i

 j

 j

i jii

    

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•  Data were collected between November 2004 and February 2005

•   A year and a half after the program had been launched•   The data cover rural areas of the country and the capital•   Three different instruments

 Standardized tests in mathematics and language were conducted forstudents in 2nd

 and 4th

 grades

 School and teacher characteristics

 Household information

•  Second grade sample has 2588 children

 1469 in treatment and 1119 in the control group

Data

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 Validity of the RDD

 First stage estimates (equation 2)

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       2

       1       3

       1       0

       7

       1       9

       2       8       3

       0

       5       2

       3       7

       5       3

       5       8

       6       4

       5       4

       5       1

       6       2

       5       8

       5       2

       5       5

       5

       0

       5       5

       5       3       5

       4

       5       8

       6       7

       5       3

       5       3

       5       2

       5       2

       5       5

       6       4

       7       5

       7       4

       5       9

       6       2

       5       8

       5       8

       7

       2

       5       3

       5       3

       8       0

       6       9

       5       8

       4

       9

       4       2

       4       2

       4       7

       3       3       3

       5

       3       0

       2       6

       3       1

       1       7

       2       5

       1       5       1

       6

       2

       9

       1       2

       5

       8

       4

       1       2

              1 1

       0

       2       0

       4       0

       6       0

       8       0

       F     r     e     q     u     e     n     c     y

       1       0

       1       5

       2       0

       2       5

       3       0

       3       5

       4       0

       4       7

 .       6       5

       5       0

 .       6       5

       5       3

 .       6       5

       6       0

       6       5

       7       0

       7       5

Selben index

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•  CCT programs appear to have a large effect on enrolment,attendance, reduction of child labour

•    These are the first steps but a focus on learning may also berequired

•    We exploited the program’s design and used an arguably credible empirical strategy and found that the BDH does notlead to higher rest scores

 Maybe we are analyzing the effects too early 

 Maybe we need to examine those lower down in the Selben

 distribution

 Highlights strengths and limitation of such programs

Concluding remarks