University of Warsaw November 19, CONDITIONAL CASH TRANSFERS, SCHOOLING AND CHILD LABOR: MICRO-SIMULATING BOLSA ESCOLA By FRANÇOIS BOURGUIGNON, FRANCISCO H. G. FERREIRA PHILLIPPE G. LEITE Presented by Luke Okafor and Elizabeth Rivard

University of Warsaw November 19, OUTLINE INTRODUCTION BOLSA ESCOLA PROGRAMME METHODOLOGY APPRAISAL OF THE STUDY SUGGESTIONS FOR IMPROVEMENT CRITIQUE BY SCHWARTZMAN CONCLUSIONS

University of Warsaw November 19, INTRODUCTION Cash transfers targeted to poor people with conditions The Brazilian National Bolsa Escola is a kind of redistributive programme with features of: -Means-test -The behavioral conditionality -Eligibility criteria Evaluation of the kind of programme could be: -Ex-post approaches -Ex-ante methods

University of Warsaw November 19, BOLSA ESCOLA PROGRAMME Bolsa Escola Programme was created by law in April 2001 Eligibility for participation in the programme -Households with monetary income below 90 Reasi (R$) per month -with children aged 6 to % school attendance Goals of the programme: -Reduction of current levels of poverty and inequality -Provision of incentives for reduction of future poverty

University of Warsaw November 19, The decision of how the child’s time allocation is made within the household ignored The decision to send the child to school is last to made The issue of various siblings in same household ignored The composition of the household is exogenous ASSUMPTIONS OF THE STUDY

University of Warsaw November 19, METHODOLOGY The occupational choice variable Si will be modeled using the standard utility-maximizing interpretation of the multinomial Logit framework, S i = k iff S k (A i, X i, H i ; Y -i + y ik ) + v ik > S j (A i, X i, H i ; Y -i + y ij ) + v ij for j ≠k (1) Collapse non-income explanatory variables into a single vector Z i and linearize U i (j) = S j (A i, X i, H i ; Y -i + y ij ) + v ji = Z i.γ j + (Y -i + y ij )α j + v ij (2)

University of Warsaw November 19, METHODOLOGY The observed marketing earning of the child denoted by w i. Assuming the standard Becker-Mincerian human capital model, writes: Log w i = X i.δ + m*Ind(Si=1) + u i (3) X i set of individual characteristics U i random error terms Ind(Si=1) indicator function Based on (3) the child’s contribution to the household income y ij under the various alternatives j

University of Warsaw November 19, METHODOLOGY Y i0 = Kwi; y i1 = MKwi; y i2 =Dy io = DKwi with M = Exp (m) where it is assumed that y ij values the output or potential market earnings Wi is decomposed into in the proportions of k, 1-M and 1-D Replacing (4)in (2) leads to U i (j) = S j (A i, X i, H i ; Y -i + y ij ) + v ji = Z i.γ j + Y -i α j + β.wi + v ij with: β 0 = α 0 K, β1= α 1 MK; β2= α 2 Dk (5)

University of Warsaw November 19, METHODOLOGY This is the final model simulated by the authors. If the coefficients of α, β, γ, wi and Vij, then the child’s occupational choice type selected by the household I is K* = Arg Max [ Ui (j)] (6) Equation (5) is the benchmark case. If the Bolsa Escola programme entitled all the children going to school a transfer of T, then, 5 is replaced by U i (j) = Z i.γ j + (Y -i + BE ij ).α j + β.wi + v ij with: βE i0 = 0 and BEi 1 =BEi 2 =T (7)

University of Warsaw November 19, APPRAISAL OF THE STUDY The individual effects could be correlated with schooling choice and the correlation between the composite error terms could make the OLS to be biased The validation of the simulated model on survey data alone may lead to biased results eg sample bias, age effects etc Calibrations based on the simulations afterwards may be biased as well

University of Warsaw November 19, APPRAISAL OF THE STUDY CONTD The eligibility condition created problem of additionality: attendance and learning, a different kind of social exclusion, and length of the programme Target assistencialist bias Table 1: Bolsa Escola in Recife and Belo Horizonte

University of Warsaw November 19, APPRAISAL OF THE STUDY CONTD Influence of unemployment in the family Influence of gender on the decision making process The problem associated with undeclared income The scored-based proxy for permanent may be too far from average truth

University of Warsaw November 19, SUGGESTIONS FOR IMPROVEMENT The use of simulation and CGE may give room for taking care of changing economic conditions in the long run The labour supply model: the intra-labour choice allocations could be incorporated into the study Validation and calibration of the model should be based on data from participants and non-participants in the Bolsa Escola programmme and the Survey

University of Warsaw November 19, CONCLUSIONS-ORIGINAL PAPER Take the size of the family into account when determining which families are eligible Monitor school attendence rather than school enrollment The assumption that in poor families, children (ages 6-13) do not go to school because they have to work and little money incentive could change this situation may be too simplistic.

University of Warsaw November 19, CONCLUSIONS-ORIGINAL PAPER Education focus of the programme (may have missed target) Target transfer to the age with the highest risk (age 14 and above)

University of Warsaw November 19, CRITIQUE BY SCHWARTZMAN Patterns of attendance not related to the stipend; limited government monitoring of attendance

University of Warsaw November 19, CRITIQUE BY SCHWARTZMAN Missing school for work was not widespread

University of Warsaw November 19, CRITIQUE BY SCHWARTZMAN Having the stipend decreased the chances of a child working for those aged 5-6 and 14-17, but not those aged 7-13

University of Warsaw November 19, CRITIQUE BY SCHWARTZMAN Children receiving the stipend actually worked more than those who did not; child labor is mostly rural, ages 15-17

University of Warsaw November 19, CRITIQUE BY SCHWARTZMAN The least poor do not always receive the stipend: majority of the poor are urban, but programme focuses on rural poor Of the 12.8 million children in families at the lowest fifth income quintile, 35% live in rural areas, but receive 40% of the stipends. Among the rural poor, 39% receive the stipend; among the urban poor, only 30%

University of Warsaw November 19, CONCLUSIONS-SCHWARTZMAN Increase stipend with age (14 and older receive more) Increase overall quality of schools Better targeting, implementation and monitoring