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How Good Are Ex Ante Program Evaluation Techniques? The Case of School Enrollment in PROGRESA

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  • Fabian Bornhorst

Abstract

This paper evaluates a microsimulation technique by comparing the simulated outcome of a program with its actual effect. The ex ante evaluation is carried out for a conditional cash transfer program, where poor households were given money if the children attended school. A model of occupational choice is used to simulate the expected impact of the program. The results suggest that the transfer would indeed increase school attendance and do more so among girls than boys. While the simulated effect tends to be larger than the actual effect, the latter lies within bootstrapped confidence intervals of the simulation.

Suggested Citation

  • Fabian Bornhorst, 2009. "How Good Are Ex Ante Program Evaluation Techniques? The Case of School Enrollment in PROGRESA," IMF Working Papers 2009/187, International Monetary Fund.
    • Handle: RePEc:imf:imfwpa:2009/187
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    References listed on IDEAS

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    1. Fran??ois Bourguignon & Francisco H. G. Ferreira & Phillippe G. Leite, 2002. "Ex-ante Evaluation of Conditional Cash Transfer Programs: The Case of Bolsa Escola," William Davidson Institute Working Papers Series 516, William Davidson Institute at the University of Michigan.
    2. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    4. Paul Schultz, T., 2004. "School subsidies for the poor: evaluating the Mexican Progresa poverty program," Journal of Development Economics, Elsevier, vol. 74(1), pages 199-250, June.
    5. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-620, September.
    6. Behrman, Jere R & Sengupta, Piyali & Todd, Petra, 2005. "Progressing through PROGRESA: An Impact Assessment of a School Subsidy Experiment in Rural Mexico," Economic Development and Cultural Change, University of Chicago Press, vol. 54(1), pages 237-275, October.
    7. François Bourguignon & Martin Fournier & Marc Gurgand, 2002. "Selection Bias Correction Based on the Multinomial Logit Model," Working Papers 2002-04, Center for Research in Economics and Statistics.
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    Cited by:

    1. Yáñes Aguilar, Ernesto, 2012. "El Impacto del Bono Juancito Pinto. Un Análisis a Partir de Micro Simulaciones," Documentos de trabajo 6/2012, Instituto de Investigaciones Socio-Económicas (IISEC), Universidad Católica Boliviana.
    2. Alina-Elena Balalia (Iosif) & Daniel Rauhut, 2012. "Assessing Territorial Impact Assessment: The Case of Services of General Interest," ERSA conference papers ersa12p251, European Regional Science Association.
    3. Yáñez, Ernesto, 2012. "El impacto del Bono Juancito Pinto. Un análisis a partir de microsimulaciones," Revista Latinoamericana de Desarrollo Economico, Carrera de Economía de la Universidad Católica Boliviana (UCB) "San Pablo", issue 17, pages 75-112, Mayo.
    4. Pablo Vidueira & José M. Díaz-Puente & María Rivera, 2014. "Socioeconomic Impact Assessment in Ex Ante Evaluations," Evaluation Review, , vol. 38(4), pages 309-335, August.

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    Keywords

    WP; age group; labor market;
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