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The Impact of Training Policies in Latin America and the Caribbean: The Case of Programa Joven

  • Cristian Aedo
  • Sergio Nuñez
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    This paper evaluates Programa Joven, a training program conducted by Argentina`s Ministerio del Trabajo. The paper adapts and applies a non-experimental evaluation methodology to answer the following questions: (1) Did Programa Joven increase the labor income of the trainees? (2) Did Programa Joven increase the probability of employment? (3) What was the rate of return to dollars spent on Programa Joven? The basic methodology used was the Matching Estimators approach. The application of this methodology requires two steps: first, the estimation of a model of program participation (propensity scores), and second, conditional upon the estimated propensity scores, the use of matching estimators to calculate the impact of the program. Three different information sources were used to estimate the propensity scores. These different information sources permitted the analysis of an additional question: how sensitive are program impact estimates to different propensity score specifications? This question has not been addressed by the previous literature but is addressed here. The paper hypothesizes that impact estimates are in fact sensitive to different propensity score specifications. Additionally, the paper reports and compares the propensity scores estimated from each of these data sources, and then estimates the program impact on earnings and employment based upon these propensity scores. Finally, the authors carry out a cost-benefit analysis of Programa Joven based upon cost information and program impact estimates (benefits).

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    File URL: http://www.iadb.org/research/pub_hits.cfm?pub_id=R-483&pub_file_name=pubR-483.pdf
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    Paper provided by Inter-American Development Bank, Research Department in its series Research Department Publications with number 3175.

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    Date of creation: Dec 2004
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    Handle: RePEc:idb:wpaper:3175
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    1. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc.
    2. HÄRDLE, Wolfgang, 1992. "Applied nonparametric methods," CORE Discussion Papers 1992003, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    4. Heckman, James J & Smith, Jeffrey, 1997. "Making the Most Out of Programme Evaluations and Social Experiments: Accounting for Heterogeneity in Programme Impacts," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 487-535, October.
    5. Heckman, James J & Ichimura, Hidehiko & Todd, Petra E, 1997. "Matching as an Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," Review of Economic Studies, Wiley Blackwell, vol. 64(4), pages 605-54, October.
    6. Charles F. Manski, 1996. "Learning about Treatment Effects from Experiments with Random Assignment of Treatments," Journal of Human Resources, University of Wisconsin Press, vol. 31(4), pages 709-733.
    7. Oliver LINTON, . "Applied nonparametric methods," Statistic und Oekonometrie 9312, Humboldt Universitaet Berlin.
    8. Heckman, James J. & Lalonde, Robert J. & Smith, Jeffrey A., 1999. "The economics and econometrics of active labor market programs," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 31, pages 1865-2097 Elsevier.
    9. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September.
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