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Program quality and treatment completion for youth training programs

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  • Dammert, Ana C.
  • Galdo, Jose

Abstract

This paper analyzes the effects of training quality on the likelihood of treatment completion by estimating dose–response functions via a generalized propensity score. Results show a statistically positive relationship between training quality and treatment completion for youth participants in Peru.

Suggested Citation

  • Dammert, Ana C. & Galdo, Jose, 2013. "Program quality and treatment completion for youth training programs," Economics Letters, Elsevier, vol. 119(3), pages 243-246.
  • Handle: RePEc:eee:ecolet:v:119:y:2013:i:3:p:243-246
    DOI: 10.1016/j.econlet.2013.03.006
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    References listed on IDEAS

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    1. Kluve, Jochen & Schneider, Hilmar & Uhlendorff, Arne & Zhao, Zhong, 2007. "Evaluating Continuous Training Programs Using the Generalized Propensity Score," IZA Discussion Papers 3255, Institute for the Study of Labor (IZA).
    2. Heckman, J.J. & Hotz, V.J., 1988. "Choosing Among Alternative Nonexperimental Methods For Estimating The Impact Of Social Programs: The Case Of Manpower Training," University of Chicago - Economics Research Center 88-12, Chicago - Economics Research Center.
    3. Michael Gerfin & Michael Lechner, 2002. "A Microeconometric Evaluation of the Active Labour Market Policy in Switzerland," Economic Journal, Royal Economic Society, vol. 112(482), pages 854-893, October.
    4. Eric A. Hanushek & Victor Lavy & Kohtaro Hitomi, 2008. "Do Students Care about School Quality? Determinants of Dropout Behavior in Developing Countries," Journal of Human Capital, University of Chicago Press, vol. 2(1), pages 69-105.
    5. James Heckman & Neil Hohmann & Jeffrey Smith & Michael Khoo, 2000. "Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 115(2), pages 651-694.
    6. Carlos A. Flores & Alfonso Flores-Lagunes & Arturo Gonzalez & Todd C. Neumann, 2012. "Estimating the Effects of Length of Exposure to Instruction in a Training Program: The Case of Job Corps," The Review of Economics and Statistics, MIT Press, vol. 94(1), pages 153-171, February.
    7. Galdo, Jose & Chong, Alberto, 2012. "Does the quality of public-sponsored training programs matter? Evidence from bidding processes data," Labour Economics, Elsevier, vol. 19(6), pages 970-986.
    8. Jochen Kluve & Hilmar Schneider & Arne Uhlendorff & Zhong Zhao, 2012. "Evaluating continuous training programmes by using the generalized propensity score," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 175(2), pages 587-617, April.
    9. FLORES-LAGUNES Alfonso & CHOE Chung & LEE Sang-Jun, 2011. "Do Dropouts Benefit from Training Programs? Korean Evidence Employing Methods for Continuous Treatments," LISER Working Paper Series 2011-34, LISER.
    10. James Heckman & Jeffrey Smith & Christopher Taber, 1998. "Accounting For Dropouts In Evaluations Of Social Programs," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 1-14, February.
    11. Waller, Marie, 2008. "Further training for the unemployed : what can we learn about dropouts from administrative data?," FDZ Methodenreport 200804_en, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
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    Cited by:

    1. repec:eee:jeeman:v:85:y:2017:i:c:p:146-170 is not listed on IDEAS
    2. Chung Choe & Alfonso Flores-Lagunes & Sang-Jun Lee, 2015. "Do dropouts with longer training exposure benefit from training programs? Korean evidence employing methods for continuous treatments," Empirical Economics, Springer, vol. 48(2), pages 849-881, March.

    More about this item

    Keywords

    Training; Quality; Dropouts; Propensity scores; Dose–response functions;

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • J2 - Labor and Demographic Economics - - Demand and Supply of Labor
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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