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Endogenous Exit Bias in Training Programs for Unemployed Workers

Author

Listed:
  • Kluve, Jochen

    (KfW Development Bank)

  • Rinne, Ulf

    (IZA)

  • Uhlendorff, Arne

    (CREST)

  • Zhao, Zhong

    (Renmin University of China)

Abstract

This paper assesses the importance of reverse causality when evaluating the impact of training duration for unemployed workers. We use planned duration as an instrumental variable for actual duration. Our results suggest that the potential endogeneity of exits seems to be only relevant in the lower and upper part of the treatment duration distribution.

Suggested Citation

  • Kluve, Jochen & Rinne, Ulf & Uhlendorff, Arne & Zhao, Zhong, 2012. "Endogenous Exit Bias in Training Programs for Unemployed Workers," IZA Discussion Papers 6565, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp6565
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    References listed on IDEAS

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    1. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    2. Fitzenberger, Bernd & Osikominu, Aderonke & Paul, Marie, 2010. "The Heterogeneous Effects of Training Incidence and Duration on Labor Market Transitions," IZA Discussion Papers 5269, Institute of Labor Economics (IZA).
    3. van Ours, Jan C., 2004. "The locking-in effect of subsidized jobs," Journal of Comparative Economics, Elsevier, vol. 32(1), pages 37-55, March.
    4. 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, President and Fellows of Harvard College, vol. 115(2), pages 651-694.
    5. Kluve, Jochen & Schneider, Hilmar & Uhlendorff, Arne & Zhao, Zhong, 2007. "Evaluating Continuous Training Programs Using the Generalized Propensity Score," Ruhr Economic Papers 35, RWI - Leibniz-Institut für Wirtschaftsforschung, Ruhr-University Bochum, TU Dortmund University, University of Duisburg-Essen.
    6. 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.
    7. 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.
    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. 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.
    10. 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.
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    Cited by:

    1. Cerqua, Augusto & Urwin, Peter & Thomson, Dave & Bibby, David, 2020. "Evaluation of education and training impacts for the unemployed: Challenges of new data," Labour Economics, Elsevier, vol. 67(C).

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    More about this item

    Keywords

    local average treatment effect; dropouts; treatment duration;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation

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