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Evaluating continuous training programs using the generalized propensity score1

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  • Kluve, Jochen
  • Schneider, Hilmar
  • Uhlendorff, Arne
  • Zhao, Zhong

Abstract

This paper assesses the dynamics of treatment effects arising from variation in the duration of training. We use German administrative data that have the extraordinary feature that the amount of treatment varies continuously from 10 days to 395 days (i.e. 13 months). This feature allows us to estimate a continuous dose-response function that relates each value of the dose, i.e. days of training, to the individual post-treatment employment probability (the response). The dose-response function is estimated after adjusting for covariate imbalance using the generalized propensity score, a recently developed method for covariate adjustment under continuous treatment regimes. Our data have the advantage that we can consider both the actual and planned training durations as treatment variables: If only actual durations are observed, treatment effect estimates may be biased because of endogenous exits. Our results indicate an increasing dose-response function for treatments of up to 100 days, which then flattens out. That is, longer training programs do not seem to add an additional treatment effect. --

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Bibliographic Info

Paper provided by Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen in its series Technical Reports with number 2007,39.

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Date of creation: 2007
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Handle: RePEc:zbw:sfb475:200739

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Related research

Keywords: Training; program evaluation; continuous treatment; generalized propensity score;

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References

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  1. Guido W. Imbens, 2004. "Nonparametric Estimation of Average Treatment Effects Under Exogeneity: A Review," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 4-29, February.
  2. Jochen Kluve & Boris Augurzky, 2005. "Assessing the performance of matching algorithms when selection into treatment is strong," RWI Discussion Papers 0021, Rheinisch-Westfälisches Institut für Wirtschaftsforschung.
  3. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
  4. Miquel, Ruth & Lechner, Michael & Wunsch, Conny, 2005. "Long-Run Effects of Public Sector Sponsored Training in West Germany," ZEW Discussion Papers 05-02, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  5. Kluve, Jochen, 2006. "The Effectiveness of European Active Labor Market Policy," IZA Discussion Papers 2018, Institute for the Study of Labor (IZA).
  6. Schneider, Hilmar & Uhlendorff, Arne, 2006. "Die Wirkung der Hartz-Reform im Bereich der beruflichen Weiterbildung," IZA Discussion Papers 2255, Institute for the Study of Labor (IZA).
  7. Flores-Lagunes, Alfonso & Gonzalez, Arturo & Neumann, Todd C., 2007. "Estimating the Effects of Length of Exposure to a Training Program: The Case of Job Corps," IZA Discussion Papers 2846, Institute for the Study of Labor (IZA).
  8. Jere R. Behrman & Yingmei Cheng & Petra E. Todd, 2004. "Evaluating Preschool Programs When Length of Exposure to the Program Varies: A Nonparametric Approach," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 108-132, February.
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Citations

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Cited by:
  1. BIA Michela & FLORES Carlos A. & MATTEI Alessandra, 2011. "Nonparametric Estimators of Dose-Response Functions," CEPS/INSTEAD Working Paper Series 2011-40, CEPS/INSTEAD.
  2. Clausen, Jens & Heinesen, Eskil & Hummelgaard, Hans & Husted, Leif & Rosholm, Michael, 2008. "The Effect of Integration Policies on the Time until Regular Employment of Newly Arrived Immigrants: Evidence from Denmark," IZA Discussion Papers 3849, Institute for the Study of Labor (IZA).
  3. Crombrugghe Denis de & Espinoza Henry & Heijke Hans, 2010. "Determinants of dropout behaviour in a job training programme for disadvantaged youths," ROA Research Memorandum 008, Maastricht University, Research Centre for Education and the Labour Market (ROA).
  4. Heyer, Gerd & Koch, Susanne & Stephan, Gesine & Wolff, Joachim, 2012. "Evaluation der aktiven Arbeitsmarktpolitik: Ein Sachstandsbericht für die Instrumentenreform 2011 (Evaluation of active labor market programs : a summary of recent results for the German program refo," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 45(1), pages 41-62.
  5. Michela Bia & Alessandra Mattei, 2012. "Assessing the effect of the amount of financial aids to Piedmont firms using the generalized propensity score," Statistical Methods and Applications, Springer, vol. 21(4), pages 485-516, November.
  6. J. Kluve & H. Lehmann & C. M. Schmidt, 2007. "Disentangling Treatment Effects of Active Labor Market Policies: The Role of Labor Force Status Sequences," Working Papers 620, Dipartimento Scienze Economiche, Universita' di Bologna.

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