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Evaluating continuous training programmes by using the generalized propensity score

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

Summary: The paper assesses the heterogeneity 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 probability of employment (the response). The dose-response function is estimated after adjusting for covariate imbalance by using the generalized propensity score, which is a recently developed method for covariate adjustment under continuous treatment regimes. Our data have the advantage that we can consider both the actual and the planned durations of training 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 120 days, which then flattens out, i.e. longer training programmes do not seem to add an additional treatment effect.

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File URL: http://hdl.handle.net/10.1111/j.1467-985X.2011.01000.x
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Article provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series A (Statistics in Society).

Volume (Year): 175 (2012)
Issue (Month): 2 (04)
Pages: 587-617

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Handle: RePEc:bla:jorssa:v:175:y:2012:i:2:p:587-617
DOI: j.1467-985X.2011.01000.x
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  1. Blien, Uwe & Hirschenauer, Franziska & Arendt, Manfred & Braun, Hans Jürgen & Gunst, Dieter-Michael & Kilcioglu, Sibel & Kleinschmidt, Helmut & Musati, Martina & Roß, Hermann & Vollkommer, Dieter & We, 2004. "Typisierung von Bezirken der Agenturen für Arbeit (Classification of employment office areas)," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 37(2), pages 146-175.
  2. 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).
  3. Peter R. Mueser & Kenneth Troske & Alexey Gorislavsky, 2003. "Using State Administrative Data to Measure Program Performance," Working Papers 0309, Department of Economics, University of Missouri.
  4. repec:iab:iabzaf:v:37:i:2:p:146-175 is not listed on IDEAS
  5. Jochen Kluve & Boris Augurzky, 2007. "Assessing the performance of matching algorithms when selection into treatment is strong," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 533-557.
  6. 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.
  7. Guido W. Imbens, 2003. "Nonparametric Estimation of Average Treatment Effects under Exogeneity: A Review," NBER Technical Working Papers 0294, National Bureau of Economic Research, Inc.
  8. Juan José Díaz & Sudhanshu Handa, 2005. "An Assessment of Propensity Score Matching as a Non Experimental Impact Estimator: Evidence from Mexico's PROGRESA Program," IDB Publications (Working Papers) 25418, Inter-American Development Bank.
  9. James J. Heckman, 1989. "Choosing Among Alternative Nonexperimental Methods for Estimating the Impact of Social Programs: The Case of Manpower Training," NBER Working Papers 2861, National Bureau of Economic Research, Inc.
  10. Jacobi, Lena & Kluve, Jochen, 2007. "Before and after the Hartz reforms: The performance of active labour market policy in Germany," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 40(1), pages 45-64.
  11. Kosuke Imai & Gary King & Elizabeth A. Stuart, 2008. "Misunderstandings between experimentalists and observationalists about causal inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(2), pages 481-502.
  12. Conny Wunsch, 2005. "Labour Market Policy in Germany: Institutions, Instruments and Reforms since Unification," University of St. Gallen Department of Economics working paper series 2005 2005-06, Department of Economics, University of St. Gallen.
  13. Ulf Rinne & Marc Schneider & Arne Uhlendorff, 2011. "Do the skilled and prime-aged unemployed benefit more from training? Effect heterogeneity of public training programmes in Germany," Applied Economics, Taylor & Francis Journals, vol. 43(25), pages 3465-3494.
  14. 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.
  15. repec:iab:iabzaf:v:40:i:1:p:45-64 is not listed on IDEAS
  16. 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.
  17. Ulf Rinne & Marc Schneider & Arne Uhlendorff, 2007. "Too Bad to Benefit?: Effect Heterogeneity of Public Training Programs," Discussion Papers of DIW Berlin 749, DIW Berlin, German Institute for Economic Research.
  18. Gerfin, Michael & Lechner, Michael, 2001. "A Microeconometric Evaluation of Active Labour Market Policy in Switzerland," CEPR Discussion Papers 2993, C.E.P.R. Discussion Papers.
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