IDEAS home Printed from https://ideas.repec.org/p/iza/izadps/dp3255.html
   My bibliography  Save this paper

Evaluating Continuous Training Programs Using the Generalized Propensity Score

Author

Listed:
  • Kluve, Jochen

    (KfW Development Bank)

  • Schneider, Hilmar

    (University of Luxembourg)

  • Uhlendorff, Arne

    (CREST)

  • Zhao, Zhong

    (Renmin University of China)

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.

Suggested Citation

  • Kluve, Jochen & Schneider, Hilmar & Uhlendorff, Arne & Zhao, Zhong, 2007. "Evaluating Continuous Training Programs Using the Generalized Propensity Score," IZA Discussion Papers 3255, Institute of Labor Economics (IZA).
  • Handle: RePEc:iza:izadps:dp3255
    as

    Download full text from publisher

    File URL: https://docs.iza.org/dp3255.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Schneider, Hilmar & Uhlendorff, Arne, 2006. "Die Wirkung der Hartz-Reform im Bereich der beruflichen Weiterbildung (The effect of the Hartz reform in the field of further vocational training)," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 39(3/4), pages 477-490.
    2. Michael Lechner & Ruth Miquel & Conny Wunsch, 2011. "Long‐Run Effects Of Public Sector Sponsored Training In West Germany," Journal of the European Economic Association, European Economic Association, vol. 9(4), pages 742-784, August.
    3. Lechner, Michael, 1999. "Identification and Estimation of Causal Effects of Multiple Treatments Under the Conditional Independence Assumption," IZA Discussion Papers 91, Institute of Labor Economics (IZA).
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Schneider, Hilmar & Uhlendorff, Arne, 2006. "Die Wirkung der Hartz-Reform im Bereich der beruflichen Weiterbildung," IZA Discussion Papers 2255, Institute of Labor Economics (IZA).
    12. 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 of Labor Economics (IZA).
    13. Alfonso Flores-Lagunes & Arturo Gonzalez & Todd C. Neumann, 2007. "Estimating the Effects of Length of Exposure to a Training Program: The Case of Job Corps," Working Papers 1042, Princeton University, Department of Economics, Industrial Relations Section..
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kluve, Jochen & Schneider, Hilmar & Uhlendorff, Arne & Zhao, Zhong, 2012. "Evaluating continuous training programmes by using the generalized propensity score," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 175(2), pages 587-617.
    2. Jochen Kluve & Hilmar Schneider & Arne Uhlendorff & Zhong Zhao, 2007. "Evaluating Continuous Training Programs Using the Generalized Propensity Score," Ruhr Economic Papers 0035, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    3. repec:zbw:rwirep:0035 is not listed on IDEAS
    4. Michael Lechner & Ruth Miquel, 2010. "Identification of the effects of dynamic treatments by sequential conditional independence assumptions," Empirical Economics, Springer, vol. 39(1), pages 111-137, August.
    5. 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 of Labor Economics (IZA).
    6. Michael Lechner & Stephan Wiehler, 2013. "Does the Order and Timing of Active Labour Market Programmes Matter?," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 75(2), pages 180-212, April.
    7. Frölich, Markus & Lechner, Michael, 2010. "Exploiting Regional Treatment Intensity for the Evaluation of Labor Market Policies," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1014-1029.
    8. Lechner, Michael & Wiehler, Stephan, 2007. "Does the Order and Timing of Active Labor Market Programs Matter?," IZA Discussion Papers 3092, Institute of Labor Economics (IZA).
    9. Alfonso Flores-Lagunes & Arturo Gonzalez & Todd C. Neumann, 2007. "Estimating the Effects of Length of Exposure to a Training Program: The Case of Job Corps," Working Papers 1042, Princeton University, Department of Economics, Industrial Relations Section..
    10. Lechner Michael & Miquel Ruth & Wunsch Conny, 2007. "The Curse and Blessing of Training the Unemployed in a Changing Economy: The Case of East Germany After Unification," German Economic Review, De Gruyter, vol. 8(4), pages 468-509, December.
    11. Stefanie Behncke & Markus Frölich & Michael Lechner, 2010. "Unemployed and their caseworkers: should they be friends or foes?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 67-92, January.
    12. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    13. Behncke, Stefanie & Frölich, Markus & Lechner, Michael, 2008. "A Caseworker Like Me: Does the Similarity between Unemployed and Caseworker Increase Job Placements?," IZA Discussion Papers 3437, Institute of Labor Economics (IZA).
    14. Martin Huber & Michael Lechner & Conny Wunsch, 2011. "Does leaving welfare improve health? Evidence for Germany," Health Economics, John Wiley & Sons, Ltd., vol. 20(4), pages 484-504, April.
    15. Carlos A. Flores & Oscar A. Mitnik, 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," Working Papers 2010-10, University of Miami, Department of Economics.
    16. Lechner, Michael, 2008. "Long-Run Labour Market Effects of Individual Sports Activities," IZA Discussion Papers 3559, Institute of Labor Economics (IZA).
    17. Lechner, Michael, 2009. "Long-run labour market and health effects of individual sports activities," Journal of Health Economics, Elsevier, vol. 28(4), pages 839-854, July.
    18. Conny Wunsch, 2007. "Optimal Use of Labour Market Policies," University of St. Gallen Department of Economics working paper series 2007 2007-26, Department of Economics, University of St. Gallen.
    19. Michael Lechner & Ruth Miquel & Conny Wunsch, 2011. "Long‐Run Effects Of Public Sector Sponsored Training In West Germany," Journal of the European Economic Association, European Economic Association, vol. 9(4), pages 742-784, August.
    20. Stephan, Gesine & Rässler, Susanne & Schewe, Torben, 2006. "Das TrEffeR-Projekt der Bundesagentur für Arbeit : die Wirkung von Maßnahmen aktiver Arbeitsmarktpolitik (The TrEffeR project of the Federal Employment Agency : the effect of active labour market poli," Zeitschrift für ArbeitsmarktForschung - Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 39(3/4), pages 447-465.
    21. Richard Blundell & Lorraine Dearden & Barbara Sianesi, 2003. "Evaluating the impact of education on earnings in the UK: Models, methods and results from the NCDS," IFS Working Papers W03/20, Institute for Fiscal Studies.

    More about this item

    Keywords

    program evaluation; continuous treatment; generalized propensity score; training;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • J68 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Public Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:iza:izadps:dp3255. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Holger Hinte (email available below). General contact details of provider: https://edirc.repec.org/data/izaaade.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.