Evaluating Continuous Training Programs Using the Generalized Propensity Score
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.Download Info
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Paper provided by DIW Berlin, German Institute for Economic Research in its series Discussion Papers of DIW Berlin with number 752.Length: 44 p.
Date of creation: 2007
Date of revision:
Publication status: published in: Journal of the Royal Statistical Society Series A 175 (2012) Part 2, 587-617
Handle: RePEc:diw:diwwpp:dp752
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Related research
Keywords: Training; program evaluation; continuous treatment; generalized propensity score;Other versions of this item:
- 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.
- 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).
- 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, and Vacancies - - - Public Policy
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-01-05 (All new papers)
References
References listed on IDEASPlease report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.Cited by:
- Kluve, Jochen & Lehmann, Hartmut & Schmidt, Christoph M., 2008.
"Disentangling Treatment Effects of Active Labor Market Policies: The Role of Labor Force Status Sequences,"
Labour Economics,
Elsevier, vol. 15(6), pages 1270-1295, December.
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"SPS Capitalization into Land Value: Generalized Propensity Score Evidence from the EU,"
Open Access publications from Katholieke Universiteit Leuven
urn:hdl:123456789/319541, Katholieke Universiteit Leuven.
- Pavel Ciaian & d'Artis Kancs & Jerzy Michalek, 2011. "SPS Capitalization into Land Value : Generalized Propensity Score Evidence from the EU," LICOS Discussion Papers 29311, LICOS - Centre for Institutions and Economic Performance, KU Leuven.
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- Carlos A. Flores & Oscar A. Mitnik, 2009.
"Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data,"
Working Papers
2010-9, University of Miami, Department of Economics.
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