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Long-Run Effects of Dynamically Assigned Treatments: A New Methodology and an Evaluation of Training Effects on Earnings

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  • van den Berg, Gerard J.

    (University of Groningen)

  • Vikström, Johan

    (IFAU)

Abstract

We propose and implement a new method to estimate treatment effects in settings where individuals need to be in a certain state (e.g. unemployment) to be eligible for a treatment, treatments may commence at different points in time, and the outcome of interest is realized after the individual left the initial state. An example concerns the effect of training on earnings in subsequent employment. Any evaluation needs to take into account that some of those who are not trained at a certain time in unemployment will leave unemployment before training while others will be trained later. We are interested in effects of the treatment at a certain elapsed duration compared to "no treatment at any subsequent duration". We prove identification under unconfoundedness and propose inverse probability weighting estimators. A key feature is that weights given to outcome observations of non-treated depend on the remaining time in the initial state. We study earnings effects of WIA training in the US and long-run effects of a training program for unemployed workers in Sweden. Estimates are positive and sizeable, exceeding those obtained by using common static methods, and suggesting a reappraisal of training.

Suggested Citation

  • van den Berg, Gerard J. & Vikström, Johan, 2019. "Long-Run Effects of Dynamically Assigned Treatments: A New Methodology and an Evaluation of Training Effects on Earnings," IZA Discussion Papers 12470, IZA Network @ LISER.
    • Handle: RePEc:iza:izadps:dp12470
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    References listed on IDEAS

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    1. Lechner, Michael & Wunsch, Conny, 2013. "Sensitivity of matching-based program evaluations to the availability of control variables," Labour Economics, Elsevier, vol. 21(C), pages 111-121.
    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. Katarina Richardson & Gerard J. Berg, 2013. "Duration Dependence Versus Unobserved Heterogeneity In Treatment Effects: Swedish Labor Market Training And The Transition Rate To Employment," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 28(2), pages 325-351, March.
    4. Carolyn Heinrich & Peter Mueser & Kenneth Troske & Kyung-Seong Jeon & Daver Kahvecioglu, 2013. "Do Public Employment and Training Programs Work?," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-23, December.
    5. Regner, Hakan, 2002. "A nonexperimental evaluation of training programs for the unemployed in Sweden," Labour Economics, Elsevier, vol. 9(2), pages 187-206, April.
    6. Matias Busso & John DiNardo & Justin McCrary, 2014. "New Evidence on the Finite Sample Properties of Propensity Score Reweighting and Matching Estimators," The Review of Economics and Statistics, MIT Press, vol. 96(5), pages 885-897, December.
    7. Muller, Paul & van der Klaauw, Bas & Heyma, Arjan, 2017. "Comparing Econometric Methods to Empirically Evaluate Job-Search Assistance," Working Papers in Economics 691, University of Gothenburg, Department of Economics.
    8. Bruno Crépon & Marc Ferracci & Grégory Jolivet & Gerard J. van den Berg, 2009. "Active Labor Market Policy Effects in a Dynamic Setting," Journal of the European Economic Association, MIT Press, vol. 7(2-3), pages 595-605, 04-05.
    9. Conny Wunsch & Michael Lechner, 2008. "What Did All the Money Do? On the General Ineffectiveness of Recent West German Labour Market Programmes," Kyklos, Wiley Blackwell, vol. 61(1), pages 134-174, February.
    10. Ham, John C & LaLonde, Robert J, 1996. "The Effect of Sample Selection and Initial Conditions in Duration Models: Evidence from Experimental Data on Training," Econometrica, Econometric Society, vol. 64(1), pages 175-205, January.
    11. Carling, Kenneth & Richardson, Katarina, 2001. "The relative efficiency of labor market programs: Swedish experience from the 1990's," Working Paper Series 2001:2, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    12. David S. Lee, 2009. "Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 76(3), pages 1071-1102.
    13. Michael Lechner, 2002. "Some practical issues in the evaluation of heterogeneous labour market programmes by matching methods," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 165(1), pages 59-82, February.
    14. Caliendo, Marco & Mahlstedt, Robert & Mitnik, Oscar A., 2017. "Unobservable, but unimportant? The relevance of usually unobserved variables for the evaluation of labor market policies," Labour Economics, Elsevier, vol. 46(C), pages 14-25.
    15. Lechner, Michael, 1999. "Earnings and Employment Effects of Continuous Off-the-Job Training in East Germany after Unification," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(1), pages 74-90, January.
    16. Huber, Martin & Lechner, Michael & Wunsch, Conny, 2013. "The performance of estimators based on the propensity score," Journal of Econometrics, Elsevier, vol. 175(1), pages 1-21.
    17. Fredrik Andersson & Harry J. Holzer & Julia I. Lane & David Rosenblum & Jeffrey Smith, 2024. "Does Federally Funded Job Training Work? Nonexperimental Estimates of WIA Training Impacts Using Longitudinal Data on Workers and Firms," Journal of Human Resources, University of Wisconsin Press, vol. 59(4), pages 1244-1283.
    18. James J. Heckman & Hidehiko Ichimura & Petra Todd, 1998. "Matching As An Econometric Evaluation Estimator," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(2), pages 261-294.
    19. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
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    Cited by:

    1. Cockx, Bart & Lechner, Michael & Bollens, Joost, 2023. "Priority to unemployed immigrants? A causal machine learning evaluation of training in Belgium," Labour Economics, Elsevier, vol. 80(C).
    2. Marco Caliendo & Robert Mahlstedt & Gerard J. van den Berg & Johan Vikström, 2023. "Side effects of labor market policies," Scandinavian Journal of Economics, Wiley Blackwell, vol. 125(2), pages 339-375, April.
    3. Doerr, Annabelle, 2022. "Vocational Training for Female Job Returners - Effects on Employment, Earnings and Job Quality," Working papers 2022/02, Faculty of Business and Economics - University of Basel.
    4. Anže Burger & Jochen Kluve & Milan Vodopivec & Matija Vodopivec, 2022. "A comprehensive impact evaluation of active labour market programmes in Slovenia," Empirical Economics, Springer, vol. 62(6), pages 3015-3039, June.
    5. Doerr, Annabelle, 2022. "Vocational training for female job returners - Effects on employment, earnings and job quality," Labour Economics, Elsevier, vol. 75(C).

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    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • J3 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs

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