IDEAS home Printed from https://ideas.repec.org/p/hhs/ifauwp/2015_005.html
   My bibliography  Save this paper

Evaluation of sequences of treatments with application to active labor market policies

Author

Listed:
  • Vikström, Johan

    (IFAU - Institute for Evaluation of Labour Market and Education Policy)

Abstract

This paper proposes a new framework for analyzing the effects of sequences of treatments with duration outcomes. Applications include sequences of active labor market policies assigned at specific unemployment durations and sequences of medical treatments. We consider evaluation under unconfoundedness and propose conditions under which the survival time under a specific treatment regime can be identified. We introduce inverse probability weighting estimators for various average effects. The finite sample properties of the estimators are investigated in a simulation study. The new estimator is applied to Swedish data on participants in training, in a work practice program and in subsidized employment. One result is that enrolling an unemployed person twice in the same program or in two different programs one after the other leads to longer unemployment spells compared to only participating in a single program once.

Suggested Citation

  • Vikström, Johan, 2015. "Evaluation of sequences of treatments with application to active labor market policies," Working Paper Series 2015:5, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    • Handle: RePEc:hhs:ifauwp:2015_005
    as

    Download full text from publisher

    File URL: http://www.ifau.se/Upload/pdf/se/2015/wp-2015-05-Evaluation-of-sequences-of-treatments-with-application-to-active-labor-market-policies.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Richard K. Crump & V. Joseph Hotz & Guido W. Imbens & Oscar A. Mitnik, 2009. "Dealing with limited overlap in estimation of average treatment effects," Biometrika, Biometrika Trust, vol. 96(1), pages 187-199.
    2. 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.
    3. Martin Biewen & Bernd Fitzenberger & Aderonke Osikominu & Marie Paul, 2014. "The Effectiveness of Public-Sponsored Training Revisited: The Importance of Data and Methodological Choices," Journal of Labor Economics, University of Chicago Press, vol. 32(4), pages 837-897.
    4. Van den Berg, Gerard J., 2001. "Duration models: specification, identification and multiple durations," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 55, pages 3381-3460, Elsevier.
    5. 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.
    6. 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.
    7. László Mátyás & Patrick Sevestre (ed.), 2008. "The Econometrics of Panel Data," Advanced Studies in Theoretical and Applied Econometrics, Springer, number 978-3-540-75892-1, July-Dece.
    8. Lechner, Michael, 2009. "Sequential Causal Models for the Evaluation of Labor Market Programs," Journal of Business & Economic Statistics, American Statistical Association, vol. 27, pages 71-83.
    9. James J. Heckman & Jeffrey A. Smith, 1999. "The Pre-Program Earnings Dip and the Determinants of Participation in a Social Program: Implications for Simple Program Evaluation Strategies," NBER Working Papers 6983, National Bureau of Economic Research, Inc.
    10. Hernan M. A & Brumback B. & Robins J. M, 2001. "Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 440-448, June.
    11. Heckman, James J & Smith, Jeffrey A, 1999. "The Pre-programme Earnings Dip and the Determinants of Participation in a Social Programme. Implications for Simple Programme Evaluation Strategies," Economic Journal, Royal Economic Society, vol. 109(457), pages 313-348, July.
    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. 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.
    2. Hugo Bodory & Martin Huber & Lukáš Lafférs, 2022. "Evaluating (weighted) dynamic treatment effects by double machine learning [Identification of causal effects using instrumental variables]," The Econometrics Journal, Royal Economic Society, vol. 25(3), pages 628-648.
    3. 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.
    4. Martin Huber & Michael Lechner & Anthony Strittmatter, 2018. "Direct and indirect effects of training vouchers for the unemployed," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(2), pages 441-463, February.
    5. Cerqua, Augusto & Urwin, Peter & Thomson, Dave & Bibby, David, 2020. "Evaluation of education and training impacts for the unemployed: Challenges of new data," Labour Economics, Elsevier, vol. 67(C).
    6. Hagen, Tobias, 2016. "Econometric Evaluation of a Placement Coaching Program for Recipients of Disability Insurance Benefits in Switzerland," VfS Annual Conference 2016 (Augsburg): Demographic Change 145736, Verein für Socialpolitik / German Economic Association.
    7. Hagen, Tobias, 2016. "Econometric evaluation of a placement coaching program for recipients of disability insurance benefits in Switzerland," Working Paper Series 10, Frankfurt University of Applied Sciences, Faculty of Business and Law.
    8. Lombardi, Stefano & van den Berg, Gerard J. & Vikström, Johan, 2020. "Empirical Monte Carlo evidence on estimation of Timing-of-Events models," Working Paper Series 2020:26, IFAU - Institute for Evaluation of Labour Market and Education Policy, revised 05 Jan 2021.
    9. Stenberg, Anders & Westerlund, Olle, 2016. "Flexibility at a cost – Should governments stimulate tertiary education for adults?," The Journal of the Economics of Ageing, Elsevier, vol. 7(C), pages 69-86.
    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. Michael Lechner & Anthony Strittmatter, 2019. "Practical procedures to deal with common support problems in matching estimation," Econometric Reviews, Taylor & Francis Journals, vol. 38(2), pages 193-207, February.
    12. 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.
    13. Pizer, William A. & Morgenstern, Richard & Shih, Jhih-Shyang, 2011. "The performance of industrial sector voluntary climate programs: Climate Wise and 1605(b)," Energy Policy, Elsevier, vol. 39(12), pages 7907-7916.
    14. J. van den Berg, Gerard & Kunaschk, Max & Lang, Julia & Stephan, Gesine & Uhlendorff, Arne, 2023. "Predicting re-employment: machine learning versus assessments by unemployed workers and by their caseworkers," Working Paper Series 2023:22, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    15. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    16. Doerr, Annabelle, 2022. "Vocational training for female job returners - Effects on employment, earnings and job quality," Labour Economics, Elsevier, vol. 75(C).
    17. Michael C. Knaus & Michael Lechner & Anthony Strittmatter, 2022. "Heterogeneous Employment Effects of Job Search Programs: A Machine Learning Approach," Journal of Human Resources, University of Wisconsin Press, vol. 57(2), pages 597-636.
    18. Kazuaki Okamura & Nizamul Islam, 2021. "Effects of the timing of childbirth on female labor supply: an analysis using the sequential matching approach," Applied Economics, Taylor & Francis Journals, vol. 53(28), pages 3253-3266, June.
    19. Barbara Sianesi, 2014. "Dealing with randomisation bias in a social experiment: the case of ERA," IFS Working Papers W14/10, Institute for Fiscal Studies.
    20. Celeste K. Carruthers & Thomas Sanford, 2015. "Way Station or Launching Pad? Unpacking the Returns to Postsecondary Adult Education," Working Papers 2015-02, University of Tennessee, Department of Economics.

    More about this item

    Keywords

    Treatment effects; dynamic treatment assignment; dynamic selection; program evaluation; work practice; training; subsidized employment;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hhs:ifauwp:2015_005. 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: Ali Ghooloo (email available below). General contact details of provider: https://edirc.repec.org/data/ifagvse.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.