IDEAS home Printed from https://ideas.repec.org/a/wly/emetrp/v90y2022i3p1337-1354.html
   My bibliography  Save this article

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

Author

Listed:
  • Gerard J. van den Berg
  • Johan Vikström

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 nontreated depend on the remaining time in the initial state. We study effects of a training program for unemployed workers in Sweden. Estimates are positive and sizeable, exceeding those obtained with common static methods. This calls for a reappraisal of training as a tool to bring unemployed back to work.

Suggested Citation

  • Gerard J. van den Berg & Johan Vikström, 2022. "Long‐Run Effects of Dynamically Assigned Treatments: A New Methodology and an Evaluation of Training Effects on Earnings," Econometrica, Econometric Society, vol. 90(3), pages 1337-1354, May.
    • Handle: RePEc:wly:emetrp:v:90:y:2022:i:3:p:1337-1354
    DOI: 10.3982/ECTA17522
    as

    Download full text from publisher

    File URL: https://doi.org/10.3982/ECTA17522
    Download Restriction: no
    File URL: https://libkey.io/10.3982/ECTA17522?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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, 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.
    3. 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.
    4. 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.
    5. 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.
    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. Michael Lechner, 1999. "Nonparametric bounds on employment and income effects of continuous vocational training in East Germany," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 1-28.
    8. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Canzian, Giulia & Meroni, Elena Claudia & Santangelo, Giulia, 2023. "Evaluation of a Flemish Active Labour Market Policy in the framework of the European Social Fund. Results and challenges," Socio-Economic Planning Sciences, Elsevier, vol. 88(C).
    3. Humlum, Anders & Munch, Jakob R. & Rasmussen, Mette, 2023. "What Works for the Unemployed? Evidence from Quasi-Random Caseworker Assignments," IZA Discussion Papers 16033, Institute of Labor Economics (IZA).

    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. 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, Institute of Labor Economics (IZA).
    2. 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.
    3. Dettmann, E. & Becker, C. & Schmeißer, C., 2011. "Distance functions for matching in small samples," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1942-1960, May.
    4. 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.
    5. Katharina Dengler, 2019. "Effectiveness of sequences of classroom training for welfare recipients: what works best in West Germany?," Applied Economics, Taylor & Francis Journals, vol. 51(1), pages 1-46, January.
    6. 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).
    7. 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.
    8. 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.
    9. Doerr, Annabelle, 2022. "Vocational training for female job returners - Effects on employment, earnings and job quality," Labour Economics, Elsevier, vol. 75(C).
    10. 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.
    11. 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.
    12. Lechner, Michael & Sari, Nazmi, 2015. "Labor market effects of sports and exercise: Evidence from Canadian panel data," Labour Economics, Elsevier, vol. 35(C), pages 1-15.
    13. Hämäläinen, Kari & Ollikainen, Virve, 2004. "Differential Effects of Active Labour Market Programmes in the Early Stages of Young People's Unemployment," Research Reports 115, VATT Institute for Economic Research.
    14. Dettmann, Eva & Becker, Claudia & Schmeißer, Christian, 2010. "Is there a Superior Distance Function for Matching in Small Samples?," IWH Discussion Papers 3/2010, Halle Institute for Economic Research (IWH).
    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. Biewen, Martin & Fitzenberger, Bernd & Osikominu, Aderonke & Waller, Marie, 2007. "Which Program for Whom? Evidence on the Comparative Effectiveness of Public Sponsored Training Programs in Germany," ZEW Discussion Papers 07-042, ZEW - Leibniz Centre for European Economic Research.
    17. Stefanie Behncke, 2009. "How Does Retirement Affect Health?," University of St. Gallen Department of Economics working paper series 2009 2009-13, Department of Economics, University of St. Gallen.
    18. Marloes Lammers & Lucy Kok, 2021. "Are active labor market policies (cost-)effective in the long run? Evidence from the Netherlands," Empirical Economics, Springer, vol. 60(4), pages 1719-1746, April.
    19. Jespersen, Svend T. & Munch, Jakob R. & Skipper, Lars, 2008. "Costs and benefits of Danish active labour market programmes," Labour Economics, Elsevier, vol. 15(5), pages 859-884, October.
    20. 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.

    More about this item

    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:wly:emetrp:v:90:y:2022:i:3:p:1337-1354. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/essssea.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.