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Matching Estimating of Dynamic Treatment Models: Some Practical Issues

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  • Michael Lechner

Abstract

Lechner and Miquel (2001) approached the causal analysis of sequences of interventions from a potential outcome perspective based on selection on observable type of assumptions (sequential conditional independence assumptions). Lechner (2004) proposed matching estimators for this framework. However, many practical issues that might have substantial consequences for interpretation of the results have not been thoroughly investigated so far. This paper discusses some of these practical issues. The discussion is related to estimates based on an artificial data set for which the true values of the parameters are known and that shares many features of data that could be used for an empirical dynamic matching analysis.

Suggested Citation

  • Michael Lechner, 2006. "Matching Estimating of Dynamic Treatment Models: Some Practical Issues," University of St. Gallen Department of Economics working paper series 2006 2006-03, Department of Economics, University of St. Gallen.
    • Handle: RePEc:usg:dp2006:2006-03
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    Cited by:

    1. Cheng Hsiao & Yan Shen & Boqing Wang & Greg Weeks, 2013. "Evaluating the Impacts of Washington State Repeated Job Search Services on the Earnings of Prime-age," Working Papers 2013-10-14, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    2. Fali Huang & Myoung-Jae Lee, 2010. "Dynamic treatment effect analysis of TV effects on child cognitive development," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(3), pages 392-419.
    3. Stephan Gesine, 2008. "The Effects of Active Labor Market Programs in Germany: An Investigation Using Different Definitions of Non-Treatment," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(5-6), pages 586-611, October.
    4. repec:wyi:journl:002075 is not listed on IDEAS
    5. Dengler, Katharina, 2013. "Effectiveness of sequences of One-Euro-Jobs : is it better to do more One-Euro-Jobs or to wait?," IAB-Discussion Paper 201316, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    6. Michael Lechner, 2006. "The Relation of Different Concepts of Causality in Econometrics," University of St. Gallen Department of Economics working paper series 2006 2006-15, Department of Economics, University of St. Gallen.
    7. Wang‐Sheng Lee & Sandy Suardi, 2011. "Minimum Wages and Employment: Reconsidering the Use of a Time Series Approach as an Evaluation Tool," British Journal of Industrial Relations, London School of Economics, vol. 49(Supplemen), pages 376-401, July.
    8. 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.
    9. Michael Lechner & Stephan Wiehler, 2007. "Does the Order and Timing of Active Labor Market Programs Matter?," University of St. Gallen Department of Economics working paper series 2007 2007-38, Department of Economics, University of St. Gallen.
    10. Stefan Boes, 2009. "Partial Identification of Discrete Counterfactual Distributions with Sequential Update of Information," SOI - Working Papers 0918, Socioeconomic Institute - University of Zurich.

    More about this item

    Keywords

    Dynamic treatment regimes; nonparametric identification; causal effects; sequential randomisation; programme evaluation; treatment effects; dynamic matching; panel data;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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