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Identification of Dynamic Treatment Effects by Instrumental Variables

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  • Ruth Miquel

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Abstract

This paper considers the problem of the identification of causal effects using instrumental variables. We are interested in the effects of some treatments on certain outcomes. First, we consider that a participation in a treatment or a program is only possible one time but we have the choice between more than one program. Under a monotonicity condition and an exclusion restriction, pair-wise Local Average Treatment Effects are identifiable. Second, we consider the case where only one program is available but more than one participation is possible, leading to a comparison of sequences of participations (or sequences of programs). In this framework a problem of endogeneity appears: the outcome after one period, affected by the participation in this period, can influence the participation in the next period. Under different versions of the monotonicity condition and the exclusion restriction, identification of the causal effects of sequences of programs are investigated. The introduction of a second period implies a loss of identification for some effects of interest even without any endogeneity problem.

Suggested Citation

  • Ruth Miquel, 2002. "Identification of Dynamic Treatment Effects by Instrumental Variables," University of St. Gallen Department of Economics working paper series 2002 2002-11, Department of Economics, University of St. Gallen.
  • Handle: RePEc:usg:dp2002:2002-11
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    File URL: http://ux-tauri.unisg.ch/RePEc/usg/dp2002/dp0211miquel_ganz.pdf
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    References listed on IDEAS

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    1. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics,in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366 Elsevier.
    2. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    3. A. D. Roy, 1951. "Some Thoughts On The Distribution Of Earnings," Oxford Economic Papers, Oxford University Press, vol. 3(2), pages 135-146.
    4. Abadie A., 2002. "Bootstrap Tests for Distributional Treatment Effects in Instrumental Variable Models," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 284-292, March.
    5. James Heckman, 1997. "Instrumental Variables: A Study of Implicit Behavioral Assumptions Used in Making Program Evaluations," Journal of Human Resources, University of Wisconsin Press, vol. 32(3), pages 441-462.
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    Cited by:

    1. Weili Ding & Steven F. Lehrer, 2010. "Estimating Treatment Effects from Contaminated Multiperiod Education Experiments: The Dynamic Impacts of Class Size Reductions," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 31-42, February.
    2. repec:bla:jorssb:v:79:y:2017:i:5:p:1645-1666 is not listed on IDEAS
    3. Michael Lechner, 2011. "The Relation of Different Concepts of Causality Used in Time Series and Microeconometrics," Econometric Reviews, Taylor & Francis Journals, vol. 30(1), pages 109-127.
    4. Ruth Miquel, 2003. "Identification of Effects of Dynamic Treatments with a Difference-in-Differences Approach," University of St. Gallen Department of Economics working paper series 2003 2003-06, Department of Economics, University of St. Gallen.
    5. Huber, Martin & W├╝thrich, Kaspar, 2017. "Evaluating local average and quantile treatment effects under endogeneity based on instruments: a review," FSES Working Papers 479, Faculty of Economics and Social Sciences, University of Freiburg/Fribourg Switzerland.
    6. Steven Lehrer & Weili Ding, 2004. "Estimating Dynamic Treatment Effects from Project STAR," Econometric Society 2004 North American Summer Meetings 252, Econometric Society.

    More about this item

    Keywords

    Compliers; Local Average Treatment Effect; dynamic treatment regimes; nonparametric identification; instruments;

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

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