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Dynamic Econometric Program Evaluation

Author

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  • Abbring, Jaap H.

    (Tilburg University)

Abstract

H. Theil has made important contributions to the analysis of simultaneous-equations models. This paper gives an exposition of some closely related recent developments in microeconometrics, with a focus on efforts to develop robust methods for dynamic policy evaluation. We set the stage with a brief discussion of the static treatment-effect approach to program evaluation and non-parametric structural models. We then critically analyze the dynamic treatment-effects approach adopted from statistics. Finally, we review the eventhistory approach. We clarify some of the fundamental problems that arise in the analysis of such models by rephrasing a canonical version as a simultaneous-equations model.

Suggested Citation

  • Abbring, Jaap H., 2003. "Dynamic Econometric Program Evaluation," IZA Discussion Papers 804, Institute of Labor Economics (IZA).
    • Handle: RePEc:iza:izadps:dp804
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. 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.
    2. Jaap H. Abbring, 2006. "The Event-History Approach to Program Evaluation," Tinbergen Institute Discussion Papers 06-057/3, Tinbergen Institute, revised 29 Oct 2007.
    3. Mensah, Edouard R. & Filipski, Mateusz J., 2022. "Saving for a rainy day: the impact of natural disasters on savings rates," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322266, Agricultural and Applied Economics Association.
    4. Marie Albertine Djuikom, 2018. "Incentives to labour migration and agricultural productivity: The Bayesian perspective," WIDER Working Paper Series wp-2018-45, World Institute for Development Economic Research (UNU-WIDER).
    5. Stephen Kastoryano & Bas van der Klaauw, 2022. "Dynamic evaluation of job search assistance," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(2), pages 227-241, March.
    6. Lechner, Michael, 2013. "Treatment effects and panel data," Economics Working Paper Series 1314, University of St. Gallen, School of Economics and Political Science.
    7. Stephan Thomsen, 2009. "Job Search Assistance Programs in Europe: Evaluation Methods and Recent Empirical Findings," FEMM Working Papers 09018, Otto-von-Guericke University Magdeburg, Faculty of Economics and Management.
    8. Rhian M. Daniel & Bianca L. De Stavola & Simon N. Cousens, 2011. "gformula: Estimating causal effects in the presence of time-varying confounding or mediation using the g-computation formula," Stata Journal, StataCorp LP, vol. 11(4), pages 479-517, December.

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    More about this item

    Keywords

    dynamic policy evaluation; structural models; treatment effects; event-history analysis;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies

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