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Generalized Propensity Scores for Multiple Continuous Treatment Variables

Author

Listed:
  • Peter Egger
  • Maximilian Von Ehrlich

Abstract

This paper illustrates that the generalized propensity score method can easily be applied with multiple continuous endogenous treatment variables. Consistency proofs carry over straightforwardly to this general case, and the approach is shown to work well in finite samples with various data-generating processes and up to five continuous endogenous treatment variables.

Suggested Citation

  • Peter Egger & Maximilian Von Ehrlich, 2013. "Generalized Propensity Scores for Multiple Continuous Treatment Variables," CESifo Working Paper Series 4074, CESifo Group Munich.
  • Handle: RePEc:ces:ceswps:_4074
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    File URL: http://www.cesifo-group.de/DocDL/cesifo1_wp4074.pdf
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    References listed on IDEAS

    as
    1. Kosuke Imai & David A. van Dyk, 2004. "Causal Inference With General Treatment Regimes: Generalizing the Propensity Score," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 854-866, January.
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    Cited by:

    1. Jessie Bakens & Raymond Florax & Henri (H.L.F.) de Groot & Peter Mulder, 2018. "Living Apart Together: The Economic Value of Ethnic Diversity in Cities," Tinbergen Institute Discussion Papers 18-029/VIII, Tinbergen Institute.
    2. Per G. Fredriksson & Jim R. Wollscheid, 2014. "Political Institutions, Political Careers and Environmental Policy," Kyklos, Wiley Blackwell, vol. 67(1), pages 54-73, February.
    3. Egger, Peter Hannes & Egger, Peter, 2016. "Heterogeneous Effects of Tariff and Nontariff Policy Barriers in General Equilibrium," Annual Conference 2016 (Augsburg): Demographic Change 145675, Verein für Socialpolitik / German Economic Association.

    More about this item

    Keywords

    generalized propensity score estimation; multiple treatments; continuous endogenous treatments;

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

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