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Generalized Propensity Scores for Multiple Continuous Treatment Variables

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  • 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.
    • Handle: RePEc:ces:ceswps:_4074
    as

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    File URL: https://www.cesifo.org/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. Binkley, James K. & Young, Jeffrey S., 2022. "Deficient Dietary Behavior in Low-Income Americans: Assessing the Role of Diet Costs," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322055, Agricultural and Applied Economics Association.
    2. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    3. Egger, Peter H. & Ehrlich, Maximilian v. & Nelson, Douglas R., 2020. "The trade effects of skilled versus unskilled migration," Journal of Comparative Economics, Elsevier, vol. 48(2), pages 448-464.
    4. Sourafel Girma & Hibret Maemir, 2022. "Joint effects of exporting and outward FDI on firm‐level capital investment in India," Review of Development Economics, Wiley Blackwell, vol. 26(1), pages 606-624, February.
    5. Enrico Cristofoletti, 2021. "A Stata package for the estimation of the dose-response function when the treatment is multidimensional," DEM Working Papers 2021/07, Department of Economics and Management.
    6. Mulwa, Chalmers K. & Visser, Martine, 2020. "Farm diversification as an adaptation strategy to climatic shocks and implications for food security in northern Namibia," World Development, Elsevier, vol. 129(C).
    7. Per G. Fredriksson & Jim R. Wollscheid, 2014. "Political Institutions, Political Careers and Environmental Policy," Kyklos, Wiley Blackwell, vol. 67(1), pages 54-73, February.
    8. Jessie Bakens & Raymond JGM Florax & Henri LF de Groot & Peter Mulder, 2022. "Living apart together: The economic value of ethnic diversity in cities," Environment and Planning B, , vol. 49(8), pages 2267-2282, October.
    9. Egger, Peter Hannes & Egger, Peter, 2016. "Heterogeneous Effects of Tariff and Nontariff Policy Barriers in General Equilibrium," VfS Annual Conference 2016 (Augsburg): Demographic Change 145675, Verein für Socialpolitik / German Economic Association.
    10. Finn McGuire & Noemi Kreif & Peter C. Smith, 2021. "The effect of distance on maternal institutional delivery choice: Evidence from Malawi," Health Economics, John Wiley & Sons, Ltd., vol. 30(9), pages 2144-2167, September.

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    More about this item

    Keywords

    generalized propensity score estimation; multiple treatments; continuous endogenous treatments;
    All these keywords.

    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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