IDEAS home Printed from https://ideas.repec.org/p/ces/ceswps/_4074.html
   My bibliography  Save this paper

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

    Download full text from publisher

    File URL: https://www.cesifo.org/DocDL/cesifo1_wp4074.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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).
    3. 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.
    4. 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.
    5. Per G. Fredriksson & Jim R. Wollscheid, 2014. "Political Institutions, Political Careers and Environmental Policy," Kyklos, Wiley Blackwell, vol. 67(1), pages 54-73, February.
    6. 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.
    7. 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.
    8. Tadao Hoshino, 2021. "Estimating a Continuous Treatment Model with Spillovers: A Control Function Approach," Papers 2112.15114, arXiv.org, revised Jan 2023.
    9. 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.
    10. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    2. Pablo Ibarraran & Miguel Sarzosa & Yuri Suarez Dillon Soares, 2008. "The Welfare Impacts of Local Investment Projects: Evidence from the Guatemala FIS," OVE Working Papers 0208, Inter-American Development Bank, Office of Evaluation and Oversight (OVE).
    3. Jerzy Michalek & Pavel Ciaian & d’Artis Kancs, 2014. "Capitalization of the Single Payment Scheme into Land Value: Generalized Propensity Score Evidence from the European Union," Land Economics, University of Wisconsin Press, vol. 90(2), pages 260-289.
    4. Hilal Atasoy & Rajiv D. Banker & Paul A. Pavlou, 2016. "On the Longitudinal Effects of IT Use on Firm-Level Employment," Information Systems Research, INFORMS, vol. 27(1), pages 6-26, March.
    5. Tugba Akkaya Hocagil & Richard J. Cook & Sandra W. Jacobson & Joseph L. Jacobson & Louise M. Ryan, 2021. "Propensity score analysis for a semi‐continuous exposure variable: a study of gestational alcohol exposure and childhood cognition," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(4), pages 1390-1413, October.
    6. Becker, Sascha O. & Egger, Peter H. & von Ehrlich, Maximilian, 2012. "Too much of a good thing? On the growth effects of the EU's regional policy," European Economic Review, Elsevier, vol. 56(4), pages 648-668.
    7. Malcolm Keswell & Michael R. Carter, 2011. "Poverty and Land Distribution: Evidence from a Natural Experiment," WIDER Working Paper Series wp-2011-046, World Institute for Development Economic Research (UNU-WIDER).
    8. Yannis Yatracos, 2013. "Equal percent bias reduction and variance proportionate modifying properties with mean–covariance preserving matching," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 65(1), pages 69-87, February.
    9. W K Newey & S Stouli, 2022. "Heterogeneous coefficients, control variables and identification of multiple treatment effects [Multivalued treatments and decomposition analysis: An application to the WIA program]," Biometrika, Biometrika Trust, vol. 109(3), pages 865-872.
    10. Chunrong Ai & Oliver Linton & Kaiji Motegi & Zheng Zhang, 2021. "A unified framework for efficient estimation of general treatment models," Quantitative Economics, Econometric Society, vol. 12(3), pages 779-816, July.
    11. Ida D'Attoma & Silvia Pacei, 2018. "Evaluating the Effects of Product Innovation on the Performance of European Firms by Using the Generalised Propensity Score," German Economic Review, Verein für Socialpolitik, vol. 19(1), pages 94-112, February.
    12. Martin Huber & Yu‐Chin Hsu & Ying‐Ying Lee & Layal Lettry, 2020. "Direct and indirect effects of continuous treatments based on generalized propensity score weighting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(7), pages 814-840, November.
    13. Jun Du & Sourafel Girma, 2009. "The Effects of Foreign Acquisition on Domestic and Export Markets Dynamics in China," The World Economy, Wiley Blackwell, vol. 32(1), pages 164-177, January.
    14. Carina Steckenleiter & Michael Lechner & Tim Pawlowski & Ute Schüttoff, 2023. "Do local expenditures on sports facilities affect sports participation?," Economic Inquiry, Western Economic Association International, vol. 61(4), pages 1103-1128, October.
    15. 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.
    16. Michela Bia & Carlos A. Flores & Alfonso Flores-Lagunes & Alessandra Mattei, 2014. "A Stata package for the application of semiparametric estimators of dose–response functions," Stata Journal, StataCorp LP, vol. 14(3), pages 580-604, September.
    17. Steckenleiter, Carina & Lechner, Michael & Pawlowski, Tim & Schüttoff, Ute, 2019. "Do local public expenditures on sports facilities affect sports participation in Germany?," Economics Working Paper Series 1905, University of St. Gallen, School of Economics and Political Science.
    18. Flores, Carlos A. & Mitnik, Oscar A., 2009. "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data," IZA Discussion Papers 4451, Institute of Labor Economics (IZA).
    19. A. Giffin & B. J. Reich & S. Yang & A. G. Rappold, 2023. "Generalized propensity score approach to causal inference with spatial interference," Biometrics, The International Biometric Society, vol. 79(3), pages 2220-2231, September.
    20. Tan Trung Luong & Uthayasankar Sivarajah & Vishanth Weerakkody, 2021. "Do Agile Managed Information Systems Projects Fail Due to a Lack of Emotional Intelligence?," Information Systems Frontiers, Springer, vol. 23(2), pages 415-433, April.

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ces:ceswps:_4074. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Klaus Wohlrabe (email available below). General contact details of provider: https://edirc.repec.org/data/cesifde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.