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Estimating Person-Centered Treatment (PeT) Effects Using Instrumental Variables

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  • Anirban Basu

Abstract

This paper builds on the methods of local instrumental variables developed by Heckman and Vytlacil (1999, 2001, 2005) to estimate person-centered treatment (PeT) effects that are conditioned on the person's observed characteristics and averaged over the potential conditional distribution of unobserved characteristics that lead them to their observed treatment choices. PeT effects are more individualized than conditional treatment effects from a randomized setting with the same observed characteristics. PeT effects can be easily aggregated to construct any of the mean treatment effect parameters and, more importantly, are well-suited to comprehend individual-level treatment effect heterogeneity. The paper presents the theory behind PeT effects, studies their finite-sample properties using simulations and presents a novel analysis of treatment evaluation in health care.

Suggested Citation

  • Anirban Basu, 2012. "Estimating Person-Centered Treatment (PeT) Effects Using Instrumental Variables," NBER Working Papers 18056, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:18056
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    References listed on IDEAS

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    1. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    2. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, May.
    3. Heckman, James, 2001. "Accounting for Heterogeneity, Diversity and General Equilibrium in Evaluating Social Programmes," Economic Journal, Royal Economic Society, vol. 111(475), pages 654-699, November.
    4. James J. Heckman & Jeffrey Smith & Nancy Clements, 1997. "Making The Most Out Of Programme Evaluations and Social Experiments: Accounting For Heterogeneity in Programme Impacts," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 487-535.
    5. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-1149, September.
    6. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, vol. 27(3), pages 531-543, May.
    7. James J. Heckman & Sergio Urzua & Edward Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 389-432, August.
    8. Andrew M. Jones (ed.), 2006. "The Elgar Companion to Health Economics," Books, Edward Elgar Publishing, number 3572.
    9. Basu, Anirban, 2011. "Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care," Journal of Health Economics, Elsevier, vol. 30(3), pages 549-559, May.
    10. Carneiro, Pedro & Lee, Sokbae, 2009. "Estimating distributions of potential outcomes using local instrumental variables with an application to changes in college enrollment and wage inequality," Journal of Econometrics, Elsevier, vol. 149(2), pages 191-208, April.
    11. Anirban Basu, 2009. "Individualization at the Heart of Comparative Effectiveness Research: The Time for i-CER Has Come," Medical Decision Making, , vol. 29(6), pages 9-11, November.
    12. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: An application in breast cancer patients," Health, Econometrics and Data Group (HEDG) Working Papers 07/07, HEDG, c/o Department of Economics, University of York.
    13. Amitabh Chandra & Douglas O. Staiger, 2007. "Productivity Spillovers in Health Care: Evidence from the Treatment of Heart Attacks," Journal of Political Economy, University of Chicago Press, vol. 115(1), pages 103-140.
    14. Meltzer, D. & Egleston, B. & Abdalla, I., 2001. "Patterns of prostate cancer treatment by clinical stage and age," American Journal of Public Health, American Public Health Association, vol. 91(1), pages 126-128.
    15. Garber, Alan M. & Phelps, Charles E., 1997. "Economic foundations of cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 16(1), pages 1-31, February.
    16. Hsiao,Cheng & Morimune,Kimio & Powell,James L. (ed.), 2001. "Nonlinear Statistical Modeling," Cambridge Books, Cambridge University Press, number 9780521662468.
    17. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    18. Anirban Basu & James J. Heckman & Salvador Navarro-Lozano & Sergio Urzua, 2007. "Use of instrumental variables in the presence of heterogeneity and self-selection: an application to treatments of breast cancer patients," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1133-1157.
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    Cited by:

    1. Basu Anirban, 2013. "Personalized Medicine in the Context of Comparative Effectiveness Research," Forum for Health Economics & Policy, De Gruyter, vol. 16(2), pages 73-86, June.

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • D04 - Microeconomics - - General - - - Microeconomic Policy: Formulation; Implementation; Evaluation
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior

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