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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.
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    4. 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.
    5. 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.
    6. 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.
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    17. Hsiao,Cheng & Morimune,Kimio & Powell,James L. (ed.), 2001. "Nonlinear Statistical Modeling," Cambridge Books, Cambridge University Press, number 9780521662468, September.
    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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