This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Use of instrumental variables in the presence of heterogeneity and self-selection: An application in breast cancer patients

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Anirban Basu
James J. Heckman
Salvador Navarro-Lozano
Sergio Urzua

Additional information is available for the following registered author(s):

Abstract

Instrumental variables methods (IV) are widely used in the health economics literature to adjust for hidden selection biases in observational studies when estimating treatment effects. Less attention has been paid in the applied literature to the proper use of instrumental variables if treatment effects are heterogeneous across subjects and individuals select treatments based on expected idiosyncratic gains or losses from treatments. In this paper, we analyze the role of conventional instrumental variable analysis and alternative approaches using instrumental variables for estimating treatment effects for models with treatment heterogeneity and self-selection. Instead of interpreting IV estimates as the effect of treatment at an unknown margin of patients, we identify the marginal patients and we apply the method of local instrumental variables to estimate the Average Treatment Effect (ATE) and the Effect on the Treated (TT) on 5-year direct costs of breast conserving surgery and radiation therapy compared to mastectomy in breast cancer patients. We use a sample from the Outcomes and Preferences in Older Women, Nationwide Survey (OPTIONS) which is designed to be representative of all female Medicare beneficiaries (aged 67 or older) with newly diagnosed breast cancer between 1992 and 1994. Our results reveal some of the advantages and limitations of conventional and alternative IV methods in estimating mean treatment effect parameters.

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://www.york.ac.uk/res/herc/documents/wp/07_07.pdf
File Format: application/pdf
File Function: Main text
Download Restriction: no

Publisher Info
Paper provided by HEDG, c/o Department of Economics, University of York in its series Health, Econometrics and Data Group (HEDG) Working Papers with number 07/07.

Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Length:
Date of creation: Jun 2007
Date of revision:
Handle: RePEc:yor:hectdg:07/07

Contact details of provider:
Postal: HEDG/HERC, Department of Economics and Related Studies, University of York, York, YO10 5DD, United Kingdom
Phone: (0)1904 433776
Fax: (0)1904 433759
Email:
Web page: http://www.york.ac.uk/res/herc/research/hedg/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (David Hobbs).

Related research
Keywords: Self-selection; essential heterogeneity; instrumental variables; breast cancer; local instrumental variable method.;

Other versions of this item:

Find related papers by JEL classification:
C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models

This paper has been announced in the following NEP Reports:

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. James J. Heckman & Sergio Urzua & Edward J. Vytlacil, 2006. "Understanding Instrumental Variables in Models with Essential Heterogeneity," NBER Working Papers 12574, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  2. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    Other versions:
  3. James J. Heckman & Edward Vytlacil, 2001. "Policy-Relevant Treatment Effects," American Economic Review, American Economic Association, vol. 91(2), pages 107-111, May. [Downloadable!] (restricted)
  4. Jack Hadley & Daniel Polsky & Jeanne S. Mandelblatt & Jean M. Mitchell & Jane C. Weeks & Qin Wang & Yi-Ting Hwang, 2003. "An exploratory instrumental variable analysis of the outcomes of localized breast cancer treatments in a medicare population," Health Economics, John Wiley & Sons, Ltd., vol. 12(3), pages 171-186. [Downloadable!]
  5. Angrist, Joshua D. & Krueger, Alan B., 1999. "Empirical strategies in labor economics," Handbook of Labor Economics, in: O. Ashenfelter & D. Card (ed.), Handbook of Labor Economics, edition 1, volume 3, chapter 23, pages 1277-1366 Elsevier. [Downloadable!] (restricted)
    Other versions:
  6. Gary Chamberlain & Guido Imbens, 2004. "Random Effects Estimators with many Instrumental Variables," Econometrica, Econometric Society, vol. 72(1), pages 295-306, 01. [Downloadable!] (restricted)
  7. James J. Heckman & Edward Vytlacil, 2005. "Structural Equations, Treatment Effects, and Econometric Policy Evaluation," Econometrica, Econometric Society, vol. 73(3), pages 669-738, 05. [Downloadable!] (restricted)
    Other versions:
  8. James J. Heckman & Edward J. Vytlacil, 2000. "Local Instrumental Variables," NBER Technical Working Papers 0252, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  9. Anirban Basu & Willard G. Manning & John Mullahy, 2004. "Comparing alternative models: log vs Cox proportional hazard?," Health Economics, John Wiley & Sons, Ltd., vol. 13(8), pages 749-765. [Downloadable!]
  10. LaLonde, Robert J, 1986. "Evaluating the Econometric Evaluations of Training Programs with Experimental Data," American Economic Review, American Economic Association, vol. 76(4), pages 604-20, September. [Downloadable!] (restricted)
  11. Bjorklund, Anders & Moffitt, Robert, 1987. "The Estimation of Wage Gains and Welfare Gains in Self-selection," The Review of Economics and Statistics, MIT Press, vol. 69(1), pages 42-49, February. [Downloadable!] (restricted)
  12. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-59, July. [Downloadable!] (restricted)
    Other versions:
  13. Heckman, James J & Honore, Bo E, 1990. "The Empirical Content of the Roy Model," Econometrica, Econometric Society, vol. 58(5), pages 1121-49, September. [Downloadable!] (restricted)
  14. Heckman, James J. & Vytlacil, Edward J., 2000. "The relationship between treatment parameters within a latent variable framework," Economics Letters, Elsevier, vol. 66(1), pages 33-39, January. [Downloadable!] (restricted)
  15. James J. Heckman & Jeffrey A. Smith, 1998. "Evaluating the Welfare State," NBER Working Papers 6542, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  16. Carneiro, Pedro & Hansen, Karsten T. & Heckman, James J., 2003. "Estimating Distributions of Treatment Effects with an Application to the Returns to Schooling and Measurement of the Effects of Uncertainty on College Choice," IZA Discussion Papers 767, Institute for the Study of Labor (IZA). [Downloadable!]
    Other versions:
Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. David Epstein & Dolores Jiménez-Rubio & Peter C. Smith & Marc Suhrcke, 2009. "Social determinants of health: an economic perspective," Health Economics, John Wiley & Sons, Ltd., vol. 18(5), pages 495-502. [Downloadable!]
Statistics
Access and download statistics

Did you know? You too can volunteer for RePEc, for example by encouraging others to use our services.

This page was last updated on 2009-11-16.


This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.