Use of instrumental variables in the presence of heterogeneity and self-selection: An application in breast cancer patients
Anirban Basu (),
Salvador Navarro () and
Health, Econometrics and Data Group (HEDG) Working Papers from HEDG, c/o Department of Economics, University of York
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.
Keywords: Self-selection; essential heterogeneity; instrumental variables; breast cancer; local instrumental variable method. (search for similar items in EconPapers)
JEL-codes: C01 C21 C31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-dcm and nep-hea
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