A review of instrumental variables estimation in the applied health sciences

Paul Grootendorst

Social and Economic Dimensions of an Aging Population Research Papers from McMaster University

Abstract: Health scientists often use observational data to estimate treatment effects when controlled experiments are not feasible. A limitation of observational research is non-random selection of subjects into different treatments, potentially leading to selection bias. The 2 commonly used solutions to this problem – covariate adjustment and fully parametric models – are limited by strong and untestable assumptions. Instrumental variables estimation can be a viable alternative. In this paper, I review examples of the application of IV in the health and social sciences, I show how the IV estimator works, I discuss the factors that affect its performance, I review how the interpretation of the IV estimator changes when treatment effects vary by individual, and consider the application of IV to nonlinear models.

Keywords: instrumental variables; treatment effects; health outcomes (search for similar items in EconPapers)
JEL-codes: C31 I12 (search for similar items in EconPapers)
Pages: 32 pages
Date: 2007-06
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (6)

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