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Sensitivity Analysis for Instrumental Variables Regression with Overidentifying Restrictions
Dylan S. Small
Journal of the American Statistical Association
Vol. 102, No. 479 (Sep., 2007), pp. 1049-1058
Stable URL: http://www.jstor.org/stable/27639945
Page Count: 10
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Instrumental variables regression (IV regression) is a method for making causal inferences about the effect of a treatment based on an observationa study in which there are unmeasured confounding variables. The method requires one or more valid instrumental variables (IVs); a valid IV is a variable that is associated with the treatment, is independent of unmeasured confounding variables, and has no direct effect on the outcome. Often there is uncertainty about the validity of the proposed IVs. When a researcher proposes more than one IV, the validity of these IVs can be tested through the "overidentifying restrictions test." Although the overidentifying restrictions test does provide some information, the test has no power versus certain alternatives and can have low power versus many alternatives due to its omnibus nature. To fully address uncertainty about the validity of the proposed IVs, we argue that a sesitivity analysis is needed. A sensitivity analysis examines the impact of plausible amount of invalidity if the proposed IVs on inferences for the parameters of interest. We develop a method of sensitivity analysis for IV regression with overidentifying restrictions that makes full use of the information provided by the overidentifying restrictions test but provides more information than the test by exploring sensitivity ti violations of the validity of the proposed IVs in directions for which the test has low power. Our sensitivity analysis uses interpretable parameters that can be discussed with subject matter experts. We illustrate our method using a study of food demand among rural households in the Philippines.
Journal of the American Statistical Association © 2007 American Statistical Association