Transcription of Testing for Weak Instruments in Linear IV Regression
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Testing for Weak Instruments in Linear IV Regression
Testing for Weak Instruments in Linear IV Regression August 2001 (This revision: February 2003) James H. Stock Department of Economics, Harvard University and the National Bureau of Economic Research and Motohiro Yogo* Department of Economics, Harvard University ABSTRACT Weak Instruments can produce biased IV estimators and hypothesis tests with large size distortions. But what, precisely, are weak Instruments , and how does one detect them in practice? This paper proposes quantitative definitions of weak Instruments based on the maximum IV estimator bias, or the maximum Wald test size distortion, when there are multiple endogenous regressors.
the instruments are weak if the conventional α-level Wald test based on IV statistics has an actual size that could exceed a certain threshold r, for example r = 10% when α = 5%. Each of these definitions yields a set of population parameters that defines weak instruments, that is, a “weak instrument set.”
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