Bootstrap inference in a linear equation estimated by instrumental variables

Russell Davidson and James MacKinnon

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Abstract: We study several tests for the coefficient of the single right-hand-side endogenous variable in a linear equation estimated by instrumental variables. We show that writing all the test statistics—Student's t, Anderson-Rubin, the LM statistic of Kleibergen and Moreira (K), and likelihood ratio (LR)—as functions of six random quantities leads to a number of interesting results about the properties of the tests under weakinstrument asymptotics. We then propose several new procedures for bootstrapping the three non-exact test statistics and also a new conditional bootstrap version of the LR test. These use more efficient estimates of the parameters of the reduced-form equation than existing procedures. When the best of these new procedures is used, both the K and conditional bootstrap LR tests have excellent performance under the null. However, power considerations suggest that the latter is probably the method of choice.

Keywords: bootstrap; weak instruments; IV estimation (search for similar items in EconPapers)
Date: 2009-12-22
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00442713
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Related works:
Journal Article: Bootstrap inference in a linear equation estimated by instrumental variables (2008)
Working Paper: Bootstrap Inference In A Linear Equation Estimated By Instrumental Variables (2008)
Working Paper: BOOTSTRAP INFERENCE IN A LINEAR EQUATION ESTIMATED BY INSTRUMENTAL VARIABLES (2006)
Working Paper: Bootstrap Inference In A Linear Equation Estimated By Instrumental Variables (2006)
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