Wild bootstrap tests for IV regression

Russell Davidson and James MacKinnon

Working Papers from HAL

Abstract: We propose a wild bootstrap procedure for linear regression models estimated by instrumental variables. Like other bootstrap procedures that we have proposed elsewhere, it uses efficient estimates of the reduced-form equation(s). Unlike them, it takes account of possible heteroskedasticity of unknown form. We apply this procedure to t tests, including heteroskedasticity-robust t tests, and to the Anderson-Rubin test. We provide simulation evidence that it works far better than older methods, such as the pairs bootstrap. We also show how to obtain reliable confidence intervals by inverting bootstrap tests. An empirical example illustrates the utility of these procedures.

Keywords: Instrumental variables estimation; two-stage least squares; weak instruments; wild bootstrap; pairs bootstrap; residual bootstrap; confidence intervals; Anderson-Rubin test (search for similar items in EconPapers)
Date: 2009-12-30
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00443550
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Citations: View citations in EconPapers (1)

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Related works:
Journal Article: Wild Bootstrap Tests for IV Regression (2010)
Working Paper: WILD BOOTSTRAP TESTS FOR IV REGRESSION (2007)
Working Paper: Wild Bootstrap Tests For Iv Regression (2007)
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