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WILD BOOTSTRAP TESTS FOR IV REGRESSION

Russell Davidson and James MacKinnon ()

Departmental Working Papers from McGill University, Department of Economics

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 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.

JEL-codes: C12 C15 C30 (search for similar items in EconPapers)
Pages: 27 pages
Date: 2007-08
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Related works:
Journal Article: Wild Bootstrap Tests for IV Regression (2010) Downloads
Working Paper: Wild bootstrap tests for IV regression (2009) Downloads
Working Paper: Wild Bootstrap Tests For Iv Regression (2007) Downloads
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