Wild Bootstrap Tests for IV Regression

Russell Davidson and James MacKinnon ()

No 1135, Working Papers from Queen's 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 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; two-stage least squares; wild bootstrap; pairs bootstrap; residual bootstrap; weak instruments; confidence intervals (search for similar items in EconPapers)
JEL-codes: C12 C15 C30 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: Written
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http://www.econ.queensu.ca/working_papers/papers/qed_wp_1135.pdf Second version 2008 (application/pdf)

Related works:
Working Paper: WILD BOOTSTRAP TESTS FOR IV REGRESSION (2007)
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Persistent link: http://EconPapers.repec.org/RePEc:qed:wpaper:1135

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