Wild Bootstrap Tests For Iv Regression

James MacKinnon and Russell Davidson

No 1135, Working Paper from Economics Department, Queen's University

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 bootstraptests. 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)
Pages: 27 pages
Date: 2007-08
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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https://www.econ.queensu.ca/sites/econ.queensu.ca/files/qed_wp_1135.pdf First version 2007 (application/pdf)

Related works:
Journal Article: Wild Bootstrap Tests for IV Regression (2010)
Working Paper: Wild bootstrap tests for IV regression (2009)
Working Paper: WILD BOOTSTRAP TESTS FOR IV REGRESSION (2007)
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Persistent link: https://EconPapers.repec.org/RePEc:qed:wpaper:1135

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