Bootstrap Tests of Nonnested Linear Regression Models

Russell Davidson and James MacKinnon ()

No 954, Working Papers from Queen's University, Department of Economics

Abstract: The J test for nonnested regression models often works badly as an asymptotic test, but it generally works very well when bootstrapped. We provide a theoretical analysis of the J test which explains both of these phenomena. We also propose a modified version of the test which works even better than the ordinary J test when bootstrapped. Using our theoretical results to make simulation much faster, we obtain extremely accurate Monte Carlo results which demonstrate just how well the bootstrapped tests perform.

Keywords: J test; Nonnested hypothesis test; Bootstrap; Regression (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
Date: Written
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http://www.econ.queensu.ca/working_papers/papers/qed_wp_954.pdf First version 1997 (application/pdf)

Related works:
Working Paper: Bootstrap Tests of Nonnested Linear Regression Models (1995)
Working Paper: Bootstrap Tests of Nonnested Linear Regression Models (1997)
Journal Article: Bootstrap J tests of nonnested linear regression models (2002)
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Persistent link: http://EconPapers.repec.org/RePEc:qed:wpaper:954

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