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Bootstrap HAC tests for ordinary least squares regressions

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JournalOxford Bulletin of Economics and Statistics
DateE-pub ahead of print - 24 Oct 2011
DatePublished (current) - Dec 2012
Issue number6
Volume74
Number of pages20
Pages (from-to)903-922
Early online date24/10/11
Original languageEnglish

Abstract

There is a need for tests that are derived from the ordinary least squares (OLS) estimators of regression coefficients and are useful in the presence of unspecified forms of heteroskedasticity and autocorrelation. A method that uses the moving block bootstrap and quasi-estimators in order to derive a consistent estimator of the asymptotic covariance matrix for the OLS estimators and robust significance tests is proposed. The method is shown to be asymptotically valid and Monte Carlo evidence indicates that it is capable of providing good control of significance levels in finite samples and good power compared with two other bootstrap tests.

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