Bootstrap HAC tests for ordinary least squares regressions

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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.
Original languageEnglish
Pages (from-to)903-922
Number of pages20
JournalOxford Bulletin of Economics and Statistics
Issue number6
Early online date24 Oct 2011
Publication statusPublished - Dec 2012

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