HAC Standard Errors and the Event Study Methodology: A Cautionary Note
George S. Ford
Phoenix Center for Advanced Legal & Economic Public Policy Studies
John D. Jackson
Auburn University - Department of Economics
University of Louisiana at Lafayette
November 2, 2008
Applied Economics Letters, Vol. 17, No. 12, 2010
In support of Fomby and Murfin (2005), we demonstrate empirically, rather than theoretically, the severe consequences of using HAC standard errors in regression-based financial event studies. Applying an event study to a recent merger, we show that the use of HAC standard errors render misleading conclusions. Critical values for t-tests on the event dummy variables are about 15 times larger than the nominal values using only a year of daily return data. Even with samples of only 100 returns, critical values exceed nominal critical values by a factor of 10.
Number of Pages in PDF File: 6
Keywords: Event Study, HAC, Heteroscedasticity Robust Standard ErrorsAccepted Paper Series
Date posted: November 4, 2008 ; Last revised: December 6, 2010
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