Robust covariance matrix estimation: HAC estimates with long memory/antipersistence correction

Peter M. Robinson

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: Smoothed nonparametric estimates of the spectral density matrix at zero frequency have been widely used in econometric inference, because they can consistently estimate the covariance matrix of a partial sum of a possibly dependent vector process. When elements of the vector process exhibit long memory or antipersistence such estimates are inconsistent. We propose estimates which are still consistent in such circumstances, adapting automatically to memory parameters that can vary across the vector and be unknown.

Keywords: Covariance matrix estimation; long memory; antipersistence correction; "HAC" estimates; vector process; spectral density. (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2004-03
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:ehl:lserod:2157

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