ROBUST COVARIANCE MATRIX ESTIMATION: "HAC" Estimates with Long Memory/Antipersistence Correction
AbstractSmoothed 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.
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Bibliographic InfoPaper provided by Suntory and Toyota International Centres for Economics and Related Disciplines, LSE in its series STICERD - Econometrics Paper Series with number /2004/471.
Date of creation: Mar 2004
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Covariance matrix estimation; long memory; antipersistence correction; "HAC" estimates; vector process; spectral density.;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2005-01-02 (All new papers)
- NEP-ECM-2005-01-02 (Econometrics)
- NEP-ETS-2005-01-02 (Econometric Time Series)
- NEP-FIN-2005-01-02 (Finance)
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