Robinson, Peter M. (2004) Robust covariance matrix estimation : HAC estimates with long memory/antipersistence correction. Econometrics; EM/2004/471, EM/04/471. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London, UK.
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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.
|Item Type:||Monograph (Discussion Paper)|
|Additional Information:||© 2004 Peter M Robinson|
|Library of Congress subject classification:||H Social Sciences > HB Economic Theory|
|Journal of Economic Literature Classification System:||C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models|
|Sets:||Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
|Date Deposited:||27 Apr 2007|
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