Efficiency in Estimation of Memory

30 Pages Posted: 6 Oct 2006

See all articles by Willa W. Chen

Willa W. Chen

Texas A&M University - Department of Statistics

Date Written: March 21, 2006

Abstract

We study the efficiency of semiparametric estimates of memory parameter. We propose a class of shift invariant tapers of order (p,q). For a fixed p, the variance inflation factor of the new tapers approaches 1 as q goes to infinity. We show that for d in (-1/2, p+1/2), the proposed tapered Gaussian Semiparametric Estimator has the same limiting distribution as the nontapered version for d in (-1/2, 1/2). The new estimator is mean and polynomial trend invariant, and is computationally advantageous in comparison to the recently proposed Exact Local Whittle estimator. The simulation study shows that our estimator has comparable or better mean squared error in finite samples for a variety of models.

Keywords: Gaussian semiparametric estimation,t apering, periodogram

JEL Classification: C13, C22

Suggested Citation

Chen, Willa W., Efficiency in Estimation of Memory (March 21, 2006). Available at SSRN: https://ssrn.com/abstract=935100 or http://dx.doi.org/10.2139/ssrn.935100

Willa W. Chen (Contact Author)

Texas A&M University - Department of Statistics ( email )

155 Ireland Street
447 Blocker
College Station, TX 77843
United States

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