A Two-Stage Plug-In Bandwidth Selection and Its Implementation in Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation

Masayuki Hirukawa (mhirukaw@alcor.concordia.ca)
Additional contact information
Masayuki Hirukawa: Department of Economics, Concordia University

No 4005, Working Papers from Concordia University, Department of Economics

Abstract: The performance of a kernel HAC estimator depends on the accuracy of the estimation of the normalized curvature, an unknown quantity in the optimal bandwidth represented as the spectral density and its derivative. This paper proposes to estimate it with a general class of kernels. The AMSE of the kernel estimator and the AMSE-optimal bandwidth are derived. It is shown that the optimal bandwidth for the kernel estimator should grow at a much slower rate than the one for the HAC estimator with the same kernel. A solve-the-equation implementation method is also proposed. Finite sample performances are assessed through simulations.

Keywords: Covariance matrix estimation; Kernel estimator; Bandwidth selection; Spectral density; Asymptotic mean squared error (search for similar items in EconPapers)
JEL-codes: C12 C22 C32 (search for similar items in EconPapers)
Pages: 58 pages
Date: 2004-09
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:crd:wpaper:04005

Access Statistics for this paper

More papers in Working Papers from Concordia University, Department of Economics Contact information at EDIRC.
Bibliographic data for series maintained by Economics Department (paul.gomme@concordia.ca).