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KERNEL AND BANDWIDTH SELECTION, PREWHITENING, AND THE PERFORMANCE OF THE FULLY MODIFIED LEAST SQUARES ESTIMATION METHOD

Published online by Cambridge University Press:  17 May 2002

Christina Christou  and
Nikitas Pittis
Christina Christou
Affiliation:
University of Cyprus
Nikitas Pittis
Affiliation:
University of Piraeus
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Abstract

This paper examines several practical issues regarding the implementation of the Phillips and Hansen fully modified least squares (FMLS) method for the estimation of a cointegrating vector. Various versions of this method arise by selecting between standard and prewhitened kernel estimation and between parametric and nonparametric automatic bandwidth estimators and also among alternative kernels. A Monte Carlo study is conducted to investigate the finite-sample properties of the alternative versions of the FMLS procedure. The results suggest that the prewhitened kernel estimator of Andrews and Monahan (1992, Econometrica 60, 953–966) in which the bandwidth parameter is selected via the nonparametric procedure of Newey and West (1994, Review of Economic Studies 61, 631–653) minimizes the second-order asymptotic bias effects.

Type
Research Article
Information
Econometric Theory , Volume 18 , Issue 4 , August 2002 , pp. 948 - 961
Copyright
© 2002 Cambridge University Press

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