Finite Sample Improvement in Statistical Inference with I(1) Processes

28 Pages Posted: 21 Jul 2008

See all articles by D. Marinucci

D. Marinucci

affiliation not provided to SSRN

Date Written: July 2001

Abstract

Robinson and Marinucci (1998) investigated the asymptotic behaviour of a narrow-band semiparametric procedure termed Frequency Domain Least Squares (FDLS) in the broad context of fractional cointegration analysis. Here we restrict to the standard case when the data are I(1) and the cointegrating errors are I(0), proving that modifications of the Fully-Modified Ordinary Least Squares (FM-OLS) procedure of Phillips and Hansen (1990) which use the FDLS idea have the same asymptotically desirable properties as FM-OLS, and, on the basis of a Monte Carlo study, find evidence that they have superior finite-sample properties; the new procedures are also shown to compare satisfactorily with parametric estimates.

JEL Classification: C13, C14

Suggested Citation

Marinucci, D., Finite Sample Improvement in Statistical Inference with I(1) Processes (July 2001). LSE STICERD Research Paper No. EM422, Available at SSRN: https://ssrn.com/abstract=1162603

D. Marinucci (Contact Author)

affiliation not provided to SSRN