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Finite sample improvements in statistical inference with I(1) processes
Author(s) -
Marinucci D.,
Robinson P. M.
Publication year - 2001
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.613
Subject(s) - cointegration , ordinary least squares , context (archaeology) , parametric statistics , monte carlo method , sample (material) , econometrics , statistical inference , inference , mathematics , least squares function approximation , statistics , computer science , physics , paleontology , artificial intelligence , estimator , biology , thermodynamics
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 discussion 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. Copyright © 2001 John Wiley & Sons, Ltd.