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Finite sample improvements in statistical inference with I(1) processes

Marinucci, D. and Robinson, Peter (2001) Finite sample improvements in statistical inference with I(1) processes. Econometrics; EM/2001/422, EM/01/422. Suntory and Toyota International Centres for Economics and Related Disciplines, London School of Economics and Political Science, London.

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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.

Item Type: Monograph (Discussion Paper)
Official URL: http://sticerd.lse.ac.uk
Additional Information: © 2001 the authors
Uncontrolled Keywords: Fully-modified ordinary least squares; finite sample improvements; statistical inference with I(1) processes; Monte Carlo study; parametric estimates
Library of Congress subject classification: H Social Sciences > HB Economic Theory
Journal of Economic Literature Classification System: C - Mathematical and Quantitative Methods > C2 - Econometric Methods: Single Equation Models; Single Variables > C22 - Time-Series Models
Sets: Collections > Economists Online
Departments > Economics
Research centres and groups > Suntory and Toyota International Centres for Economics and Related Disciplines (STICERD)
Rights: http://www.lse.ac.uk/library/rights/LSERO.htm
Identification Number: EM/01/422
URL: http://eprints.lse.ac.uk/2161/

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