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Asymptotic efficiency of the ordinary least squares estimator for regressions with unstable regressors

Title
Asymptotic efficiency of the ordinary least squares estimator for regressions with unstable regressors
Authors
Shin D.W.Oh M.S.
Ewha Authors
오만숙신동완
SCOPUS Author ID
오만숙scopus; 신동완scopus
Issue Date
2002
Journal Title
Econometric Theory
ISSN
0266-4666JCR Link
Citation
vol. 18, no. 5, pp. 1121 - 1138
Indexed
SCIE; SSCI; SCOPUS scopus
Abstract
For regression models with general unstable regressors having characteristic roots on the unit circle and general stationary errors independent of the regressors, sufficient conditions are investigated under which the ordinary least squares estimator (OLSE) is asymptotically efficient in that it has the same limiting distribution as the generalized least squares estimator (GLSE) under the same normalization. A key condition for the asymptotic efficiency of the OLSE is that one multiplicity of a characteristic root of the regressor process is strictly greater than the multiplicities of the other roots. Under this condition, the covariance matrix Γ of the errors and the regressor matrix X are shown to satisfy a relationship (ΓX = XC + V for some matrix C) for V asymptotically dominated by X, which is analogous to the condition (ΓX = XC for some matrix C) for numerical equivalence of the OLSE and the GLSE.
DOI
10.1017/S0266466602185057
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자연과학대학 > 통계학전공 > Journal papers
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