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Asymptotic efficiency of the ordinary least-squares estimator for sur models with integrated regressors

Title
Asymptotic efficiency of the ordinary least-squares estimator for sur models with integrated regressors
Authors
Shin D.W.Joon Kim H.Jhee W.-C.
Ewha Authors
신동완
SCOPUS Author ID
신동완scopus
Issue Date
2007
Journal Title
Statistics and Probability Letters
ISSN
0167-7152JCR Link
Citation
vol. 77, no. 1, pp. 75 - 82
Indexed
SCIE; SCOPUS WOS scopus
Abstract
For seemingly unrelated regression (SUR) models with integrated regressors, two sufficient conditions are identified, under which the ordinary least-squares estimator (OLSE) is asymptotically efficient. The first condition is that every pair of regressor processes are cointegrated in a specific way that one regressor is a linear combination of the other regressor up to a zero-mean stationary error and the second condition is that, for every pair of regressor processes, the pair of error processes deriving the regressor processes have zero long-run covariance. © 2006 Elsevier B.V. All rights reserved.
DOI
10.1016/j.spl.2006.05.024
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
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