ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS

Dong Wan Shin and Man Suk Oh

Econometric Theory, 2002, vol. 18, issue 05, pages 1121-1138

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 of the errors and the regressor matrix X are shown to satisfy a relationship ( X = XC + V for some matrix C) for V asymptotically dominated by X, which is analogous to the condition ( X = XC for some matrix C) for numerical equivalence of the OLSE and the GLSE.

Date: 2002

Downloads: (external link)
http://journals.cambridge.org/abstract_S0266466602185057 link to article abstract page (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cup:etheor:v:18:y:2002:i:05:p:1121-1138_18

Access Statistics for this article

More articles in Econometric Theory from Cambridge University Press
Address: The Edinburgh Building, Shaftesbury Road, Cambridge CB2 2RU UK
Series data maintained by Mike Eden ().