Asymptotic efficiency of the ordinary least-squares estimator for sur models with integrated regressors
- Authors
- Shin, Dong Wan; Kim, Han Joon; Jhee, Won-Chul
- Issue Date
- 1-Jan-2007
- Publisher
- ELSEVIER SCIENCE BV
- Keywords
- cointegration; efficiency; generalized least-squares estimator; long-run covariance
- Citation
- STATISTICS & PROBABILITY LETTERS, v.77, no.1, pp.75 - 82
- Journal Title
- STATISTICS & PROBABILITY LETTERS
- Volume
- 77
- Number
- 1
- Start Page
- 75
- End Page
- 82
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/23648
- DOI
- 10.1016/j.spl.2006.05.024
- ISSN
- 0167-7152
- 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. (c) 2006 Elsevier B.V: All rights reserved.
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Collections - College of Engineering > Industrial and Data Engineering > Journal Articles
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