Asymptotic efficiency of the ordinary least-squares estimator for sur models with integrated regressors
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.
Volume (Year): 77 (2007)
Issue (Month): 1 (January)
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- Moon, Hyungsik R., 1999. "A note on fully-modified estimation of seemingly unrelated regressions models with integrated regressors," Economics Letters, Elsevier, vol. 65(1), pages 25-31, October.
- Kramer, Walter & Hassler, Uwe, 1998.
"Limiting efficiency of OLS vs. GLS when regressors are fractionally integrated,"
Elsevier, vol. 60(3), pages 285-290, September.
- Krämer, Walter & Hassler, Uwe, 1997. "Limiting efficiency of OLS vs. GLS when regressors are fractionally integrated," Technical Reports 1997,01, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Li, Kai, 1999. "Testing Symmetry and Proportionality in PPP: A Panel-Data Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 17(4), pages 409-18, October.
- Peter C.B. Phillips & Steven N. Durlauf, 1985.
"Multiple Time Series Regression with Integrated Processes,"
Cowles Foundation Discussion Papers
768, Cowles Foundation for Research in Economics, Yale University.
- P. C. B. Phillips & S. N. Durlauf, 1986. "Multiple Time Series Regression with Integrated Processes," Review of Economic Studies, Oxford University Press, vol. 53(4), pages 473-495.
- Shin, Dong Wan & Oh, Man Suk, 2002. "Asymptotic Efficiency Of The Ordinary Least Squares Estimator For Regressions With Unstable Regressors," Econometric Theory, Cambridge University Press, vol. 18(05), pages 1121-1138, October.
- Peter C. B. Phillips & Bruce E. Hansen, 1990. "Statistical Inference in Instrumental Variables Regression with I(1) Processes," Review of Economic Studies, Oxford University Press, vol. 57(1), pages 99-125.
- Yuichi Kitamura & Peter C.B. Phillips, 1994.
"Fully Modified IV, GIVE and GMM Estimation with Possibly Non-Stationary Regressions and Instruments,"
Cowles Foundation Discussion Papers
1082, Cowles Foundation for Research in Economics, Yale University.
- Kitamura, Yuichi & Phillips, Peter C. B., 1997. "Fully modified IV, GIVE and GMM estimation with possibly non-stationary regressors and instruments," Journal of Econometrics, Elsevier, vol. 80(1), pages 85-123, September.
- Shin, Dong Wan & Oh, Man-Suk, 2004. "Fully modified semiparametric GLS estimation for regressions with nonstationary seasonal regressors," Journal of Econometrics, Elsevier, vol. 122(2), pages 247-280, October.
- Walter Torous & Rossen Valkanov & Shu Yan, 2004. "On Predicting Stock Returns with Nearly Integrated Explanatory Variables," The Journal of Business, University of Chicago Press, vol. 77(4), pages 937-966, October.
- Baltagi, Badi H., 1988. "The Efficiency of OLS in a Seemingly Unrelated Regressions Model," Econometric Theory, Cambridge University Press, vol. 4(03), pages 536-537, December.
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