Finite sample efficiency of OLS in linear regression models with long-memory disturbances
AbstractOLS is as efficient as GLS in the linear regression model with long-memory errors as the long-memory parameter approaches the boundary of the stationarity region_ provided the model contains a constant term. This generalizes previous results of Samarov Taqqu (Journal of Time Series Analysis 9 1998 pp, 191 â 200) to the regression case and gives a further example of the âhigh_correlation asymptotics of KrÃ¤mer & Baltagi (Economics Letters 50, 1996, pp. 13 â 17). --
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Bibliographic InfoArticle provided by Elsevier in its journal Economics Letters.
Volume (Year): 72 (2001)
Issue (Month): 2 (August)
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Web page: http://www.elsevier.com/locate/ecolet
Other versions of this item:
- Kleiber, Christian, 2000. "Finite sample efficiency of OLS in linear regression models with long-memory disturbances," Technical Reports 2000,34, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
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- Kramer, Walter & Baltagi, Badi, 1996. "A general condition for an optimal limiting efficiency of OLS in the general linear regression model," Economics Letters, Elsevier, vol. 50(1), pages 13-17, January.
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- Chung, Ching-Fan, 1994. "A note on calculating the autocovariances of the fractionally integrated ARMA models," Economics Letters, Elsevier, vol. 45(3), pages 293-297.
- Martellosio, Federico, 2011. "Efficiency of the OLS estimator in the vicinity of a spatial unit root," Statistics & Probability Letters, Elsevier, vol. 81(8), pages 1285-1291, August.
- Kleiber, Christian & Krämer, Walter, 2004. "Finite sample of the Durbin-Watson test against fractionally integrated disturbances," Technical Reports 2004,15, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Ko, Kyungduk & Lee, Jaechoul & Lund, Robert, 2008. "Confidence intervals for long memory regressions," Statistics & Probability Letters, Elsevier, vol. 78(13), pages 1894-1902, September.
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