A parametric approach to the estimation of cointegration vectors in panel data
AbstractIn this paper a parametric framework for estimation and inference in cointegrated panel data models is considered that is based on a cointegrated VAR(p) model. A convenient two-step estimator is suggested where in the first step all individual specific parameters are estimated, whereas in the second step the long-run parameters are estimated from a pooled least-squares regression. The two-step estimator and related test procedures can easily be modified to account for contemporaneously correlated errors, a feature that is often encountered in multi-country studies. Monte Carlo simulations suggest that the two-step estimator and related test procedures outperform semiparametric alternatives such as the FM-OLS approach, especially if the number of time periods is small.
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Bibliographic InfoPaper provided by International Conferences on Panel Data in its series 10th International Conference on Panel Data, Berlin, July 5-6, 2002 with number B5-4.
Date of creation: Mar 2002
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- Jorg Breitung, 2005. "A Parametric approach to the Estimation of Cointegration Vectors in Panel Data," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 151-173.
- Breitung, Jörg, 2002. "A parametric approach to the estimation of cointegration vectors in panel data," SFB 373 Discussion Papers 2002,3, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- NEP-ALL-2002-07-04 (All new papers)
- NEP-ECM-2002-07-10 (Econometrics)
- NEP-ETS-2002-07-04 (Econometric Time Series)
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