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A Parametric approach to the Estimation of Cointegration Vectors in Panel Data

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  • Jorg Breitung

Abstract

In this article, 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, and 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 fully modified OLS approach, especially if the number of time periods is small.

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File URL: http://www.tandfonline.com/doi/abs/10.1081/ETC-200067895
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Econometric Reviews.

Volume (Year): 24 (2005)
Issue (Month): 2 ()
Pages: 151-173

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Handle: RePEc:taf:emetrv:v:24:y:2005:i:2:p:151-173

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Related research

Keywords: Cointegrated systems; Estimation; Inference; Panel data;

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References

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  1. Yoosoon Chang, 2000. "Bootstrap Unit Root Tests in Panels with Cross-Sectional Dependency," Cowles Foundation Discussion Papers 1251, Cowles Foundation for Research in Economics, Yale University.
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  17. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-80, November.
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