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A parametric approach to the estimation of cointegration vectors in panel data

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  • Breitung, Jörg

Abstract

In this paper a parametric framework for stimation and inference in cointegrated panel data models is considered that is based on a cointegrated VAR(p) model. A convenient two-step estimator is uggested 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.

Suggested Citation

  • 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.
    • Handle: RePEc:zbw:sfb373:20023
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