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

Jörg Breitung ()

No B5-4, 10th International Conference on Panel Data, Berlin, July 5-6, 2002 from International Conferences on Panel Data

Abstract: In 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.

Date: 2002-03
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (9)

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Related works:
Journal Article: A Parametric approach to the Estimation of Cointegration Vectors in Panel Data (2005) Downloads
Working Paper: A parametric approach to the estimation of cointegration vectors in panel data (2002) Downloads
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