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 leastsquares regression. The two-step estimator and related test procedures can easily be modified to account for contemporaneously

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... 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. * The research for this paper was carried out within the SFB 373 at the Humboldt University Berlin and the METEOR research project "Macroeconomic Consequences of Financial Crises" at the University of Maastricht. I wish to thank Ralf Brüggemann, Gerd Hansen and Uwe Hassler for helpful comments and suggestions.