Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/65349 
Authors: 
Year of Publication: 
2002
Series/Report no.: 
SFB 373 Discussion Paper No. 2002,3
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
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.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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