Likelihood-Based Cointegration Analysis in Panels of Vector Error Correction Models

Abstract

We propose a likelihood-based framework for cointegration analysis in panels of a fixed number of vector error-correction (VEC) models. We obtain likelihood ratio statistics to test for a common cointegration rank across the individual VEC models with both heterogeneous and homogeneous cointegrating vectors. Their limiting distributions are a summation of the limiting behavior of Johansen trace statistics. We extend the asymptotic distribution theory to cover the case of an infinite cross-sectional dimension. We apply the framework to a dataset of exchange rates and appropriate monetary fundamentals. We find evidence for the validity of the monetary exchange rate model within a panel of VEC models for three major European countries, whereas the results based on individual VEC models for each of these countries separately are less supportive.

Citation

Groen, J. J. J. and F. Kleibergen (2003), “Likelihood-Based Cointegration Analysis in Panels of Vector Error Correction Models” Journal of Business & Economic Statistics: Vol. 21, pages 295–318.