GVAR A Case of Spurious Cross-Sectional Cointegration

Abstract

Global Vector Autoregressive models came to be used quite widely in
empirical studies using macroeconomic non-stationary panel data for the global
economy. In this paper, it is shown that when the loading matrix of the
cointegrating vectors is not block-diagonal and the cross-sectional spillovers of
disequilibrium exist, the use of the GVAR model leads to spurious cross-sectional
long-run relationships. Moreover, the results of Monte Carlo simulation show
that the GVAR model is outperformed by other valid econometric approaches
in terms of the maximum likelihood estimator of long-run coefficients, when the
cointegrating vectors matrix is block-diagonal.