GVAR: A Case of Spurious Cross-Sectional Cointegration

• Autorzy: Piotr Kębłowski
• Języki publikacji: EN

Abstrakty

EN

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. (original abstract)

Słowa kluczowe

EN

Vector Autoregression Model (VAR); Monte Carlo simulation; Cointegration

PL

Model wektorowej autoregresji; Symulacja Monte Carlo; Kointegracja

• Czasopismo: Central European Journal of Economic Modelling and Econometrics (CEJEME)
• Rocznik: 2021
• Tom: 13
• Numer: nr 2
• Strony: 175--187

Twórcy

autor

Piotr Kębłowski

• University of Łódź, Poland

Bibliografia

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Identyfikatory

DOI

10.24425/cejeme.2021.137360