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A copula-VAR-X approach for industrial production modelling and forecasting
Authors:Carluccio Bianchi  Alessandro Carta  Dean Fantazzini  Maria Elena De Giuli  Mario A. Maggi
Affiliation:1. Dipartimento di Economia Politica e Metodi Quantitativi , Università di Pavia , Via S. Felice, 5, I27100 Pavia, Italy cbianchi@eco.unipv.it;3. Department of Statistics , University of Warwick , Coventry, CV4 7AL, UK;4. Moscow School of Economics , 1, Building 61, Leninskie Gory, 119992, M. V. Lomonosov MSU, Moscow, Russia;5. Dipartimento di Ricerche Aziendali , Università di Pavia , Via S. Felice, 5, I27100 Pavia, Italy
Abstract:
World economies, and especially European ones, have become strongly interconnected in the last decade and a joint modelling is required. We propose here the use of copulae to build flexible multivariate distributions, since they allow for a rich dependence structure and more flexible marginal distributions that better fit the features of empirical data, such as leptokurtosis. We use our approach to forecast industrial production series in the core European Monetary Union (EMU) countries and we provide evidence that the copula-Vector Autoregression (VAR) model outperforms or at worst compares similarly to normal VAR models, keeping the same computational tractability of the latter approach.
Keywords:
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