A Copula-VAR-X Approach for Industrial Production Modelling and Forecasting

Carluccio Bianchi (), Alessandro Carta (), Dean Fantazzini, Maria Elena De Giuli () and Mario A. Maggi ()
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Carluccio Bianchi: Department of Economics and Quantitative Methods, University of Pavia
Alessandro Carta: Department of Economics and Quantitative Methods, University of Pavia
Maria Elena De Giuli: Department of Economics and Quantitative Methods, University of Pavia
Mario A. Maggi: Department of Economics and Quantitative Methods, University of Pavia

No 105, Quaderni di Dipartimento from University of Pavia, Department of Economics and Quantitative Methods

Abstract: World economies, and especially European ones, have become strongly interconnected in the last decades and a joint modelling is required. We propose here the use of Copulas 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 EMU countries and we provide evidence that the copula-VAR model outperforms or at worst compares similarly to normal VAR models, keeping the same computational tractability of the latter approach.

Keywords: Forecasting; Industrial Production; Copulas; VAR models. (search for similar items in EconPapers)
JEL-codes: C13 C32 C51 C53 (search for similar items in EconPapers)
Pages: 19 pages
Date: 2009-11
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Related works:
Journal Article: A copula-VAR-X approach for industrial production modelling and forecasting (2010)
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