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A copula-VAR-X approach for industrial production modelling and forecasting

  • Carluccio Bianchi
  • Alessandro Carta
  • Dean Fantazzini
  • Maria Elena De Giuli
  • Mario Maggi

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.

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Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 42 (2010)
Issue (Month): 25 ()
Pages: 3267-3277

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Handle: RePEc:taf:applec:v:42:y:2010:i:25:p:3267-3277
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  1. Giorgio Bodo & Roberto Golinelli & Giuseppe Parigi, 2000. "Forecasting Industrial Production in the Euro Area," Temi di discussione (Economic working papers) 370, Bank of Italy, Economic Research and International Relations Area.
  2. Rosenberg, Joshua V., 1998. "Pricing multivariate contingent claims using estimated risk-neutral density functions," Journal of International Money and Finance, Elsevier, vol. 17(2), pages 229-247, April.
  3. Thierry Roncalli & Gael Riboulet & Ashkan Nikeghbali & Vado Durrleman & Erick Bouy?, 2001. "Copulas: an Open Field for Risk Management," Working Papers wp01-01, Warwick Business School, Finance Group.
  4. Timo Terasvirta & Clive W.J Granger & Andrew Patton, 2003. "Common factors in conditional distributions for Bivariate time series," FMG Discussion Papers dp455, Financial Markets Group.
  5. Bradley, Michael D. & Jansen, Dennis W., 2004. "Forecasting with a nonlinear dynamic model of stock returns and industrial production," International Journal of Forecasting, Elsevier, vol. 20(2), pages 321-342.
  6. Carlo Favero & Iryna Kaminska & Ulf Soderstrom, 2005. "The Predictive Power of the Yield Spread: Further Evidence and a Structural Interpretation," Working Papers 280, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
  7. Joshua V. Rosenberg, 2003. "Nonparametric pricing of multivariate contingent claims," Staff Reports 162, Federal Reserve Bank of New York.
  8. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.
  9. Whitney K. Newey & Douglas G. Steigerwald, 1997. "Asymptotic Bias for Quasi-Maximum-Likelihood Estimators in Conditional Heteroskedasticity Models," Econometrica, Econometric Society, vol. 65(3), pages 587-600, May.
  10. Hansen, Peter Reinhard, 2005. "A Test for Superior Predictive Ability," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 365-380, October.
  11. Asger Lunde & Peter Reinhard Hansen, 2001. "A Forecast Comparison of Volatility Models: Does Anything Beat a GARCH(1,1)?," Working Papers 2001-04, Brown University, Department of Economics.
  12. Baffigi, Alberto & Golinelli, Roberto & Parigi, Giuseppe, 2004. "Bridge models to forecast the euro area GDP," International Journal of Forecasting, Elsevier, vol. 20(3), pages 447-460.
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