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Forecasting and turning point predictions in a Bayesian panel VAR model

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  • Fabio Canova

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  • Matteo Ciccarelli

Abstract

We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model which accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for a particular type of diffuse, for Minnesota-type and for hierarchical priors. Formulas for multistep, multiunit point and average forecasts are provided. An application to the problem of forecasting the growth rate of output and of predicting turning points in the G-7 illustrates the approach. A comparison with alternative forecasting methods is also provided.

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Bibliographic Info

Paper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 443.

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Date of creation: Oct 1999
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Handle: RePEc:upf:upfgen:443

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Web page: http://www.econ.upf.edu/

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Keywords: Forecasting; turning points; bayesian methods; panel VAR; Markov chains Monte Carlo methods;

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  9. Canova, Fabio & Ciccarelli, Matteo, 2004. "Forecasting and turning point predictions in a Bayesian panel VAR model," Journal of Econometrics, Elsevier, vol. 120(2), pages 327-359, June.
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