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Forecasting and Turning Point Predictions in a Bayesian Panel VAR Model

Fabio Canova () and Matteo Ciccarelli

No 2961, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We provide methods for forecasting variables and predicting turning points in panel Bayesian VARs. We specify a flexible model that accounts for both interdependencies in the cross section and time variations in the parameters. Posterior distributions for the parameters are obtained for hierarchical and for Minnesota-type 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.

Keywords: bayesian methods panel VAR markov chains monte carlo methods; forecasting; turning points (search for similar items in EconPapers)
JEL-codes: C11 C15 E32 E37 (search for similar items in EconPapers)
Date: 2001-09
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Related works:
Journal Article: Forecasting and turning point predictions in a Bayesian panel VAR model (2004) Downloads
Working Paper: FORECASTING AND TURNING POINT PREDICTIONS IN A BAYESIAN PANEL VAR MODEL (2000) Downloads
Working Paper: Forecasting and turning point predictions in a Bayesian panel VAR model (1999) Downloads
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