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G-7 Inflation Forecasts

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Canova, Fabio

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Abstract

This Paper compares the forecasting performance of some leading models of inflation for the cross section of G-7 countries. We show that bivariate and trivariate models suggested by economic theory or statistical analysis are hardly better than univariate models. Phillips curve specifications fit well into this class. Significant improvements in both the MSE of the forecasts and turning point prediction are obtained with time-varying coefficients models that exploit international interdependencies. The performance of the latter class of models is independent of the sample, while it is not the case for standard specifications.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 3283.

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Date of creation: Mar 2002
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Handle: RePEc:cpr:ceprdp:3283

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Keywords: forecasting inflation markov chain monte carlo methods panel var models

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  13. Fuhrer, Jeff & Moore, George, 1995. "Inflation Persistence," The Quarterly Journal of Economics, MIT Press, vol. 110(1), pages 127-59, February. [Downloadable!] (restricted)
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  18. Fabio Canova & Matteo Ciccarelli, 1999. "Forecasting and Turning Point Predictions in a Bayesian Panel VAR Model," Economics Working Papers 443, Department of Economics and Business, Universitat Pompeu Fabra. [Downloadable!]
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. William T. Gavin & Athena T. Theodorou, 2004. "A common model approach to macroeconomics: using panel data to reduce sampling error," Working Papers 2003-045, Federal Reserve Bank of St. Louis. [Downloadable!]
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  2. Jens Larsen & Ben May & James Talbot, . "Estimating real interest rates for the United Kingdom," Bank of England working papers 200, Bank of England. [Downloadable!]
  3. P.J.G. Vlaar & A.H.J. den Reijer, 2003. "Forecasting inflation: An art as well as a science!," DNB Staff Reports (discontinued) 107, Netherlands Central Bank. [Downloadable!]
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  4. Todd E. Clark & Michael W. McCracken, 2006. "Forecasting of small macroeconomic VARs in the presence of instabilities," Research Working Paper RWP 06-09, Federal Reserve Bank of Kansas City. [Downloadable!]
  5. Claus Brand & Hans-Eggert Reimers & Franz Seitz, 2003. "Narrow Money and the Business Cycle: Theoretical aspects and euro area evdence," Macroeconomics 0303012, EconWPA. [Downloadable!]
  6. Todd E. Clark & Michael W. McCracken, 2003. "The predictive content of the output gap for inflation : resolving in-sample and out-of-sample evidence," Research Working Paper RWP 03-06, Federal Reserve Bank of Kansas City. [Downloadable!]
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  7. Kirstin Hubrich, 2004. "Forecasting euro area inflation: Does aggregating forecasts by HICP component improve forecast accuracy?," Computing in Economics and Finance 2004 230, Society for Computational Economics. [Downloadable!]
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  8. Melisso Boschi & Alessandro Girardi, 2007. "Euro area inflation: long-run determinants and short-run dynamics," Applied Financial Economics, Taylor and Francis Journals, vol. 17(1), pages 9-24, January. [Downloadable!] (restricted)
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  9. Peter Hoerdahl & Oreste Tristani, 2004. "A joint econometric model of macroeconomic and term structure dynamics," Econometric Society 2004 North American Summer Meetings 379, Econometric Society. [Downloadable!]
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  10. A.H.J. den Reijer & P.J.G. Vlaar, 2003. "Forecasting Inflation in the Netherlands and the Euro Area," WO Research Memoranda (discontinued) 723, Netherlands Central Bank, Research Department. [Downloadable!]
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