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In search of a robust inflation forecast

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Author Info
Scott Brave
Jonas D. M. Fisher

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Abstract

It is difficult to consistently improve upon forecasts of inflation based solely on the most recent data on inflation. In this article, we show how to do so. Our main finding is that the most robust forecasts combine information from several different forecasting models, each of which incorporates the information in the available inflation indicators in different ways.

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File URL: http://www.chicagofed.org/publications/economicperspectives/ep_4qtr2004_part2_Brave_Fisher.pdf
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Publisher Info
Article provided by Federal Reserve Bank of Chicago in its journal Economic Perspectives.

Volume (Year): (2004)
Issue (Month): Q IV ()
Pages: 12-31
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:fip:fedhep:y:2004:i:qiv:p:12-31:n:v.28no.4

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Keywords: Inflation (Finance);

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References listed on IDEAS
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. Stephen G. Cecchetti & Rita S. Chu & Charles Steindel, 2000. "The unreliability of inflation indicators," Current Issues in Economics and Finance, Federal Reserve Bank of New York, issue Apr. [Downloadable!]
  2. Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band Pass Filter," NBER Working Papers 7257, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
    • Lawrence J. Christiano & Terry J. Fitzgerald, 1999. "The Band pass filter," Working Paper 9906, Federal Reserve Bank of Cleveland. [Downloadable!]
    • Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, 05. [Downloadable!] (restricted)
  3. Andrew Atkeson & Lee E. Ohanian., 2001. "Are Phillips curves useful for forecasting inflation?," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Win, pages 2-11. [Downloadable!]
  4. James H. Stock & Mark W. Watson, 2003. "Forecasting Output and Inflation: The Role of Asset Prices," Journal of Economic Literature, American Economic Association, vol. 41(3), pages 788-829, September.
    Other versions:
  5. Christopher A. Sims, 2002. "The Role of Models and Probabilities in the Monetary Policy Process," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 33(2002-2), pages 1-62. [Downloadable!]
Full references

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. James H. Stock & Mark W. Watson, 2008. "Phillips Curve Inflation Forecasts," NBER Working Papers 14322, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  2. Doyle, Matthew, 2006. "Empirical Phillips Curves in OECD Countries: Has There Been A Common Breakdown?," Staff General Research Papers 12684, Iowa State University, Department of Economics. [Downloadable!]
  3. Andrew Ang & Geert Bekaert & Min Wei, 2006. "Do macro variables, asset markets, or surveys forecast inflation better?," Finance and Economics Discussion Series 2006-15, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
    Other versions:
  4. James H. Stock & Mark W. Watson, 2008. "Phillips curve inflation forecasts," Conference Series ; [Proceedings], Federal Reserve Bank of Boston. [Downloadable!]
  5. Todd E. Clark & Michael W. McCracken, 2006. "Combining forecasts from nested models," Research Working Paper RWP 06-02, Federal Reserve Bank of Kansas City. [Downloadable!]
    Other versions:
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