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Sources of Disagreement in Inflation Forecasts: An International Empirical Investigation

  • Richard Dennis
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    Central to the conduct of monetary policy are inflation forecasts. Inflation forecast are not unique. Central banks and professional organizations generate inflation forecasts while households are surveyed about their inflation outlook. This paper estimates inflation forecast disagreement for nine economies over the 1999-2009 period, five of which target inflation. I find that central bank transparency tends to increase forecast disagreement. To the extent this reflects the attention paid to inflation performance the implication is that transparency is beneficial. Moreover, this finding does not appear to be a feature that applies only to central banks that must adhere to an inflation target.

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    File URL: http://cama.crawford.anu.edu.au/pdf/working-papers/2012/422012.pdf
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    Paper provided by Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University in its series CAMA Working Papers with number 2012-42.

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    Length: 81 pages
    Date of creation: Sep 2012
    Date of revision:
    Handle: RePEc:een:camaaa:2012-42
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    1. Alan S. Blinder & Michael Ehrmann & Marcel Fratzscher & Jakob De Haan & David-Jan Jansen, 2008. "Central Bank Communication and Monetary Policy: A Survey of Theory and Evidence," NBER Working Papers 13932, National Bureau of Economic Research, Inc.
    2. Carin A.B. van der Cruijsen & Sylvester C.W. Eijffinger & Lex H. Hoogduin, 2008. "Optimal Central Bank Transparency," DNB Working Papers 178, Netherlands Central Bank, Research Department.
    3. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2003. "Disagreement about Inflation Expectations," Harvard Institute of Economic Research Working Papers 2011, Harvard - Institute of Economic Research.
    4. Martin Ellison & Thomas J. Sargent, 2012. "A Defense Of The Fomc," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(4), pages 1047-1065, November.
    5. Lahiri, Kajal & Sheng, Xuguang, 2008. "Evolution of forecast disagreement in a Bayesian learning model," Journal of Econometrics, Elsevier, vol. 144(2), pages 325-340, June.
    6. Dovern, Jonas & Fritsche, Ulrich & Slacalek, Jiri, 2009. "Disagreement among forecasters in G7 countries," Working Paper Series 1082, European Central Bank.
    7. Stephen Morris & Hyun Song Shin, 2005. "Central Bank Transparency and the Signal Value of Prices," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 36(2), pages 1-66.
    8. Daron Acemoglu & Victor Chernozhukov & Muhamet Yildiz, 2006. "Learning and Disagreement in an Uncertain World," NBER Working Papers 12648, National Bureau of Economic Research, Inc.
    9. Kazuhiko Hayakawa, 2009. "First Difference or Forward Orthogonal Deviation- Which Transformation Should be Used in Dynamic Panel Data Models?: A Simulation Study," Economics Bulletin, AccessEcon, vol. 29(3), pages 2008-2017.
    10. Smith, Jeremy & McAleer, Michael, 1995. "Alternative Procedures for Converting Qualitative Response Data to Quantitative Expectations: An Application to Australian Manufacturing," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(2), pages 165-85, April-Jun.
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