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Inflation expectations, disagreement, and monetary policy

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  • Hoffmann, Mathias
  • Hürtgen, Patrick

Abstract

Survey data on inflation expectations show that: (i) private sector forecasts and central bank forecasts are not fully aligned and (ii) private sector forecasters disagree about inflation expectations. To reconcile these two facts we introduce dispersed information in a New Keynesian model, where as a result, inflation expectations differ between the private sector and the central bank. We show that output and inflation responses change markedly when the central bank responds to private sector inflation expectations rather than to their own.

Suggested Citation

  • Hoffmann, Mathias & Hürtgen, Patrick, 2016. "Inflation expectations, disagreement, and monetary policy," Discussion Papers 31/2016, Deutsche Bundesbank.
    • Handle: RePEc:zbw:bubdps:312016
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    References listed on IDEAS

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    1. Christina D. Romer & David H. Romer, 2004. "A New Measure of Monetary Shocks: Derivation and Implications," American Economic Review, American Economic Association, vol. 94(4), pages 1055-1084, September.
    2. Kristoffer Nimark, 2007. "Dynamic higher order expectations," Economics Working Papers 1118, Department of Economics and Business, Universitat Pompeu Fabra, revised Mar 2011.
    3. Nimark, Kristoffer, 2008. "Dynamic pricing and imperfect common knowledge," Journal of Monetary Economics, Elsevier, vol. 55(2), pages 365-382, March.
    4. George-Marios Angeletos & Jennifer La'O, 2010. "Noisy Business Cycles," NBER Chapters, in: NBER Macroeconomics Annual 2009, Volume 24, pages 319-378, National Bureau of Economic Research, Inc.
    5. Bartosz Mackowiak & Mirko Wiederholt, 2009. "Optimal Sticky Prices under Rational Inattention," American Economic Review, American Economic Association, vol. 99(3), pages 769-803, June.
    6. Kristoffer P. Nimark, 2014. "Man-Bites-Dog Business Cycles," American Economic Review, American Economic Association, vol. 104(8), pages 2320-2367, August.
    7. Andrade, Philippe & Crump, Richard K. & Eusepi, Stefano & Moench, Emanuel, 2016. "Fundamental disagreement," Journal of Monetary Economics, Elsevier, vol. 83(C), pages 106-128.
    8. Rondina, Giacomo & Walker, Todd B., 2021. "Confounding dynamics," Journal of Economic Theory, Elsevier, vol. 196(C).
    9. Leonardo Melosi, 2014. "Signaling Effects of Monteray Policy," 2014 Meeting Papers 830, Society for Economic Dynamics.
    10. James Cloyne & Patrick Hürtgen, 2016. "The Macroeconomic Effects of Monetary Policy: A New Measure for the United Kingdom," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(4), pages 75-102, October.
    11. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
    12. Stefano Eusepi & Richard Crump & Emanuel Moench & Philippe Andrade, 2014. "Noisy Information and Fundamental Disagreement," 2014 Meeting Papers 797, Society for Economic Dynamics.
    13. Townsend, Robert M, 1983. "Forecasting the Forecasts of Others," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 546-588, August.
    14. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    15. Knüppel, Malte & Vladu, Andreea L., 2016. "Approximating fixed-horizon forecasts using fixed-event forecasts," Discussion Papers 28/2016, Deutsche Bundesbank.
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    Cited by:

    1. Falck, Elisabeth & Hoffmann, Mathias & Hürtgen, Patrick, 2017. "Disagreement and monetary policy," Discussion Papers 29/2017, Deutsche Bundesbank.
    2. Gabriel Caldas Montes & Caio Ferrari Ferreira, 2019. "Does monetary policy credibility mitigate the effects of uncertainty about exchange rate on uncertainties about both inflation and interest rate?," International Economics and Economic Policy, Springer, vol. 16(4), pages 649-678, October.

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    More about this item

    Keywords

    business cycles; survey data; learning; disagreement; monetary policy;
    All these keywords.

    JEL classification:

    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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