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Belief Distortions and Uncertainty About Inflation

Author

Listed:
  • Stefano Fasani
  • Giuseppe Pagano Giorgianni
  • Valeria Patella
  • Lorenza Rossi

Abstract

This paper studies the macroeconomic effects of a belief distortion shock—defined as the unexpected component of household inflation expectations after accounting for professional forecasts and observable fundamentals. Using survey data, U.S. macroeconomic variables, and machine-learning methods, we identify this shock and examine its effects both within and outside the zero lower bound (ZLB), conditioning on household inflation uncertainty. The shock raises inflation, uncertainty, and unemployment in normal times. At the ZLB, the shock reduces real interest rates and becomes expansionary; however, the accompanying rise in inflation uncertainty dampens or can even reverse these effects. A New Keynesian model with belief shocks replicates these dynamics and matches the empirical patterns of inflation uncertainty.

Suggested Citation

  • Stefano Fasani & Giuseppe Pagano Giorgianni & Valeria Patella & Lorenza Rossi, 2025. "Belief Distortions and Uncertainty About Inflation," CESifo Working Paper Series 12209, CESifo.
  • Handle: RePEc:ces:ceswps:_12209
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    References listed on IDEAS

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    1. Olivier Coibion & Yuriy Gorodnichenko & Johannes Wieland, 2012. "The Optimal Inflation Rate in New Keynesian Models: Should Central Banks Raise Their Inflation Targets in Light of the Zero Lower Bound?," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 79(4), pages 1371-1406.
    2. Frank Smets & Rafael Wouters, 2007. "Shocks and Frictions in US Business Cycles: A Bayesian DSGE Approach," American Economic Review, American Economic Association, vol. 97(3), pages 586-606, June.
    3. Diegel, Max & Nautz, Dieter, 2021. "Long-term inflation expectations and the transmission of monetary policy shocks: Evidence from a SVAR analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 130(C).
    4. Neville Francis & Michael T. Owyang & Jennifer E. Roush & Riccardo DiCecio, 2014. "A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks," The Review of Economics and Statistics, MIT Press, vol. 96(4), pages 638-647, October.
    5. Guido Lorenzoni, 2009. "A Theory of Demand Shocks," American Economic Review, American Economic Association, vol. 99(5), pages 2050-2084, December.
    6. José Luis Montiel Olea & Mikkel Plagborg‐Møller, 2021. "Local Projection Inference Is Simpler and More Robust Than You Think," Econometrica, Econometric Society, vol. 89(4), pages 1789-1823, July.
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    Cited by:

    1. Giuseppe Pagano Giorgianni, 2025. "Gas supply shocks, uncertainty and price setting: evidence from Italian firms," Papers 2510.03792, arXiv.org, revised Dec 2025.

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    More about this item

    Keywords

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    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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