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Belief distortions and Disagreement about Inflation

Author

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  • Giuseppe Pagano Giorgianni

    (Sapienza University Rome, Italy)

  • Valeria Patella

    (Sapienza University Rome, Italy)

Abstract

Disagreement in beliefs correlates with consensus expectations, inflation, and forecast errors. We evaluate whether disagreement emerges endogenously from irrational beliefs, and whether it is relevant for inflation and unemployment outcomes. Using the microdata of households' one-year-ahead inflation expectations from the Michigan Survey of Consumers, we estimate a functional data measure of inflation beliefs’ distribution. Disagreement explains most of its effect on inflation. Then, local projections simulate a belief distortion shock and show that an increase in consensus pessimism - defined as upward biases in inflation and unemployment forecasts - leads agents to price future uncertainty using information from the cross-sectional distribution of inflation expectations: higher inflation disagreement reflects lower expected profits, hence leading firms to increase inflation; whereas, they become more attentive towards firing decisions, explaining negligible effects on unemployment in the short to medium term.

Suggested Citation

  • Giuseppe Pagano Giorgianni & Valeria Patella, 2024. "Belief distortions and Disagreement about Inflation," Working Paper series 24-08, Rimini Centre for Economic Analysis.
    • Handle: RePEc:rim:rimwps:24-08
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    References listed on IDEAS

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    Cited by:

    1. Koop, Gary & Korobilis, Dimitris, 2013. "Large time-varying parameter VARs," Journal of Econometrics, Elsevier, vol. 177(2), pages 185-198.
    2. Hollmayr, Josef & Matthes, Christian, 2015. "Learning about fiscal policy and the effects of policy uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 59(C), pages 142-162.
    3. Michele Campolieti & Deborah Gefang & Gary Koop, 2011. "Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada," Working Papers 1138, University of Strathclyde Business School, Department of Economics.
    4. Michal Franta & Roman Horvath & Marek Rusnak, 2014. "Evaluating changes in the monetary transmission mechanism in the Czech Republic," Empirical Economics, Springer, vol. 46(3), pages 827-842, May.
    5. Chan, Joshua & Strachan, Rodney, 2012. "Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods," MPRA Paper 39360, University Library of Munich, Germany.
    6. Chauvet, Marcelle & Tierney, Heather L. R., 2007. "Real Time Changes in Monetary Policy," MPRA Paper 16199, University Library of Munich, Germany, revised Apr 2009.
    7. repec:rim:rimwps:26-08 is not listed on IDEAS

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    More about this item

    Keywords

    Inflation; Disagreement; Survey Expectations Microdata; Functional Data Analysis; Local Projections; Counterfactuals;
    All these keywords.

    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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