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Belief distortions and Disagreement about Inflation

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  • Giuseppe Pagano Giorgianni
  • Valeria Patella

Abstract

Disagreement in inflation expectations amplifies inflation and lowers unemployment when beliefs are systematically upward-biased. Using the 1-year-ahead inflation forecast microdata from the Michigan Survey of Consumers, we employ a NK-Phillips curve framework and compute local projections on the contribution of inflation beliefs' distributions to inflation, in response to a belief distortion shock. They reveal that higher expected inflation leads firms to overreact by raising prices, when the shock is less informative and expectations are more dispersed. Hence, a weak consensus prompts confident, sentiment-driven expectations, and firms' expansionary behaviors, reducing unemployment and sustaining production. Conversely, a strong and more informative consensus about future inflationary outcomes fosters contractionary adjustments, increasing unemployment, and easing the labor market.

Suggested Citation

  • Giuseppe Pagano Giorgianni & Valeria Patella, 2025. "Belief distortions and Disagreement about Inflation," Working Papers in Public Economics 256, Department of Economics and Law, Sapienza University of Roma.
    • Handle: RePEc:sap:wpaper:wp256
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    References listed on IDEAS

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    More about this item

    Keywords

    Inflation; Belief Formation; Heterogeneous Agents; Survey Expectation Microdata; NK Phillips Curve; Functional Data Analysis; Local Projections;
    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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