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Heterogeneous beliefs and the Phillips curve

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  • Meeks, Roland

    (International Monetary Fund)

  • Monti, Francesca

    (Bank of England)

Abstract

We establish a set of novel empirical facts concerning cross-section distributions of inflation expectations reported in surveys. Almost all the variation in expectations about their mean may be summarized via three factors we call disagreement, skew, and shape. We adopt a functional principal component regression approach to estimating forward-looking models of inflation that exploits the heterogeneity present in individual-level data. By using survey information more effectively, our approach reveals an enhanced role for expectations in inflation dynamics that is robust to lagged inflation, trend inflation, and supply factors. Our findings hold in similar form across two major economies.

Suggested Citation

  • Meeks, Roland & Monti, Francesca, 2019. "Heterogeneous beliefs and the Phillips curve," Bank of England working papers 807, Bank of England.
  • Handle: RePEc:boe:boeewp:0807
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    Cited by:

    1. Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2021. "Heterogeneity and Aggregate Fluctuations," NBER Working Papers 28853, National Bureau of Economic Research, Inc.
    2. Yoosoon Chang & Ana María Herrera & Elena Pesavento, 2023. "Oil prices uncertainty, endogenous regime switching, and inflation anchoring," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 820-839, September.
    3. Hilde C. Bjørnland & Yoosoon Chang & Jamie L. Cross, 2023. "Oil and the Stock Market Revisited: A Mixed Functional VAR Approach," CAMA Working Papers 2023-18, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    5. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    6. Tsiaplias, Sarantis, 2020. "Time-Varying Consumer Disagreement and Future Inflation," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    7. Andreasen, Martin M. & Caggiano, Giovanni & Castelnuovo, Efrem & Pellegrino, Giovanni, 2024. "Does risk matter more in recessions than in expansions? Implications for monetary policy," Journal of Monetary Economics, Elsevier, vol. 143(C).
    8. Ellison, Martin & Macaulay, Alistair, 2021. "A rational inattention unemployment trap," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    9. Michael Ehrmann & Paul Hubert, 2022. "Information Acquisition ahead of Monetary Policy Announcements," Working papers 897, Banque de France.
    10. Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
    11. Arndt, Sarah, 2024. "Different Newspapers – Different Inflation Perceptions," Working Papers 0748, University of Heidelberg, Department of Economics.
    12. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.

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    More about this item

    Keywords

    Survey expectations; inflation dynamics; density function; functional regression; functional principal components;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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