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Heterogeneous beliefs and the Phillips curve

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  • Meeks, Roland
  • Monti, Francesca

Abstract

Heterogeneous beliefs modify the New Keynesian Phillips curve by introducing a term in the cross-section distribution of expectations. To take that model to the data, we develop a novel functional data approach to estimation and inference that accounts for variation in distributions of expectations. We find that this variation may be summarized using a handful of functional factors, and demonstrate their statistical and economic relevance for inflation dynamics. Our results are among the first to highlight the potential benefits to be gained in empirical work from a rigorous treatment of diverse beliefs in the study of macroeconomic outcomes.

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  • Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
  • Handle: RePEc:eee:moneco:v:139:y:2023:i:c:p:41-54
    DOI: 10.1016/j.jmoneco.2023.06.003
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    1. Olivier Coibion & Yuriy Gorodnichenko & Saten Kumar, 2018. "How Do Firms Form Their Expectations? New Survey Evidence," American Economic Review, American Economic Association, vol. 108(9), pages 2671-2713, September.
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    3. Crump, Richard K. & Eusepi, Stefano & Tambalotti, Andrea & Topa, Giorgio, 2022. "Subjective intertemporal substitution," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 118-133.
    4. Pfajfar, Damjan & Santoro, Emiliano, 2010. "Heterogeneity, learning and information stickiness in inflation expectations," Journal of Economic Behavior & Organization, Elsevier, vol. 75(3), pages 426-444, September.
    5. N. Gregory Mankiw & Ricardo Reis & Justin Wolfers, 2004. "Disagreement about Inflation Expectations," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 209-270, National Bureau of Economic Research, Inc.
    6. López-Pintado, Sara & Romo, Juan, 2009. "On the Concept of Depth for Functional Data," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 718-734.
    7. Olivier Coibion & Yuriy Gorodnichenko, 2012. "What Can Survey Forecasts Tell Us about Information Rigidities?," Journal of Political Economy, University of Chicago Press, vol. 120(1), pages 116-159.
    8. Sophocles Mavroeidis & Mikkel Plagborg-Møller & James H. Stock, 2014. "Empirical Evidence on Inflation Expectations in the New Keynesian Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 52(1), pages 124-188, March.
    9. Cobham,David & Eitrheim,Øyvind & Gerlach,Stefan & Qvigstad,Jan F. (ed.), 2010. "Twenty Years of Inflation Targeting," Cambridge Books, Cambridge University Press, number 9780521768184, November.
    10. Ang, Andrew & Bekaert, Geert & Wei, Min, 2007. "Do macro variables, asset markets, or surveys forecast inflation better?," Journal of Monetary Economics, Elsevier, vol. 54(4), pages 1163-1212, May.
    11. Bowsher, Clive G. & Meeks, Roland, 2008. "The Dynamics of Economic Functions: Modeling and Forecasting the Yield Curve," Journal of the American Statistical Association, American Statistical Association, vol. 103(484), pages 1419-1437.
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    Cited by:

    1. Schorfheide, Frank & Chang, Minsu & Chen, Xiaohong, 2021. "Heterogeneity and Aggregate Fluctuations," CEPR Discussion Papers 16183, C.E.P.R. Discussion Papers.
    2. Tsiaplias, Sarantis, 2020. "Time-Varying Consumer Disagreement and Future Inflation," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    3. Ellison, Martin & Macaulay, Alistair, 2021. "A rational inattention unemployment trap," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    4. Michael Ehrmann & Paul Hubert, 2022. "Information Acquisition ahead of Monetary Policy Announcements," Working papers 897, Banque de France.
    5. Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
    6. Hilde C. Bjørnland & Yoosoon Chang & Jamie L. Cross, 2023. "Oil and the Stock Market Revisited: A mixed functional VAR approach," Working Papers No 03/2023, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    7. 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.
    8. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    9. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org.

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    More about this item

    Keywords

    Inflation dynamics; New Keynesian Phillips curve; Survey expectations; Functional principal components; Functional regression;
    All these keywords.

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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