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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.

Suggested Citation

  • 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. Philip T. Reiss & Jeff Goldsmith & Han Lin Shang & R. Todd Ogden, 2017. "Methods for Scalar-on-Function Regression," International Statistical Review, International Statistical Institute, vol. 85(2), pages 228-249, August.
    2. Olivier Coibion & Yuriy Gorodnichenko & Rupal Kamdar, 2018. "The Formation of Expectations, Inflation, and the Phillips Curve," Journal of Economic Literature, American Economic Association, vol. 56(4), pages 1447-1491, December.
    3. 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.
    4. 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.
    5. 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.
    6. Andrade, Philippe & Le Bihan, Hervé, 2013. "Inattentive professional forecasters," Journal of Monetary Economics, Elsevier, vol. 60(8), pages 967-982.
    7. Park, Joon Y. & Qian, Junhui, 2012. "Functional regression of continuous state distributions," Journal of Econometrics, Elsevier, vol. 167(2), pages 397-412.
    8. Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
    9. 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.
    10. Davidson, Russell & MacKinnon, James G, 1981. "Several Tests for Model Specification in the Presence of Alternative Hypotheses," Econometrica, Econometric Society, vol. 49(3), pages 781-793, May.
    11. Ulrike Malmendier & Stefan Nagel, 2016. "Learning from Inflation Experiences," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(1), pages 53-87.
    12. 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.
    13. Tsiaplias, Sarantis, 2020. "Time-Varying Consumer Disagreement and Future Inflation," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    14. 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.
    15. Ricardo Reis, 2021. "Losing the Inflation Anchors," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 52(2 (Fall)), pages 307-379.
    16. Orazio Attanasio & Agnes Kovacs & Krisztina Molnar, 2020. "Euler Equations, Subjective Expectations and Income Shocks," Economica, London School of Economics and Political Science, vol. 87(346), pages 406-441, April.
    17. Sophocles Mavroeidis & Mikkel Plagborg-M?ller & 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.
    18. Roberts, John M, 1995. "New Keynesian Economics and the Phillips Curve," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 27(4), pages 975-984, November.
    19. Andrew Filardo & Hans Genberg, 2010. "Targeting inflation in Asia and the Pacific: lessons from the recent past," BIS Papers chapters, in: Bank for International Settlements (ed.), The international financial crisis and policy challenges in Asia and the Pacific, volume 52, pages 251-273, Bank for International Settlements.
    20. Binder, Carola Conces, 2015. "Whose expectations augment the Phillips curve?," Economics Letters, Elsevier, vol. 136(C), pages 35-38.
    21. Harris, Milton & Raviv, Artur, 1993. "Differences of Opinion Make a Horse Race," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 473-506.
    22. Cecchetti, Stephen & Feroli, Michael & Hooper, Peter & Kashyap, Anil & Schoenholtz, Kermit L., 2017. "Deflating Inflation Expectations: The Implications of Inflation’s Simple Dynamics," CEPR Discussion Papers 11925, C.E.P.R. Discussion Papers.
    23. 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.
    24. Kneip A. & Utikal K. J, 2001. "Inference for Density Families Using Functional Principal Component Analysis," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 519-542, June.
    25. Christopher D. Carroll, 2003. "Macroeconomic Expectations of Households and Professional Forecasters," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 118(1), pages 269-298.
    26. Branch, William A. & McGough, Bruce, 2009. "A New Keynesian model with heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1036-1051, May.
    27. Robert Rich & Joseph Tracy, 2010. "The Relationships among Expected Inflation, Disagreement, and Uncertainty: Evidence from Matched Point and Density Forecasts," The Review of Economics and Statistics, MIT Press, vol. 92(1), pages 200-207, February.
    28. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    29. Reiss, Philip T. & Ogden, R. Todd, 2007. "Functional Principal Component Regression and Functional Partial Least Squares," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 984-996, September.
    30. Ruey S. Tsay, 2016. "Some Methods for Analyzing Big Dependent Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 673-688, October.
    31. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    32. Francesco D’Acunto & Ulrike Malmendier & Juan Ospina & Michael Weber, 2021. "Exposure to Grocery Prices and Inflation Expectations," Journal of Political Economy, University of Chicago Press, vol. 129(5), pages 1615-1639.
    33. G. Elliott & C. Granger & A. Timmermann (ed.), 2013. "Handbook of Economic Forecasting," Handbook of Economic Forecasting, Elsevier, edition 1, volume 2, number 2.
    34. Patton, Andrew J. & Timmermann, Allan, 2010. "Why do forecasters disagree? Lessons from the term structure of cross-sectional dispersion," Journal of Monetary Economics, Elsevier, vol. 57(7), pages 803-820, October.
    35. Cobham,David & Eitrheim,Øyvind & Gerlach,Stefan & Qvigstad,Jan F. (ed.), 2010. "Twenty Years of Inflation Targeting," Cambridge Books, Cambridge University Press, number 9780521768184, January.
    36. Crump, Richard K. & Eusepi, Stefano & Tambalotti, Andrea & Topa, Giorgio, 2022. "Subjective intertemporal substitution," Journal of Monetary Economics, Elsevier, vol. 126(C), pages 118-133.
    37. Kausik Chaudhuri & Minjoo Kim & Yongcheol Shin, 2016. "Forecasting distributions of inflation rates: the functional auto-regressive approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(1), pages 65-102, January.
    38. 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. Tsiaplias, Sarantis, 2020. "Time-Varying Consumer Disagreement and Future Inflation," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    2. Grimaud, Alex & Salle, Isabelle & Vermandel, Gauthier, 2025. "A Dynare toolbox for social learning expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    3. Michael Ehrmann & Paul Hubert, 2022. "Information Acquisition ahead of Monetary Policy Announcements," Working papers 897, Banque de France.
    4. Meeks, Roland & Monti, Francesca, 2023. "Heterogeneous beliefs and the Phillips curve," Journal of Monetary Economics, Elsevier, vol. 139(C), pages 41-54.
    5. Arndt, Sarah, 2024. "Different Newspapers – Different Inflation Perceptions," Working Papers 0748, University of Heidelberg, Department of Economics.
    6. Andros Kourtellos & Christos Antonios Statheas & Marios Zachariadis, 2025. "What can we learn from the distributions of inflation expectations across European households?," University of Cyprus Working Papers in Economics 02-2025, University of Cyprus Department of Economics.
    7. Yoosoon Chang & Soyoung Kim & Joon Y. Park, 2025. "How Do Macroaggregates and Income Distribution Interact Dynamically? A Novel Structural Mixed Autoregression with Aggregate and Functional Variables," Working Papers No 01/2025, Centre for Applied Macro- and Petroleum economics (CAMP), BI Norwegian Business School.
    8. Rychalovska, Yuliya & Slobodyan, Sergey & Wouters, Raf, 2025. "Survey expectations, learning and inflation dynamics," European Economic Review, Elsevier, vol. 180(C).
    9. Ellison, Martin & Macaulay, Alistair, 2021. "A rational inattention unemployment trap," Journal of Economic Dynamics and Control, Elsevier, vol. 131(C).
    10. Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2024. "Heterogeneity and Aggregate Fluctuations," Journal of Political Economy, University of Chicago Press, vol. 132(12), pages 4021-4067.
    11. 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.
    12. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    13. Philippe Goulet Coulombe & Karin Klieber & Christophe Barrette & Maximilian Goebel, 2024. "Maximally Forward-Looking Core Inflation," Papers 2404.05209, arXiv.org.
    14. 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).
    15. Philip Bunn & Lena Anayi & Emily Barnes & Nicholas Bloom & Paul Mizen & Gregory Thwaites & Ivan Yotzov, 2024. "How Curvy is the Phillips Curve?," NBER Working Papers 33234, National Bureau of Economic Research, Inc.
    16. Czudaj, Robert L., 2023. "Anchoring of Inflation Expectations and the Role of Monetary Policy and Cost-Push Factors," MPRA Paper 119029, University Library of Munich, Germany.
    17. 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.
    18. Christian Bayer & Luis Calderon & Moritz Kuhn, 2025. "Distributional Dynamics," ECONtribute Discussion Papers Series 351, University of Bonn and University of Cologne, Germany.

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    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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