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Heterogeneity, Inattention, and Bayesian Updates

Author

Listed:
  • Raffaella Giacomini
  • Vasiliki Skreta
  • Javier Turen

Abstract

We formulate a theory of expectations updating that fits the dynamics of accuracy and disagreement in a new survey of professional forecasters. We document new stylized facts, including the puzzling persistence of disagreement as uncertainty resolves. Our theory explains these facts by allowing for different channels of heterogeneity. Agents produce an initial forecast based on heterogeneous priors and are heterogeneously "inattentive." Updaters use Bayes' rule and interpret public information using possibly heterogeneous models. Structural estimation of our theory supports the conclusion that in normal times heterogeneous priors and inattention are enough to generate persistent disagreement, but not during the crisis.

Suggested Citation

  • Raffaella Giacomini & Vasiliki Skreta & Javier Turen, 2020. "Heterogeneity, Inattention, and Bayesian Updates," American Economic Journal: Macroeconomics, American Economic Association, vol. 12(1), pages 282-309, January.
    • Handle: RePEc:aea:aejmac:v:12:y:2020:i:1:p:282-309
    DOI: 10.1257/mac.20180235
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    Cited by:

    1. Lahiri, Kajal & Zhao, Yongchen, 2020. "The Nordhaus test with many zeros," Economics Letters, Elsevier, vol. 193(C).
    2. An, Zidong & Zheng, Xinye, 2023. "Diligent forecasters can make accurate predictions despite disagreeing with the consensus," Economic Modelling, Elsevier, vol. 125(C).
    3. Alexandra Belova & Philippe Gagnepain & Stéphane Gauthier, 2020. "An assessment of Nash equilibria in the airline industry," Working Papers halshs-02932780, HAL.
    4. Gilboa, Itzhak & Samuelson, Larry & Schmeidler, David, 2022. "Learning (to disagree?) in large worlds," Journal of Economic Theory, Elsevier, vol. 199(C).
    5. Frache, Serafin & Lluberas, Rodrigo & Turen, Javier, 2024. "Belief-dependent pricing decisions," Economic Modelling, Elsevier, vol. 132(C).
    6. Brian Hill, 2022. "Updating confidence in beliefs," Post-Print hal-03503986, HAL.
    7. Fiechter, Chad M. & Kuethe, Todd H. & Zhang, Wendong, 2022. "Information Rigidities in Farmland Value Expectations," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322070, Agricultural and Applied Economics Association.
    8. Christopher S. Sutherland, 2020. "Forward Guidance and Expectation Formation: A Narrative Approach," Staff Working Papers 20-40, Bank of Canada.
    9. Fiechter, Chad & Kuethe, Todd & Zhang, Wendong, 2023. "Information Rigidities and Farmland Value Expectations," ISU General Staff Papers 202306131414240000, Iowa State University, Department of Economics.
    10. Hill, Brian, 2022. "Updating confidence in beliefs," Journal of Economic Theory, Elsevier, vol. 199(C).
    11. Keppo, Jussi & Satopää, Ville A., 2024. "Bayesian herd detection for dynamic data," International Journal of Forecasting, Elsevier, vol. 40(1), pages 285-301.
    12. Zidong An & Salem Abo‐Zaid & Xuguang Simon Sheng, 2023. "Inattention and the impact of monetary policy," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(4), pages 623-643, June.
    13. An, Zidong & Sheng, Xuguang Simon & Zheng, Xinye, 2023. "What is the role of perceived oil price shocks in inflation expectations?," Energy Economics, Elsevier, vol. 126(C).
    14. Czudaj, Robert L., 2022. "Heterogeneity of beliefs and information rigidity in the crude oil market: Evidence from survey data," European Economic Review, Elsevier, vol. 143(C).
    15. Ghosh, Aniruddha & Khan, M. Ali, 2021. "On a diversity of perspectives and world views: Learning under Bayesian vis-á-vis DeGroot updating," Economics Letters, Elsevier, vol. 202(C).
    16. Christopher S Sutherland, 2022. "Forward guidance and expectation formation: A narrative approach," BIS Working Papers 1024, Bank for International Settlements.
    17. Gilboa, Itzhak & Minardi, Stefania & Samuelson, Larry, 2020. "Theories and cases in decisions under uncertainty," Games and Economic Behavior, Elsevier, vol. 123(C), pages 22-40.
    18. Chini, Emilio Zanetti, 2023. "Can we estimate macroforecasters’ mis-behavior?," Journal of Economic Dynamics and Control, Elsevier, vol. 149(C).
    19. Yanwei Jia & Jussi Keppo & Ville Satopää, 2023. "Herding in Probabilistic Forecasts," Management Science, INFORMS, vol. 69(5), pages 2713-2732, May.

    More about this item

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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