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How Do Agents Form Macroeconomic Expectations? Evidence from Inflation Uncertainty

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  • Tao Wang

Abstract

This paper studies the behaviors of uncertainty through the lens of several popular models of expectation formation. The full-information rational expectations model (FIRE) predicts that both the ex ante uncertainty and the variance of ex post forecast errors are equal to the conditional volatility of shocks to the fundamentals. Incomplete-information models such as Sticky Expectation (SE) and Noisy Information (NI) and non-rational models such as Diagnostic Expectations (DE) predict distinctive rankings of these moments. The paper also shows that uncertainty provides additional parametric restrictions to favor SE over NI as a model of information rigidity, although both predict similar aggregate patterns of forecast errors and disagreement.

Suggested Citation

  • Tao Wang, 2024. "How Do Agents Form Macroeconomic Expectations? Evidence from Inflation Uncertainty," Staff Working Papers 24-5, Bank of Canada.
    • Handle: RePEc:bca:bocawp:24-5
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    References listed on IDEAS

    as
    1. 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.
    2. Jeffrey C. Fuhrer, 2018. "Intrinsic expectations persistence: evidence from professional and household survey expectations," Working Papers 18-9, Federal Reserve Bank of Boston.
    3. Joshua Abel & Robert Rich & Joseph Song & Joseph Tracy, 2016. "The Measurement and Behavior of Uncertainty: Evidence from the ECB Survey of Professional Forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(3), pages 533-550, April.
    4. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
    5. Davies, Anthony & Lahiri, Kajal, 1995. "A new framework for analyzing survey forecasts using three-dimensional panel data," Journal of Econometrics, Elsevier, vol. 68(1), pages 205-227, July.
    6. Sendhil Mullainathan & Marianne Bertrand, 2001. "Do People Mean What They Say? Implications for Subjective Survey Data," American Economic Review, American Economic Association, vol. 91(2), pages 67-72, May.
    7. Ball, Laurence, 1992. "Why does high inflation raise inflation uncertainty?," Journal of Monetary Economics, Elsevier, vol. 29(3), pages 371-388, June.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Business fluctuations and cycles; Inflation and prices; Monetary policy and uncertainty;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E71 - Macroeconomics and Monetary Economics - - Macro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on the Macro Economy

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