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Price Dispersion, Private Uncertainty, and Endogenous Nominal Rigidities

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  • G. Gaballo

Abstract

This paper shows that when agents learn from prices, large private uncertainty may result from a small amount of heterogeneity. As in a Phelps-Lucas island model, final producers look at the prices of their local inputs to infer aggregate conditions. However, market linkages between islands make the informativeness of local prices endogenous to general equilibrium relations. In this context, I show that a vanishingly small heterogeneity in local conditions is enough to generate an equilibrium in which prices are rigid to aggregate shocks and transmit only partial information. I use this insight as a microfoundation for price rigidity in an otherwise frictionless monetary model and show that even a tiny amount of dispersion in fundamentals can lead to large non-neutrality of money.

Suggested Citation

  • G. Gaballo, 2017. "Price Dispersion, Private Uncertainty, and Endogenous Nominal Rigidities," Working papers 653, Banque de France.
  • Handle: RePEc:bfr:banfra:653
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    Cited by:

    1. Asriyan, Vladimir & Fuchs, William & Green, Brett, 2021. "Aggregation and design of information in asset markets with adverse selection," Journal of Economic Theory, Elsevier, vol. 191(C).
    2. Ryan Chahrour & Gaetano Gaballo, 2021. "Learning from House Prices: Amplification and Business Fluctuations [House Price Booms and the Current Account]," Review of Economic Studies, Oxford University Press, vol. 88(4), pages 1720-1759.
    3. Kenza Benhima & Isabella Blengini, 2020. "Optimal Monetary Policy when Information is Market-Generated," The Economic Journal, Royal Economic Society, vol. 130(628), pages 956-975.
    4. Gaetano Gaballo, 2016. "Rational Inattention to News: The Perils of Forward Guidance," American Economic Journal: Macroeconomics, American Economic Association, vol. 8(1), pages 42-97, January.
    5. Stephane Dupraz, 2017. "A Kinked-Demand Theory of Price Rigidity," 2017 Meeting Papers 387, Society for Economic Dynamics.
    6. Angeletos, George-Marios & Iovino, Luigi & La'O, Jennifer, 2020. "Learning over the business cycle: Policy implications," Journal of Economic Theory, Elsevier, vol. 190(C).
    7. George-Marios Angeletos & Chen Lian, 2016. "Incomplete Information in Macroeconomics: Accommodating Frictions in Coordination," NBER Working Papers 22297, National Bureau of Economic Research, Inc.
    8. Jonathan J Adams, 2021. "Firestorm: Multiplicity in Models with Full Information," Working Papers 001006, University of Florida, Department of Economics.
    9. Andrade, Philippe & Coibion, Olivier & Gautier, Erwan & Gorodnichenko, Yuriy, 2022. "No firm is an island? How industry conditions shape firms’ expectations," Journal of Monetary Economics, Elsevier, vol. 125(C), pages 40-56.
    10. Plantin, Guillaume, 2020. "Bubbles against Financial Repression," CEPR Discussion Papers 15197, C.E.P.R. Discussion Papers.
    11. George-Marios Angeletos & Chen Lian, 2021. "Determinacy without the Taylor Principle," NBER Working Papers 28881, National Bureau of Economic Research, Inc.
    12. Guillaume Plantin, 2021. "Asset Bubbles and Inflation as Competing Monetary Phenomena," Working Papers hal-03792088, HAL.

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    More about this item

    Keywords

    learning from prices; expectational coordination; dispersed information.;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles

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