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On the Nature and Stability of Sentiments

Author

Listed:
  • Ryan Chahrour

    (Boston College)

  • Gaetano Gaballo

    (Banque de France, Monetary Policy Division)

Abstract

We show that non-trivial aggregate fluctuations may originate with vanishingly- small common shocks to either information or fundamentals. These "sentiment" fluctuations can be driven by self-fulfilling variation in either first-order beliefs (as in Benhabib et al., 2015) or higher-order beliefs (as in Angeletos and La'O, 2013), due to an endogenous signal structure. We analyze out-of-equilibrium best-response functions in the underlying coordination game to study whether sentiment equilibria are stable outcomes of a convergent process. We nd that limiting sentiment equilibria are generally unattainable under both higher-order belief and adaptive learning dynamics, whereas equilibria without sentiment shocks show strong stability properties. Away from the limit case, however, multiple noisy rational expectations equilibria may be stable.

Suggested Citation

  • Ryan Chahrour & Gaetano Gaballo, 2015. "On the Nature and Stability of Sentiments," Boston College Working Papers in Economics 873, Boston College Department of Economics, revised 05 May 2015.
  • Handle: RePEc:boc:bocoec:873
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    References listed on IDEAS

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    1. Woodford, Michael, 1990. "Learning to Believe in Sunspots," Econometrica, Econometric Society, vol. 58(2), pages 277-307, March.
    2. Tarek A. Hassan & Thomas M. Mertens, 2017. "The Social Cost of Near-Rational Investment," American Economic Review, American Economic Association, vol. 107(4), pages 1059-1103, April.
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    12. repec:cwl:cwldpp:1821rrr is not listed on IDEAS
    13. George-Marios Angeletos & Alessandro Pavan, 2007. "Efficient Use of Information and Social Value of Information," Econometrica, Econometric Society, vol. 75(4), pages 1103-1142, July.
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    Cited by:

    1. Robert Ulbricht & Ludwig Straub, 2015. "Endogenous Uncertainty and Credit Crunches," 2015 Meeting Papers 199, Society for Economic Dynamics.
    2. Jakob Grazzini & Domenico Massaro, 2021. "Dispersed information, social networks, and aggregate behavior," Economic Inquiry, Western Economic Association International, vol. 59(3), pages 1129-1148, July.
    3. Nabavi Larimi , Seyed Mohsen & Ehsani , Mohammad Ali & Tavakolian , Hossein, 2018. "Effect of Sentiments on Macroeconomic Variables in Iran: A Dynamic Stochastic General Equilibrium Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 13(1), pages 1-30, January.
    4. Angeletos, G.-M. & Lian, C., 2016. "Incomplete Information in Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1065-1240, Elsevier.
    5. Orlando Gomes & J. C. Sprott, 2017. "Sentiment-driven limit cycles and chaos," Journal of Evolutionary Economics, Springer, vol. 27(4), pages 729-760, September.
    6. Jakob Grazzini & Domenico Massaro, 2016. "Dispersed Information and the Origins of Aggregate Fluctuations," CESifo Working Paper Series 5957, CESifo.
    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.

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    More about this item

    Keywords

    imperfect information; animal spirits; expectational coordination;
    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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