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Beyond Rationality: Unveiling the Role of Animal Spirits and Inflation Extrapolation in Central Bank Communication of the US

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  • Arpan Chakraborty

Abstract

Modern macroeconomic models, particularly those grounded in Rational Expectation Dynamic Stochastic General Equilibrium (DSGE), operate under the assumption of fully rational decision-making. This paper examines the impact of behavioral factors, particularly 'animal spirits' (emotional and psychological influences on economic decisions) and 'inflation extrapolators', on the communication index/sentiment index of the US Federal Reserve. Utilizing simulations from a behavioral New Keynesian model alongside real-world data derived from Federal Reserve speeches, the study employs an Auto-Regressive Distributed Lag (ARDL) technique to analyze the interplay between these factors. The findings indicate that while the fraction of inflation extrapolators do not significantly affect the Fed's sentiment index, various aspects of animal spirits exert a notable impact. This suggests that not only is the US output gap influenced by animal spirits, but the Federal Reserve's communication is also substantially shaped by these behavioral factors. This highlights the limitations of rational expectation DSGE models and underscores the importance of incorporating behavioral insights to achieve a more nuanced understanding of economic dynamics and central bank communication.

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  • Arpan Chakraborty, 2024. "Beyond Rationality: Unveiling the Role of Animal Spirits and Inflation Extrapolation in Central Bank Communication of the US," Papers 2409.10938, arXiv.org.
    • Handle: RePEc:arx:papers:2409.10938
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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Pedro Bordalo & Nicola Gennaioli & Yueran Ma & Andrei Shleifer, 2020. "Overreaction in Macroeconomic Expectations," American Economic Review, American Economic Association, vol. 110(9), pages 2748-2782, September.
    3. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    4. Tuckett, David, 2012. "Financial markets are markets in stories: Some possible advantages of using interviews to supplement existing economic data sources," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1077-1087.
    5. De Grauwe, Paul & Ji, Yuemei, 2020. "Structural reforms, animal spirits, and monetary policies," European Economic Review, Elsevier, vol. 124(C).
    6. Proaño, Christian R. & Lojak, Benjamin, 2020. "Animal spirits, risk premia and monetary policy at the zero lower bound," Journal of Economic Behavior & Organization, Elsevier, vol. 171(C), pages 221-233.
    7. Pascal Seppecher & Isabelle Salle, 2015. "Deleveraging crises and deep recessions: a behavioural approach," Applied Economics, Taylor & Francis Journals, vol. 47(34-35), pages 3771-3790, July.
    8. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    9. De Grauwe, Paul & Foresti, Pasquale, 2023. "Interactions of fiscal and monetary policies under waves of optimism and pessimism," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 466-481.
    10. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    11. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    12. Paul De Grauwe, 2012. "Lectures on Behavioral Macroeconomics," Economics Books, Princeton University Press, edition 1, volume 1, number 9891.
    13. Calvo, Guillermo A., 1983. "Staggered prices in a utility-maximizing framework," Journal of Monetary Economics, Elsevier, vol. 12(3), pages 383-398, September.
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