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Firm performance, macroeconomic conditions, and “animal spirits” in a Post Keynesian model of aggregate fluctuations

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  • Shyam Gouri Suresh
  • Mark Setterfield
Abstract
We construct a multiagent system (MAS) model of cyclical growth in which aggregate fluctuations result from variations in activity at the firm level. The latter, in turn, result from changes in “animal spirits” or the state of long-run expectations (SOLE) and their effect on firms’ investment behavior. We focus on the impact of publicly available information about macroeconomic conditions—analogous to the press releases of national statistical agencies—on changes in the SOLE and hence the amplitude of aggregate fluctuations. Our results suggest that the amplitude of fluctuations is reduced by extremes of attention or inattention to aggregate economic performance, but that this relationship is subject to complicated (and possibly complex) phase transitions exhibiting extreme sensitivity to initial conditions.

Suggested Citation

  • Shyam Gouri Suresh & Mark Setterfield, 2015. "Firm performance, macroeconomic conditions, and “animal spirits” in a Post Keynesian model of aggregate fluctuations," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 38(1), pages 38-63, July.
    • Handle: RePEc:mes:postke:v:38:y:2015:i:1:p:38-63
    DOI: 10.1080/01603477.2015.1065676
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    1. Christiansen, Charlotte & Eriksen, Jonas Nygaard & Møller, Stig Vinther, 2014. "Forecasting US recessions: The role of sentiment," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 459-468.
    2. Sheila C. Dow & John Hillard (ed.), 1995. "Keynes, Knowledge And Uncertainty," Books, Edward Elgar Publishing, number 148.
    3. Susanto Basu & Brent Bundick, 2017. "Uncertainty Shocks in a Model of Effective Demand," Econometrica, Econometric Society, vol. 85, pages 937-958, May.
    4. Bill Gibson & Mark Setterfield, 2015. "Real and financial crises in the Keynes-Kalecki structuralist model: An agent-based approach," Working Papers 1517, New School for Social Research, Department of Economics.
    5. Vasilev, Aleksandar & Maksumov, Rashid, 2010. "Critical analysis of Chapter 23 of Keynes’s Notes on Mercantilism in The General Theory of Employment, Interest and Money (1936)," EconStor Research Reports 155318, ZBW - Leibniz Information Centre for Economics.
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    Cited by:

    1. Mark Setterfield, 2021. "Harrodians and Kaleckians: a suggested reconciliation and synthesis," Working Papers 2111, New School for Social Research, Department of Economics, revised Jan 2022.
    2. Citera, Emanuele & Gouri Suresh, Shyam & Setterfield, Mark, 2023. "The network origins of aggregate fluctuations: A demand-side approach," Structural Change and Economic Dynamics, Elsevier, vol. 64(C), pages 111-123.
    3. Roberto Veneziani & Luca Zamparelli & Corrado Di Guilmi, 2017. "The Agent-Based Approach To Post Keynesian Macro-Modeling," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1183-1203, December.
    4. Mark Setterfield & George Wheaton, 2024. "Animal spirits and the Goodwin pattern," Working Papers 2407, New School for Social Research, Department of Economics.
    5. Setterfield, Mark & Gouri Suresh, Shyam, 2016. "Multi-agent systems as a tool for analyzing path-dependent macrodynamics," Structural Change and Economic Dynamics, Elsevier, vol. 38(C), pages 25-37.
    6. Mark Setterfield, 2019. "Tolerable ranges of variation in the rate of capacity utilization and corridor instability: a reply to Florian Botte," Working Papers 1905, New School for Social Research, Department of Economics.
    7. Mark Setterfield, 2015. "Time variation in the size of the multiplier: a Kalecki-Harrod approach," Working Papers 1522, New School for Social Research, Department of Economics, revised Jan 2017.
    8. Ettore Gallo & Mark Setterfield, 2022. "Historical Time and the Current State of Post-Keynesian Growth Theory," Working Papers 2204, New School for Social Research, Department of Economics.

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    More about this item

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • E12 - Macroeconomics and Monetary Economics - - General Aggregative Models - - - Keynes; Keynesian; Post-Keynesian; Modern Monetary Theory
    • E32 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Business Fluctuations; Cycles
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • O41 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - One, Two, and Multisector Growth Models

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