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Heterogeneity in the Harrodian sentiment dynamics, entailing also some scope for stability

  • Reiner FrankeEmail author
Regular Article
  • 15 Downloads

Abstract

Drawing on recent ideas in the literature to model ‘animal spirits’, the paper considers the investment of heterogeneous firms that probabilistically switch between optimism and pessimism. Combining the herding component in the endogenous transition probabilities with a Harrodian feedback, a one-dimensional macroeconomic adjustment equation is set up. Assuming a ‘neutral’ herding coefficient and considering the local dynamics around the steady state with normal utilization, the equation shows a one-to-one correspondence with the neo-Kaleckian baseline model of Harrodian instability. The paper thus provides a rigorous specification of its sentiment adjustment story. In a second and innovative step, the firms are additionally allowed to be neutral. In this variant, up to three ‘fully-adjusted’ steady states come into being, which, however, cannot be distinguished from a macroeconomic point of view. While two of them exhibit the usual instability, it turns out that the equilibrium with the highest share of neutral agents can easily be locally stable. The result shows that the common macroeconomic view of Harrodian instability that essentially treats all firms alike may be too simple. Also, the economic significance of the paper’s findings goes beyond the present very limited framework.

Keywords

Agent-based modelling Three-state sentiment dynamics Multiple equilibria Herding Phase diagrams 

JEL Classification

C63 D21 E12 E30 

Notes

Acknowledgments

I wish to thank two anonymous referees for their constructive comments as well as Peter Skott for his remarks on a first draft, which led me to (try to) clarify some important points.

Funding

The author declares that he received no funds in connection with this article.

Compliance with Ethical Standards

Conflict of interests

No conflict of interest.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.University of Kiel (GER)KielGermany

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