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“Animal spirits” and bank’s lending behaviour, a disequilibrium approach

  • Carl Chiarella , Corrado Di Guilmi and Tianhao Zhi EMAIL logo
Published/Copyright: March 12, 2019
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Studies in Nonlinear Dynamics & Econometrics
From the journal Studies in Nonlinear Dynamics & Econometrics Volume 24 Issue 2

Abstract

The paper analyses from a disequilibrium perspective the role of banks’ “animal spirits” and collective behaviour in the creation of credit that, ultimately, determines the credit cycle. In particular, we propose a dynamic model to analyse how the transmission of waves of optimism and pessimism in the supply side of the credit market interacts with the business cycle. We adopt the Weidlich-Haag-Lux approach to model the opinion contagion of bankers. We test different assumptions on banks’ behaviour and find that opinion contagion and herding amongst banks play an important role in propagating the credit cycle and destabilizing the real economy. The boom phases trigger banks’ optimism that collectively lead the banks to lend excessively, thus reinforcing the credit bubble. Eventually the bubbles collapse due to an over-accumulation of debt, leading to a restrictive phase in the credit cycle.

Keywords: animal spirits; contagion; financial fragility; pro-cyclical credit cycle
JEL Classification: E12; E17; E32; G21

Acknowledgement

The authors would like to thank Frederique Bracoud, Tony He, Steve Keen, Keith Woodward, the participants to the WEHIA 2013, NED 2013 and SNDE 2014 conferences, and to the SydneyAgents seminar at the University of Technology, Sydney, and an anonymous referee for valuable feedback and comments. The usual disclaimer applies.

A Simulation results

Figure 2: The isocline of 2D model with $\dot{y}=0$y˙=0 (straight line) and $\dot{x}=0$x˙=0.
Figure 2:

The isocline of 2D model with y˙=0 (straight line) and x˙=0.

Figure 3: Simulations of the baseline model.
Figure 3:

Simulations of the baseline model.

Figure 4: The 4D model: representative simulation (top left panel: simulation over 600 periods; other panels: magnification over 100 periods.)
Figure 4:

The 4D model: representative simulation (top left panel: simulation over 600 periods; other panels: magnification over 100 periods.)

Figure 5: The 4D model: bifurcation diagrams.
Figure 5:

The 4D model: bifurcation diagrams.

Figure 6: The 4D model: bifurcation diagram for λm and x.
Figure 6:

The 4D model: bifurcation diagram for λm and x.

Figure 7: The 4D model: bifurcation diagram for λm and y.
Figure 7:

The 4D model: bifurcation diagram for λm and y.

Figure 8: The Kaldorian I-S disequilibrium.
Figure 8:

The Kaldorian I-S disequilibrium.

Figure 9: The 5D model with Kaldorian I-S Disequilibrium.
Figure 9:

The 5D model with Kaldorian I-S Disequilibrium.

Figure 10: The extended 7D model with a speculative financial sector.
Figure 10:

The extended 7D model with a speculative financial sector.

Figure 11: Bifurcation diagram: the effect of Tobin-type tax.
Figure 11:

Bifurcation diagram: the effect of Tobin-type tax.

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Published Online: 2019-03-12

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https://doi.org/10.1515/snde-2016-0095
Keywords for this article
animal spirits; contagion; financial fragility; pro-cyclical credit cycle

Articles in the same Issue

  1. Research Articles
  2. Constrained interest rates and changing dynamics at the zero lower bound
  3. A threshold mixed count time series model: estimation and application
  4. Temporal aggregation of random walk processes and implications for economic analysis
  5. Forecasting the unemployment rate over districts with the use of distinct methods
  6. Risk shocks with time-varying higher moments
  7. Fiscal policy uncertainty and US output
  8. “Animal spirits” and bank’s lending behaviour, a disequilibrium approach
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