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Too dynamic to fail. Empirical support for an autocatalytic model of Minsky's financial instability hypothesis

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  • Natasa Golo
  • David S. Bree
  • Guy Kelman
  • Leanne Usher
  • Marco Lamieri
  • Sorin Solomon

Abstract

Solomon and Golo [1] have recently proposed an autocatalytic (self-reinforcing) feedback model which couples a macroscopic system parameter (the interest rate), a microscopic parameter that measures the distribution of the states of the individual agents (the number of firms in financial difficulty) and a peer-to-peer network effect (contagion across supply chain financing). In this model, each financial agent is characterized by its resilience to the interest rate. Above a certain rate the interest due on the firm's financial costs exceeds its earnings and the firm becomes susceptible to failure (ponzi). For the interest rate levels under a certain threshold level, the firm loans are smaller then its earnings and the firm becomes 'hedge.' In this paper, we fit the historical data (2002-2009) on interest rate data into our model, in order to predict the number of the ponzi firms. We compare the prediction with the data taken from a large panel of Italian firms over a period of 9 years. We then use trade credit linkages to discuss the connection between the ponzi density and the network percolation. We find that the 'top-down'-'bottom-up' positive feedback loop accounts for most of the Minsky crisis accelerator dynamics. The peer-to-peer ponzi companies contagion becomes significant only in the last stage of the crisis when the ponzi density is above a critical value. Moreover the ponzi contagion is limited only to the companies that were not dynamic enough to substitute their distressed clients with new ones. In this respect the data support a view in which the success of the economy depends on substituting the static 'supply-network' picture with an interacting dynamic agents one.

Suggested Citation

  • Natasa Golo & David S. Bree & Guy Kelman & Leanne Usher & Marco Lamieri & Sorin Solomon, 2015. "Too dynamic to fail. Empirical support for an autocatalytic model of Minsky's financial instability hypothesis," Papers 1506.07582, arXiv.org, revised Jul 2015.
  • Handle: RePEc:arx:papers:1506.07582
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    References listed on IDEAS

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    1. Kindler, A. & Solomon, S. & Stauffer, D., 2013. "Peer-to-peer and mass communication effect on opinion shifts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 785-796.
    2. Solomon Sorin & Golo Natasa, 2013. "Minsky Financial Instability, Interscale Feedback, Percolation and Marshall–Walras Disequilibrium," Accounting, Economics, and Law: A Convivium, De Gruyter, vol. 3(3), pages 167-260, October.
    3. Oded Galor, 1996. "Discrete Dynamical Systems," Working Papers 96-23, Brown University, Department of Economics.
    4. N. G. Mankiw., 2009. "The Macroeconomist as Scientist and Engineer," VOPROSY ECONOMIKI, N.P. Redaktsiya zhurnala "Voprosy Economiki", vol. 5.
    5. Natasa Golo & Guy Kelman & David S. Bree & Leanne Usher & Marco Lamieri & Sorin Solomon, 2015. "Many-to-one contagion of economic growth rate across trade credit network of firms," Papers 1506.01734, arXiv.org.
    6. repec:mes:challe:v:18:y:1975:i:3:p:6-13 is not listed on IDEAS
    7. Charles Whalen, 2008. "Understanding the Credit Crunch as a Minsky Moment," Challenge, Taylor & Francis Journals, vol. 51(1), pages 91-109.
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    1. Natasa Golo & Guy Kelman & David S. Bree & Leanne Usher & Marco Lamieri & Sorin Solomon, 2015. "Many-to-one contagion of economic growth rate across trade credit network of firms," Papers 1506.01734, arXiv.org.

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