IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1506.07582.html
   My bibliography  Save this paper

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1506.07582
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. N. G. Mankiw, 2009. "The Macroeconomist as Scientist and Engineer," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 5.
    2. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    3. Hyman P. Minsky, 1975. "Financial Resources in a Fragile Financial Environment," Challenge, Taylor & Francis Journals, vol. 18(3), pages 6-13, July.
    4. Charles Whalen, 2008. "Understanding the Credit Crunch as a Minsky Moment," Challenge, Taylor & Francis Journals, vol. 51(1), pages 91-109.
    5. Oded Galor, 1996. "Discrete Dynamical Systems," Working Papers 96-23, Brown University, Department of Economics.
    6. 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.
    7. Oded Galor, 2007. "Discrete Dynamical Systems," Springer Books, Springer, edition 1, number 978-3-540-36776-5, December.
    8. Charles P. Kindleberger & Robert Z. Aliber, 2005. "Manias, Panics and Crashes," Palgrave Macmillan Books, Palgrave Macmillan, edition 0, number 978-0-230-62804-5.
    9. 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.
    10. John Hicks, 1981. ""IS-LM": An Explanation," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 3(2), pages 139-154, January.
    11. 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.
    12. Levy, Haim & Levy, Moshe & Solomon, Sorin, 2000. "Microscopic Simulation of Financial Markets," Elsevier Monographs, Elsevier, edition 1, number 9780124458901.
    13. Alessandro Vercelli, 2011. "A Perspective on Minsky Moments: Revisiting the Core of the Financial Instability Hypothesis," Review of Political Economy, Taylor & Francis Journals, vol. 23(1), pages 49-67.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Döpke Jörg & Fritsche Ulrich & Waldhof Gabi, 2019. "Theories, Techniques and the Formation of German Business Cycle Forecasts : Evidence from a survey of professional forecasters," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 239(2), pages 203-241, April.
    3. Döpke, Jörg & Fritsche, Ulrich & Waldhof, Gaby, 2017. "Theories, techniques and the formation of German business cycle forecasts. Evidence from a survey among professional forecasters," Working Papers 2, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    4. Roy, Saktinil & Kemme, David M., 2012. "Causes of banking crises: Deregulation, credit booms and asset bubbles, then and now," International Review of Economics & Finance, Elsevier, vol. 24(C), pages 270-294.
    5. Christensen, Bent Jesper & Nielsen, Morten Ørregaard & Zhu, Jie, 2015. "The impact of financial crises on the risk–return tradeoff and the leverage effect," Economic Modelling, Elsevier, vol. 49(C), pages 407-418.
    6. Strulik, Holger & Werner, Katharina, 2014. "Elite education, mass education, and the transition to modern growth," University of Göttingen Working Papers in Economics 205, University of Goettingen, Department of Economics.
    7. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2019. "Does machine learning help us predict banking crises?," Journal of Financial Stability, Elsevier, vol. 45(C).
    8. Carl-Johan Dalgaard & Holger Strulik, 2015. "The physiological foundations of the wealth of nations," Journal of Economic Growth, Springer, vol. 20(1), pages 37-73, March.
    9. Quamrul Ashraf & Oded Galor, 2011. "Cultural Diversity, Geographical Isolation, and the Origin of the Wealth of Nations," Working Papers 2011-16, Brown University, Department of Economics.
    10. Andreas Irmen, 2021. "Automation, growth, and factor shares in the era of population aging," Journal of Economic Growth, Springer, vol. 26(4), pages 415-453, December.
    11. Luiz Carlos Bresser-Pereira, 2010. "The global financial crisis and a new capitalism?," Journal of Post Keynesian Economics, Taylor & Francis Journals, vol. 32(4), pages 499-534, July.
    12. Beutel, Johannes & List, Sophia & von Schweinitz, Gregor, 2018. "An evaluation of early warning models for systemic banking crises: Does machine learning improve predictions?," Discussion Papers 48/2018, Deutsche Bundesbank.
    13. Gabrisch, Hubert & Orlowski, Lucjan T., 2010. "The Extreme Risk Problem for Monetary Policies of the Euro-Candidates," IWH Discussion Papers 12/2010, Halle Institute for Economic Research (IWH).
    14. Takashi Kamihigashi, 2011. "Recurrent Bubbles," The Japanese Economic Review, Japanese Economic Association, vol. 62(1), pages 27-62, March.
    15. Hiroaki Kaido & Kaspar Wüthrich, 2021. "Decentralization estimators for instrumental variable quantile regression models," Quantitative Economics, Econometric Society, vol. 12(2), pages 443-475, May.
    16. Susan Lund & Charles Roxburgh, 2010. "Debt and Deleveraging," World Economics, World Economics, 1 Ivory Square, Plantation Wharf, London, United Kingdom, SW11 3UE, vol. 11(2), pages 1-30, April.
    17. Salter, Alexander William & Tarko, Vlad, 2017. "Polycentric banking and macroeconomic stability," Business and Politics, Cambridge University Press, vol. 19(2), pages 365-395, June.
    18. Battigalli, Pierpaolo & Panebianco, Fabrizio & Pin, Paolo, 2023. "Learning and selfconfirming equilibria in network games," Journal of Economic Theory, Elsevier, vol. 212(C).
    19. Varvarigos, Dimitrios & Gil-Moltó, Maria José, 2016. "Endogenous Market Structure, Occupational Choice, And Growth Cycles," Macroeconomic Dynamics, Cambridge University Press, vol. 20(1), pages 70-94, January.
    20. Amer Tabakovic, 2015. "On the Characterization of Steady-States in Three-Dimensional Discrete Dynamical Systems," DEM Discussion Paper Series 15-16, Department of Economics at the University of Luxembourg.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1506.07582. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.