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Financial Fragility, Patterns Of Firms' Entry And Exit And Aggregate Dynamics

Listed author(s):
  • Domenico Delli Gatti, Mauro Gallegati, Gianfranco Giulioni, Antonio Palestrini, -DISCUSSANT: Thomas Brenner

Recent literature stresses the drawbacks of the representative agent ap-proach. A growing number of contributions construct model which allows for agents heterogeneity [1, 2] while others claim that aggregate phenomena could be explained by the failure of the law of large numbers rather than by exogenous shocks (see [3] for instance). Another strand of literature stresses the importance of financial factors in determining the behavior of real vari-ables [4, 5, 6]. A few recent papers combine the two concepts. They show that a measure of dispersion of the distribution, other than its average value, matters for the dynamics of the aggregate variable, i.e., one should consider the whole (statistical) distribution of individual variables [7]. Of course, this distribution is heavy in uenced by the "entry-exit" process: bankruptcy eliminates the "worse" tail of the distribution, while the characteristics of the entrants modify it. Some analytical results has been already reached within such a framework [8].The goal of this paper is to verify if and how information availability on the credit market affects the economic dynamics and the distribution of firms with respect to their financial position and size. Moreover, ows into and out of the industry could be affected by credit availability. Our results show that the mean level and the variance of indebtedness of the system varies with the availability of information. In particular, if information is asymmetric the firmsÆ leverage ratio (as proxied by the ratio of corporate debt to capital) is higher and varies very smoothly. Aggregate output is also higher when firms are very leveraged and uctuations are amplified. Since the share of more leveraged firms is procyclical, cyclical downturns are driven by the exit process. We may therefore state that, according to this model, firmsÆ financial distribution movements drive the business cycle. Our results are corroborated by an econometric analysis of the model (European data 1960:I-1997:IV).We construct an agent based model on the basis of [9]. Differently from it, we introduce a credit supply curve from the profit maximization problem of the bank. This allows us to determinate the credit equilibrium conditions for each firm. The "bank problem" deserves some explanation since it in-troduces us to the "spatial structure" of the model. Because of information imperfections, banks do not know the "true" capital level of each firm and subscribe a standard debt contract with debtors: i.e., when debt is greater than capital, the bank takes all the capital. "Lemon" firms are allowed to reduce their capital to zero if the bank asks its money back. In such a case, a bank which finances a lemon firm, may lost all the loan. We assume that the bank activity is concentrated in a local zone and we endow a bank with a square lattice filled with firms to finance. By means of a "research center" the bank knows the average level of the surrounding firmsÆ capital: i.e. it knows only the average level of the financial indicator. We also assume that the share of the lemon firms is a positive function of the mean leverage ratio of the zone. It is possible now to deal with the heterogeneity of the financial position of the firms and interaction among agents (in the case in point, there is indirect interaction through banks.)The entry exit rules are modelled as follows. The exit rules are straight-forward in this framework. First, if a firm is very leveraged, it can judge that the advantage to remain on the credit market is lower than the bur-den of debt commitments (these are the lemon firms) and leaves the market. Secondly, if a firm demands for too much credit, the bank may adopt credit rationing policies. Even this kind of firm leaves the market, even if it is able to repay all the credit. In this case the banks avoids the formation of new lemons.For the entry process we exploit our spatial structure drawn from physics field, in particular from the model of magnetization. We endow each site of our lattice with a structure enclosing its four nearest neighbors. If a site is full, nothing happens and the firm goes ahead with its activity. If the site is empty, itÆs filled according to a Gibbs probability distribution with a nearest neighbors potential with anti-ferromagnetic characteristics. This means that the probability of entry rises with the number of empty neighbors. Such a rule has proven to be very useful when we consider more banks, i.e. more zones. In this situation we can analyze the case in which the firm care about credit conditions in the entry decision. If more zones are present, we let the exponent of our Gibbs distribution to depend positively on the financial situation: all in all, the probability of a birth is higher in the zones where credit conditions are favorable.

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Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 282.

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Date of creation: 05 Jul 2000
Handle: RePEc:sce:scecf0:282
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CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain

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  1. Kiyotaki, Nobuhiro & Moore, John, 1997. "Credit Cycles," Journal of Political Economy, University of Chicago Press, vol. 105(2), pages 211-248, April.
  2. Jonas D.M. Fisher, 1998. "Credit market imperfections and the heterogeneous response of firms to monetary shocks," Working Paper Series, Macroeconomic Issues 96-23, Federal Reserve Bank of Chicago.
  3. Sidney G. Winter & Yuri M. Kaniovski & Giovanni Dosi, 2003. "A Baseline Model of Industry Evolution," LEM Papers Series 2003/12, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  4. Williamson, Stephen D., 1996. "Real business cycle research comes of age: A review essay," Journal of Monetary Economics, Elsevier, vol. 38(1), pages 161-170, August.
  5. Ricardo J. Caballero & Eduardo Engel & John Haltiwanger, 1996. "Aggregate Employment Dynamics: Building from Microeconomic Evidence," Documentos de Trabajo 6, Centro de Economía Aplicada, Universidad de Chile.
  6. Baldwin,John R. & Gorecki,Paul, 1998. "The Dynamics of Industrial Competition," Cambridge Books, Cambridge University Press, number 9780521633574, December.
  7. Richard E. Caves, 1998. "Industrial Organization and New Findings on the Turnover and Mobility of Firms," Journal of Economic Literature, American Economic Association, vol. 36(4), pages 1947-1982, December.
  8. Bruce C. Greenwald & Joseph E. Stiglitz, 1988. "Financial Market Imperfections and Business Cycles," NBER Working Papers 2494, National Bureau of Economic Research, Inc.
  9. Klepper, Steven, 1996. "Entry, Exit, Growth, and Innovation over the Product Life Cycle," American Economic Review, American Economic Association, vol. 86(3), pages 562-583, June.
  10. Pietro Reichlin & Paolo Siconolfi, 1998. "Adverse Selection of Investment Projects and the Business Cycle," Temi di discussione (Economic working papers) 326, Bank of Italy, Economic Research and International Relations Area.
  11. Steven M. Fazzari & R. Glenn Hubbard & BRUCE C. PETERSEN, 1988. "Financing Constraints and Corporate Investment," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 19(1), pages 141-206.
  12. Thomas F. Cooley & Vincenzo Quadrini, 2001. "Financial Markets and Firm Dynamics," American Economic Review, American Economic Association, vol. 91(5), pages 1286-1310, December.
  13. Bernanke, B. & Gertler, M. & Gilchrist, S., 1998. "The Financial Accelerator in a Quantitative Business Cycle Framework," Working Papers 98-03, C.V. Starr Center for Applied Economics, New York University.
  14. Hopenhayn, Hugo A, 1992. "Entry, Exit, and Firm Dynamics in Long Run Equilibrium," Econometrica, Econometric Society, vol. 60(5), pages 1127-1150, September.
  15. Lucas, Robert E., 1977. "Understanding business cycles," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 5(1), pages 7-29, January.
  16. Caballero, Ricardo J & Hammour, Mohamad L, 1994. "The Cleansing Effect of Recessions," American Economic Review, American Economic Association, vol. 84(5), pages 1350-1368, December.
  17. Luca Stanca & Domenico Delli Gatti & Mauro Gallegati, 1999. "Financial fragility, heterogeneous agents, and aggregate fluctuations: evidence from a panel of US firms," Applied Financial Economics, Taylor & Francis Journals, vol. 9(1), pages 87-99.
  18. Stanca, Luca & Gallegati, Mauro, 1999. "The Dynamic Relation between Financial Positions and Investment: Evidence from Company Account Data," Industrial and Corporate Change, Oxford University Press, vol. 8(3), pages 551-572, September.
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