Abstract
In this study, we observe the dependence of the inactive rate of firms on firm-size variables: total revenue, net income, total assets, and net assets. This is achieved using information on nearly all firms in Japan, Germany, Spain, France, the United Kingdom, Italy, Korea, and the Netherlands recorded in the Orbis database in 2015 and 2016. Here, the inactive rate means the transition rate of firms from an active state to an inactive state. First, we confirm that the financial variables in this database follow power laws in the range of large-scale data values but follow log-normal distributions in the range of mid-scale data values. Furthermore, we observe that the inactive rate of firms is constant regardless of the firm-size variables in the large-scale data range. Meanwhile, the inactive rate increases under a power-law function as financial variables decrease in the mid-scale data range. We also find that the boundary between the large- and mid-scale data ranges of the inactive rate of firms corresponds to the boundary between the power-law and log-normal distributions of the financial variables.
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Notes
Not only in Japan but also in other countries studied here, it was not clearly observed that the inactive rate of firms takes a constant value regardless of net income or net assets in the large-scale data range of the negative value. This is probably because data of the negative value is not necessarily exhaustive. In Italy, compared to other countries studied in this paper, it is thought that coverage of data of negative values was high.
References
Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Financ 23(4):589
Bottazzi G, Secchi A, Tamagni F (2008) Productivity, profitability and financial performance. Ind Corp Change 17:711
Clauset A, Shalizi CR, Newman MEJ (2009) Power-law distributions in empirical data. SIAM Rev 51:661
Coad A (2010) The exponential age distribution and the Pareto firm size distribution. J Ind Compet Trade 10:389
Coad A (2010) Investigating the exponential age distribution of firms. Economics 4:2010–17
Coad A, Tamvada JP (2008) The growth and decline of small firms in developing countries. Papers on economics and evolution 2008-08, Max Planck Institute of Economics
Fujiwara Y (2004) Zipf law in firms bankruptcy. Phys A 337:219
Fujiwara Y, Souma W, Aoyama H, Kaizoji T, Aoki M (2003) Growth and fluctuations of personal income. Phys A 321:598
Fujiwara Y, Guilmi CD, Aoyama H, Gallegati M, Souma W (2004) Do Pareto–Zipf and Gibrat laws hold true? An analysis with European firms. Phys A 335:197
Gibra R (1932) Les Inégalités économique. Sirey, Paris
Ishikawa A (2006) Derivation of the distribution from extended Gibrat’s law. Phys A 367:425
Ishikawa A (2007) The uniqueness of firm size distribution function from tent-shaped growth rate distribution. Phys A 383:79
Ishikawa A, Fujimoto S, Mizuno T, Watanabe T (2016) Firm Growth function and extended-Gibrat’s property. Adv Math Phys 2016:Article ID 9303480. https://doi.org/10.1155/2016/9303480
Ishikawa A, Fujimoto S, Mizuno T, Watanabe T (2016) Long-term firm growth properties derived from short-term laws of sales and number of employees in Japan and France. Evol Inst Econ Rev 13:409. https://doi.org/10.1007/s40844-016-0055-0
Ishikawa A, Fujimoto S, Mizuno T, Tsutomu W (2017) Dependence of the decay rate of firm activities on firm age. Evol Inst Econ Rev 14:351–362. https://doi.org/10.1007/s40844-017-0084-3
Ishikawa A, Fujimoto S, Mizuno T, Watanabe T (2017) Transition law of firms’ activity and the deficit aspect of non-Gibrat’s law. JPS Conf Proc 16:011005. https://doi.org/10.7566/JPSCP.16.011005
Ishikawa A, Fujimoto, S, Mizuno T, Watanabe T (2015) The relation between firm age distributions and the decay rate of firm activities in the United States and Japan, 2015 IEEE international conference on big data, pp 2726–2731. https://doi.org/10.1109/BigData.2015.7364073
Ishikawa A, Fujimoto S, Mizuno T, Watanabe T (2015) Firm age distributions and the decay rate of firm activities. In: Takayasu H, Ito N, Noda I, Takayasu M (eds) Proceedings of the international conference on social modeling and simulation, plus Econophysics Colloquium 2014, pp 187–194 (2015)
Miura W, Takayasu H, Takayasu M (2012) Effect of coagulation of nodes in an evolving complex network. Phys Rev Lett 108:168701
Newman MEJ (2005) Power laws, Pareto distributions and Zipf’s law. Contemp Phys 46:323
Pareto V (1897) Cours d’Économie politique. Macmillan, London
Stanley MHR, Buldyrev SV, Havlin S, Mantegna R, Salinger MA, Stanley HE (1995) Zipf plots and the size distribution of firms. Econ Lett 49:453
Sutton J (1997) Gibrat’s legacy. J Econ Lit 35:40
Tomoyose M, Fujimoto S, Ishikawa A (2009) Non-Gibrat’s law in the middle scale region. Prog Theor Phys Suppl 179:114
Acknowledgements
The authors thank the Yukawa Institute for Theoretical Physics (YITP) at Kyoto University. Discussions during the YITP workshop (YITP-W-17-14) on “Econo-physics 2017” provided a useful reference in completing this work.
Funding
This study was supported by JSPS KAKENHI Grant numbers 17K01277, 16H05904, and 18H03629, as well as funding for open collaborative research at the National Institute of Informatics (NII), Japan (FY2017).
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Ishikawa, A., Fujimoto, S. & Mizuno, T. Statistical law observed in inactive rate of firms. Evolut Inst Econ Rev 16, 201–212 (2019). https://doi.org/10.1007/s40844-018-0119-4
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DOI: https://doi.org/10.1007/s40844-018-0119-4