Scaling behavior in economics: II. Modeling of company growth

S. Buldyrev, L. A. Amaral, L. A. Amaral, S. Havlin, S. Havlin, H. Leschhorn, P. Maass, M. Salinger, H. Stanley, M. H. Stanley
{"title":"Scaling behavior in economics: II. Modeling of company growth","authors":"S. Buldyrev, L. A. Amaral, L. A. Amaral, S. Havlin, S. Havlin, H. Leschhorn, P. Maass, M. Salinger, H. Stanley, M. H. Stanley","doi":"10.1051/jp1:1997181","DOIUrl":null,"url":null,"abstract":"In the preceding paper we presented empirical results describing the growth of publicly-traded United States manufacturing firms within the years 1974--1993. Our results suggest that the data can be described by a scaling approach. Here, we propose models that may lead to some insight into these phenomena. First, we study a model in which the growth rate of a company is affected by a tendency to retain an ``optimal'' size. That model leads to an exponential distribution of the logarithm of the growth rate in agreement with the empirical results. Then, we study a hierarchical tree-like model of a company that enables us to relate the two parameters of the model to the exponent $\\beta$, which describes the dependence of the standard deviation of the distribution of growth rates on size. We find that $\\beta = -\\ln \\Pi / \\ln z$, where $z$ defines the mean branching ratio of the hierarchical tree and $\\Pi$ is the probability that the lower levels follow the policy of higher levels in the hierarchy. We also study the distribution of growth rates of this hierarchical model. We find that the distribution is consistent with the exponential form found empirically.","PeriodicalId":14774,"journal":{"name":"Journal De Physique Ii","volume":"9 1","pages":"635-650"},"PeriodicalIF":0.0000,"publicationDate":"1997-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"118","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal De Physique Ii","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1051/jp1:1997181","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 118

Abstract

In the preceding paper we presented empirical results describing the growth of publicly-traded United States manufacturing firms within the years 1974--1993. Our results suggest that the data can be described by a scaling approach. Here, we propose models that may lead to some insight into these phenomena. First, we study a model in which the growth rate of a company is affected by a tendency to retain an ``optimal'' size. That model leads to an exponential distribution of the logarithm of the growth rate in agreement with the empirical results. Then, we study a hierarchical tree-like model of a company that enables us to relate the two parameters of the model to the exponent $\beta$, which describes the dependence of the standard deviation of the distribution of growth rates on size. We find that $\beta = -\ln \Pi / \ln z$, where $z$ defines the mean branching ratio of the hierarchical tree and $\Pi$ is the probability that the lower levels follow the policy of higher levels in the hierarchy. We also study the distribution of growth rates of this hierarchical model. We find that the distribution is consistent with the exponential form found empirically.
经济学中的规模行为:2。公司成长模型
在前一篇论文中,我们提出了描述1974- 1993年间美国上市制造业公司增长的实证结果。我们的结果表明,数据可以用标度方法来描述。在这里,我们提出的模型可能会导致对这些现象的一些见解。首先,我们研究了一个模型,在这个模型中,公司的增长率受到保持“最优”规模的趋势的影响。该模型得出增长率的对数呈指数分布,与实证结果一致。然后,我们研究了一个公司的分层树状模型,使我们能够将模型的两个参数与指数$\beta$联系起来,该指数描述了增长率分布的标准差对规模的依赖。我们发现$\beta = -\ln \Pi / \ln z$,其中$z$定义了层次树的平均分支比,$\Pi$是层次树中较低层次遵循较高层次策略的概率。本文还研究了该分层模型的增长率分布。我们发现分布与经验发现的指数形式是一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信