IDEAS home Printed from https://ideas.repec.org/a/spr/eaiere/v21y2024i2d10.1007_s40844-024-00283-1.html
   My bibliography  Save this article

Mixtures of log-normal distributions in the mid-scale range of firm-size variables

Author

Listed:
  • Arturo Ramos

    (Universidad de Zaragoza)

  • Till Massing

    (Universität Duisburg-Essen)

  • Atushi Ishikawa

    (Kanazawa Gakuin University)

  • Shouji Fujimoto

    (Kanazawa Gakuin University)

  • Takayuki Mizuno

    (National Institute of Informatics
    The Graduate University for Advanced Studies [SOKENDAI]
    The University of Tokyo)

Abstract

In econophysics, firm sales and other firm-size variables follow a power-law distribution in the large-scale range and a log-normal distribution in the mid-scale range. Employing sales (operating revenues) data, we statistically tested the validity of this assertion by applying log-normal distributions and mixtures of them to the comprehensive data available in ORBIS, the world’s largest commercial database on corporate finance. The results confirm that the validity of explaining the entire range of firm-size variables with a single log-normal distribution is extremely low. We also confirmed the statistical superiority of the mid-scale range, which conventionally follows a single log-normal distribution in econophysics, described as a mixture of three log-normal distributions. This result is likely due to the observed effect of the superposition of at least a few industries, such as manufacturing, non-manufacturing, and others.

Suggested Citation

  • Arturo Ramos & Till Massing & Atushi Ishikawa & Shouji Fujimoto & Takayuki Mizuno, 2024. "Mixtures of log-normal distributions in the mid-scale range of firm-size variables," Evolutionary and Institutional Economics Review, Springer, vol. 21(2), pages 249-260, September.
    • Handle: RePEc:spr:eaiere:v:21:y:2024:i:2:d:10.1007_s40844-024-00283-1
    DOI: 10.1007/s40844-024-00283-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40844-024-00283-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40844-024-00283-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Log-normal; Mixtures; Firm-size distribution;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D39 - Microeconomics - - Distribution - - - Other
    • L25 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Performance

    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:spr:eaiere:v:21:y:2024:i:2:d:10.1007_s40844-024-00283-1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.