Statistical models for company growth

Matthieu Wyart, Jean Philippe Bouchaud

    Research output: Contribution to journalArticlepeer-review

    Abstract

    We study Sutton's 'microcanonical' model for the internal organization of firms, that leads to non-trivial scaling properties for the statistics of growth rates. We show that the growth rates are asymptotically Gaussian in this model, whereas empirical results suggest that the kurtosis of the distribution increases with size. We also obtain the conditional distribution of the number and size of sub-sectors in Sutton's model. We formulate and solve an alternative model, based on the assumption that the sector sizes follow a power-law distribution. We find in this new model both anomalous scaling of the variance of growth rates and non-Gaussian asymptotic distributions. We give some testable predictions of the two models that would differentiate them further. We also discuss why the growth rate statistics at the country level and at the company level should be identical.

    Original languageEnglish (US)
    Pages (from-to)241-255
    Number of pages15
    JournalPhysica A: Statistical Mechanics and its Applications
    Volume326
    Issue number1-2
    DOIs
    StatePublished - Aug 1 2003

    Keywords

    • Corporate growth
    • Pareto distribution
    • Scaling
    • Size distribution

    ASJC Scopus subject areas

    • Statistics and Probability
    • Condensed Matter Physics

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