A Compositional Data Analysis of Market Share Dynamics

Author Name ARATA Yoshiyuki (Fellow, RIETI) / ONOZAKI Tamotsu (Rissho University)
Creation Date/NO. May 2017 17-E-076
Research Project Sustainable Growth and Macroeconomic Policy
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The existing literature has shown that there are several statistical regularities in industrial dynamics, which are an important clue to understanding the underlying mechanism. This paper focuses on market share changes and shows that its distribution has some remarkable properties. Because of the constrained nature of market share, namely, the sum must be unity, this paper applies the recently developed method called compositional data analysis (CDA) to market share data. We find the distribution does not follow a Gaussian but instead a tent-shaped distribution with a fatter tail, which is closely related with the findings of firm growth rate distribution. With some exceptions, this statistical feature can be observed across different sectors. Furthermore, this property can be observed when we focus on the relation between the top subgroup and lower-ranked firms. This distribution shape implies that market share growth cannot be described by an accumulation of small shocks. Rather, lumpy jumps that transform the market structure are crucial in market share dynamics. Put differently, radical change in market structure is a relatively frequent phenomenon. Such implications based on statistical properties of observed data help us further investigate industrial dynamics theoretically.