The uniqueness of company size distribution function from tent-shaped growth rate distribution
classification
⚛️ physics.soc-ph
q-fin.GN
keywords
distributionapproximationsgrowthratedatafunctiongibratprofits
read the original abstract
We report the proof that the extension of Gibrat's law in the middle scale region is unique and the probability distribution function (pdf) is also uniquely derived from the extended Gibrat's law and the law of detailed balance. In the proof, two approximations are employed. The pdf of growth rate is described as tent-shaped exponential functions and the value of the origin of the growth rate distribution is constant. These approximations are confirmed in profits data of Japanese companies 2003 and 2004. The resultant profits pdf fits with the empirical data with high accuracy. This guarantees the validity of the approximations.
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