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Titlebook: Statistical Properties in Firms’ Large-scale Data; Atushi Ishikawa Book 2021 The Editor(s) (if applicable) and The Author(s), under exclus

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11#
發(fā)表于 2025-3-23 11:46:25 | 只看該作者
ategies.Foreword by Paul H. Sugarbaker, MD, Director, Progra.Recent developments in regional and systemic anticancer therapies have improved the grim outlook of patients with peritoneal carcinomatosis (PC) from ovarian or gastrointestinal origin, leading to a renewed interest in both the underlying
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發(fā)表于 2025-3-23 15:05:56 | 只看該作者
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發(fā)表于 2025-3-23 21:53:29 | 只看該作者
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發(fā)表于 2025-3-23 23:28:37 | 只看該作者
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發(fā)表于 2025-3-24 04:21:52 | 只看該作者
,Why Does Production Function Take the Cobb–Douglas Form?,ty with a quasi-inverse symmetry of variables. Based on the above discussion, we theoretically clarified why the Cobb–Douglas production function is better fit to empirical data in economics, because it uniquely derives the fact that their variables follow a power-law distribution.
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發(fā)表于 2025-3-24 09:55:16 | 只看該作者
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發(fā)表于 2025-3-24 14:04:15 | 只看該作者
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發(fā)表于 2025-3-24 18:28:48 | 只看該作者
,Non-Gibrat’s Property in the Mid-Scale Range,sets, current profits, and the number of employees. This is called Gibrat’s law. On the other hand, in the mid-scale range of firm-size variables, the growth-rate distribution changes regularly based on the initial value. This idea is referred to as the non-Gibrat’s property in this book. In this ch
19#
發(fā)表于 2025-3-24 20:35:16 | 只看該作者
20#
發(fā)表于 2025-3-24 23:18:52 | 只看該作者
,Extension of Non-Gibrat’s Property, a log-normal distribution in the mid-scale range in a certain year. Also, observing such short-term changes as two consecutive years, there is a time-reversal symmetry in the joint probability density function of such firm-size variables over “a certain year” and “next year.” Furthermore, Gibrat’s
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