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Statistical properties in firms' lar...

Ishikawa, Atushi.

Statistical properties in firms' large-scale data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical properties in firms' large-scale databy Atushi Ishikawa.
Author:	Ishikawa, Atushi.
Published:	Singapore :Springer Singapore :2021.
Description:	xv, 140 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	FinanceStatistics.
Online resource:	https://doi.org/10.1007/978-981-16-2297-7
ISBN:	9789811622977$q(electronic bk.)

Statistical properties in firms' large-scale data
Ishikawa, Atushi.

Statistical properties in firms' large-scale data[electronic resource] /by Atushi Ishikawa. - Singapore :Springer Singapore :2021. - xv, 140 p. :ill. (some col.), digital ;24 cm. - Evolutionary economics and social complexity science,v.262198-4204 ;. - Evolutionary economics and social complexity science ;v.1..

Chapter 1. Introduction -- Chapter 2. Non-Gibrat's Property in the Mid-scale Range -- Chapter 3. Quasi-statistically Varying Power-law and Log-normal Distributions -- Chapter 4. Extension of Non-Gibrat's Property -- Chapter 5. Long-term Firm Growth Derived from Non-Gibrat's Property and Gibrat's Law -- Chapter 6. Firm-age Distribution and the Inactive Rate of Firms -- Chapter 7. Statistical Properties in Inactive Rate of Firms -- Chapter 8. Power Laws with Different Exponents in Firm-Size Variables -- Chapter 9. Why does Production Function Take the Cobb-Douglas Form?.

This is the first book to provide a systematic description of statistical properties of large-scale financial data. Specifically, the power-law and log-normal distributions observed at a given time and their changes using time-reversal symmetry, quasi-time-reversal symmetry, Gibrat's law, and the non-Gibrat's property observed in a short-term period are derived here. The statistical properties observed over a long-term period, such as power-law and exponential growth, are also derived. These subjects have not been thoroughly discussed in the field of economics in the past, and this book is a compilation of the author's series of studies by reconstructing the data analyses published in 15 academic journals with new data. This book provides readers with a theoretical and empirical understanding of how the statistical properties observed in firms' large-scale data are related along the time axis. It is possible to expand this discussion to understand theoretically and empirically how the statistical properties observed among differing large-scale financial data are related. This possibility provides readers with an approach to microfoundations, an important issue that has been studied in economics for many years.

ISBN: 9789811622977$q(electronic bk.)

Standard No.: 10.1007/978-981-16-2297-7doiSubjects--Topical Terms:

897749
Finance
--Statistics.

LC Class. No.: HG176.5 / .I75 2021

Dewey Class. No.: 332.015195

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505 0 $a Chapter 1. Introduction -- Chapter 2. Non-Gibrat's Property in the Mid-scale Range -- Chapter 3. Quasi-statistically Varying Power-law and Log-normal Distributions -- Chapter 4. Extension of Non-Gibrat's Property -- Chapter 5. Long-term Firm Growth Derived from Non-Gibrat's Property and Gibrat's Law -- Chapter 6. Firm-age Distribution and the Inactive Rate of Firms -- Chapter 7. Statistical Properties in Inactive Rate of Firms -- Chapter 8. Power Laws with Different Exponents in Firm-Size Variables -- Chapter 9. Why does Production Function Take the Cobb-Douglas Form?.
520 $a This is the first book to provide a systematic description of statistical properties of large-scale financial data. Specifically, the power-law and log-normal distributions observed at a given time and their changes using time-reversal symmetry, quasi-time-reversal symmetry, Gibrat's law, and the non-Gibrat's property observed in a short-term period are derived here. The statistical properties observed over a long-term period, such as power-law and exponential growth, are also derived. These subjects have not been thoroughly discussed in the field of economics in the past, and this book is a compilation of the author's series of studies by reconstructing the data analyses published in 15 academic journals with new data. This book provides readers with a theoretical and empirical understanding of how the statistical properties observed in firms' large-scale data are related along the time axis. It is possible to expand this discussion to understand theoretically and empirically how the statistical properties observed among differing large-scale financial data are related. This possibility provides readers with an approach to microfoundations, an important issue that has been studied in economics for many years.
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