scholarly journals Exponential or Pareto: towards an evolution of equal opportunity

2021 ◽  
Author(s):  
Yong Tao
Keyword(s):  
Income Distribution ◽  
Exponential Distribution ◽  
Equal Opportunity ◽  
Pareto Distribution ◽  
Market Competition ◽  
Generalized Pareto Distribution ◽  
Underlying Mechanism ◽  
Matthew Effect ◽  
Ancient Egypt ◽  
The Matthew Effect

Abstract Pareto distribution and exponential distribution are related by the generalized Pareto distribution, which has been proposed to describe the income structure of the total population. The underlying mechanism for driving the Pareto distribution has been known as the Matthew effect of income accumulation. Today, the Pareto distribution has been observed universally in the richest class (1%~3% of populations); however, this distribution could dominate a larger proportion of populations when the investigation dated back to Renaissance Europe, Hungarian medieval society, and ancient Egypt. By contrast, the underlying mechanism for driving exponential income distribution is due to the equal opportunity of market competition, which radically differs from the Matthew effect. Here, we empirically find that, during the last 40 years, the income structures of different market-economy countries uniformly exhibit a two-class pattern, in which the great majority of populations obeys an exponential distribution and only the remaining (richest) part follows a Pareto distribution. In particular, we empirically show how the income structure in China evolved to an exponential distribution after the market-oriented economic reformation. The finding of a larger proportion of populations evolving to an exponential income distribution may reveal a potential trend of human civilization towards equal opportunity.

scholarly journals Exponential or Pareto: towards an evolution of equal opportunity

2021 ◽  
Author(s):  
Yong Tao
Keyword(s):  
Exponential Distribution ◽  
Equal Opportunity ◽  
Pareto Distribution ◽  
Market Competition ◽  
Generalized Pareto Distribution ◽  
Underlying Mechanism ◽  
Matthew Effect ◽  
Ancient Egypt ◽  
Class 1 ◽  
The Matthew Effect

Abstract Pareto distribution and exponential distribution are related by the generalized Pareto distribution, which has been proposed to describe the income structure of the total population. The underlying mechanism for driving the Pareto distribution has been known as the Matthew effect of income accumulation. Today, the Pareto distribution has been observed universally in the richest class (1%~3% of populations); however, this distribution could dominate a larger proportion of populations when the investigation dated back to Renaissance Europe, Hungarian medieval society, and ancient Egypt. By contrast, the underlying mechanism for driving exponential distribution is due to the equal opportunity of market competition, which radically differs from the Matthew effect. Here, we empirically find that, during the last 40 years, the income structure of different market-economy countries uniformly exhibits a two-class pattern, in which a larger proportion of populations is evolving to an exponential distribution, while the Pareto distribution is squeezed into a fairly small proportion. In particular, we empirically show how the income structure of China evolved to an exponential distribution after the market-oriented economic reformation. The finding of a larger proportion of populations evolving to an exponential income distribution may reveal a potential trend of human civilization towards equal opportunity.

scholarly journals Lattice–Gas–Automaton Modeling of Income Distribution

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 778
Author(s):  
Lijie Cui ◽  
Chuandong Lin
Keyword(s):  
Income Distribution ◽  
Economic Model ◽  
Income Tax ◽  
Lattice Gas ◽  
Free Market ◽  
Matthew Effect ◽  
The Other ◽  
Discrete Models ◽  
The Matthew Effect ◽  
Economic Transaction

A simple and effective lattice–gas–automaton (LGA) economic model is proposed for the income distribution. It consists of four stages: random propagation, economic transaction, income tax, and charity. Two types of discrete models are introduced: two-dimensional four-neighbor model (D2N4) and D2N8. For the former, an agent either remains motionless or travels to one of its four neighboring empty sites randomly. For the latter, the agent may travel to one of its nearest four sites or the four diagonal sites. Afterwards, an economic transaction takes place randomly when two agents are located in the nearest (plus the diagonal) neighboring sites for the D2N4 (D2N8). During the exchange, the Matthew effect could be taken into account in the way that the rich own a higher probability of earning money than the poor. Moreover, two kinds of income tax models are incorporated. One is the detailed taxable income brackets and rates, and the other is a simplified tax model based on a fitting power function. Meanwhile, charity is considered with the assumption that a richer agent donates a part of his income to charity with a certain probability. Finally, the LGA economic model is validated by using two kinds of benchmarks. One is the income distributions of individual agents and two-earner families in a free market. The other is the shares of total income in the USA and UK, respectively. Besides, impacts of the Matthew effect, income tax and charity upon the redistribution of income are investigated. It is confirmed that the model has the potential to offer valuable references for formulating financial laws and regulations.

Inference on P(Y

2020 ◽  
Vol 72 (2) ◽  
pp. 89-110
Author(s):  
Manoj Chacko ◽  
Shiny Mathew
Keyword(s):  
Maximum Likelihood ◽  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Maximum Likelihood Estimators ◽  
Record Values ◽  
Asymptotic Distributions ◽  
Bayes Estimators ◽  
Generalized Pareto ◽  
Pareto Distributions ◽  
Generalized Pareto Distributions

In this article, the estimation of [Formula: see text] is considered when [Formula: see text] and [Formula: see text] are two independent generalized Pareto distributions. The maximum likelihood estimators and Bayes estimators of [Formula: see text] are obtained based on record values. The Asymptotic distributions are also obtained together with the corresponding confidence interval of [Formula: see text]. AMS 2000 subject classification: 90B25

Fellowship Behavior in Division 17 and the MOMM Cartel

1991 ◽  
Vol 19 (2) ◽  
pp. 253-259 ◽  
Author(s):  
John J. Horan ◽  
Chris D. Erickson
Keyword(s):  
Sociology Of Science ◽  
Matthew Effect ◽  
Academic Programs ◽  
The Other ◽  
Professional Service ◽  
Science Literature ◽  
Scholarly Productivity ◽  
Governing Body ◽  
The Matthew Effect ◽  
Counseling Psychologists

Graduates and employees of four institutions-the MOMM Cartel-dominate every science and practice organ of Division 17's governing body. Counseling psychologists from the other 60 academic programs (the OUTSIDERs) face numerous barriers to professional ascendancy. Six of 13 fellow nominees during the 1988-1989 year were MOMM members; none were rejected. Three OUTSIDERs were elected; four were rejected. Mean scholarly productivity for each group was 13, 21.3, and 19.7 Psyc LIT citations, respectively. The accepted OUTSIDERs were significantly more productive than the MOMMs; two of the four rejected OUTSIDERs ranked numbers one and two in scholarly productivity among all nominees. No relationship appeared between scholarship and fellow decisions; MOMM membership strongly predicted election to fellow status. Personal familiarity with the evaluators, rather than professional service, apparently accounts for these filings -a variant of the "Matthew Effect" discussed in the sociology-of-science literature Recommendations for reform are offered

scholarly journals The Gamma Generalized Pareto Distribution with Applications in Survival Analysis

2017 ◽  
Vol 6 (3) ◽  
pp. 141 ◽  
Author(s):  
Thiago A. N. De Andrade ◽  
Luz Milena Zea Fernandez ◽  
Frank Gomes-Silva ◽  
Gauss M. Cordeiro
Keyword(s):  
Monte Carlo Simulation ◽  
Pareto Distribution ◽  
Generalized Pareto Distribution ◽  
Real Data ◽  
Model Parameters ◽  
Monte Carlo Simulation Study ◽  
Lorenz Curves ◽  
Generalized Pareto ◽  
Mathematical Properties ◽  
Pareto Model

We study a three-parameter model named the gamma generalized Pareto distribution. This distribution extends the generalized Pareto model, which has many applications in areas such as insurance, reliability, finance and many others. We derive some of its characterizations and mathematical properties including explicit expressions for the density and quantile functions, ordinary and incomplete moments, mean deviations, Bonferroni and Lorenz curves, generating function, R\'enyi entropy and order statistics. We discuss the estimation of the model parameters by maximum likelihood. A small Monte Carlo simulation study and two applications to real data are presented. We hope that this distribution may be useful for modeling survival and reliability data.

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