Modeling income distribution: An econophysics approach-Reference-Cited by-同舟云学术

Modeling income distribution: An econophysics approach

Published:2023 Issue:7 Volume:20 Page:13171-13181
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Khamnei Hossein Jabbari¹,Nikannia Sajad²,Fathi Masood³⁴,Ghorbani Shahryar⁵

Affiliation:

1. Department of Statistics, Faculty of Mathematics; Statistics and computer Science, University of Tabriz, Tabriz, Iran

2. Department of Economic, Faculty of Economic and Management, University of Tabriz, Tabriz, Iran

3. Division of Intelligent Production Systems, School of Engineering Science, University of Skövde, Skövde 54128, Sweden

4. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Uppsala 75121, Sweden

5. Production Management Department, University of Sakarya, Sakarya 54050, Turkey

Abstract

<abstract><p>This study aims to develop appropriate models for income distribution in Iran using the econophysics approach for the 2006–2018 period. For this purpose, the three improved distributions of the Pareto, Lognormal, and Gibbs-Boltzmann distributions are analyzed with the data extracted from the target household income expansion plan of the statistical centers in Iran. The research results indicate that the income distribution in Iran does not follow the Pareto and Lognormal distributions in most of the study years but follows the generalized Gibbs-Boltzmann distribution function in all study years. According to the results, the generalized Gibbs-Boltzmann distribution also properly fits the actual data distribution and could clearly explain the income distribution in Iran. The generalized Gibbs-Boltzmann distribution also fits the actual income data better than both Pareto and Lognormal distributions.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

Reference32 articles.

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