Modeling income distribution: An econophysics approach

Hossein Jabbari Khamnei; Sajad Nikannia; Masood Fathi; Shahryar Ghorbani; Hossein Jabbari Khamnei; Sajad Nikannia; Masood Fathi; Shahryar Ghorbani

doi:10.3934/mbe.2023587

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 7: 13171-13181. doi: 10.3934/mbe.2023587

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Modeling income distribution: An econophysics approach

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

Academic Editor: Piero Manfredi

Received: 21 January 2023 Revised: 27 May 2023 Accepted: 29 May 2023 Published: 07 June 2023

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.
- econophysics,
- Gibbs-Boltzmann,
- lognormal,
- pareto,
- income distribution
Citation: Hossein Jabbari Khamnei, Sajad Nikannia, Masood Fathi, Shahryar Ghorbani. Modeling income distribution: An econophysics approach[J]. Mathematical Biosciences and Engineering, 2023, 20(7): 13171-13181. doi: 10.3934/mbe.2023587

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Abstract

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.

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