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Modeling income distribution: An econophysics approach
Department of Statistics, Faculty of Mathematics ; Statistics and computer Science, University of Tabriz, Iran.
Department of Economic, Faculty of Economic and Management, University of Tabriz, Iran.
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden. (Virtual Production Development)ORCID iD: 0000-0001-5530-3517
Production Management Department, University of Sakarya, Turkey.
2023 (English)In: Mathematical Biosciences and Engineering, ISSN 1547-1063, E-ISSN 1551-0018, Vol. 20, no 7, p. 13171-13181Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
AIMS Press , 2023. Vol. 20, no 7, p. 13171-13181
Keywords [en]
econophysics, Gibbs-Boltzmann, lognormal, pareto, income distribution
National Category
Mathematics
Research subject
Virtual Production Development (VPD)
Identifiers
URN: urn:nbn:se:his:diva-22673DOI: 10.3934/mbe.2023587ISI: 001016300600003PubMedID: 37501483Scopus ID: 2-s2.0-85162240998OAI: oai:DiVA.org:his-22673DiVA, id: diva2:1765774
Note

CC BY 4.0

Special Issue: Data modeling using compound distributions: theory and applications

Correspondence: Email: h_jabbari@tabrizu.ac.ir

Available from: 2023-06-12 Created: 2023-06-12 Last updated: 2024-08-16Bibliographically approved

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Fathi, Masood

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