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Mathematical Biosciences and Engineering
Article . 2023 . Peer-reviewed
Data sources: Crossref
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Modeling income distribution: An econophysics approach

Authors: Khamnei, Hossein Jabbari; Nikannia, Sajad; Fathi, Masood; Ghorbani, Shahryar;

Modeling income distribution: An econophysics approach

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>

Country
Sweden
Keywords

Gibbs-Boltzmann, Matematik, econophysics, gibbs-boltzmann, income distribution, QA1-939, pareto, TP248.13-248.65, Mathematics, lognormal, Biotechnology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
gold