Wealth Distribution Involving Psychological Traits and Non-Maxwellian Collision Kernel
A kinetic exchange model is developed to investigate wealth distribution in a market. The model incorporates a value function that captures the agents’ psychological traits, governing their wealth allocation based on behavioral responses to perceived potential losses and returns. To account for the...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-01-01
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| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/27/1/64 |
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| Summary: | A kinetic exchange model is developed to investigate wealth distribution in a market. The model incorporates a value function that captures the agents’ psychological traits, governing their wealth allocation based on behavioral responses to perceived potential losses and returns. To account for the impact of transaction frequency on wealth dynamics, a non-Maxwellian collision kernel is introduced. Applying quasi-invariant limits and Boltzmann-type equations, a Fokker–Planck equation is derived. We obtain an entropy explicit stationary solution that exhibits exponential convergence to a lognormal wealth distribution. Numerical experiments support the theoretical insights and highlight the model’s significance in understanding wealth distribution. |
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| ISSN: | 1099-4300 |