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Kinetic Models of Wealth Distribution with Extreme Inequality: Numerical Study of Their Stability against Random
Asim Ghosh1, Suchismita Banerjee2, Sanchari Goswami3
1Department of Physics, Raghunathpur College, Raghunathpur, Purulia 723133, India.
Entropy (Basel, Switzerland)
|July 29, 2023
Summary
Kinetic exchange models explore wealth concentration. The Banerjee model shows extreme wealth condensation, but random exchanges prevent this, offering insights into economic inequality dynamics.
Area of Science:
- Economic modeling
- Statistical physics
- Computational economics
Background:
- Global wealth inequality is a significant concern, with a small elite holding disproportionate wealth.
- Kinetic exchange models are used to simulate market dynamics and wealth distribution.
Purpose of the Study:
- To investigate if kinetic exchange models can replicate extreme wealth concentration.
- To analyze the statistical properties of the Chakraborti, Banerjee, and Goswami-Sen models.
Main Methods:
- Exploration of kinetic exchange models, including the Chakraborti and Banerjee models.
- Utilizing Monte Carlo simulations to study statistical features.
- Analyzing the impact of random exchange probabilities on wealth condensation.
Main Results:
- The Chakraborti model leads to complete wealth condensation in one individual.
- The Banerjee model results in approximately 99.98% of wealth held by ten agents.
- Introducing random exchanges or using models like Goswami-Sen prevents wealth condensation.
Conclusions:
- Kinetic exchange models can exhibit extreme wealth concentration, mirroring real-world inequality.
- Random exchange probabilities are crucial in mitigating wealth condensation.
- Model dynamics, such as those in the Goswami-Sen model, can inherently prevent extreme wealth disparities.
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