Abstract

It is well known that two different underlying dynamics lead to different patterns of income/wealth distribution such as the Boltzmann–Gibbs form for the lower end and the Pareto-like power-law form for the higher-end. The Boltzmann–Gibbs distribution is naturally derived from maximizing the entropy of random interactions among agents, whereas the Pareto distribution requires a rational approach of economics dependent on the wealth level. More interestingly, the Pareto regime is very dynamic, whereas the Boltzmann–Gibbs regime is stable over time. Also, there are some cases in which the distributions of income/wealth are bimodal or polymodal. In order to incorporate the dynamic aspects of the Pareto regime and the polymodal forms of income/wealth distribution into one stochastic model, we present a modified agent-based model based on classical kinetic wealth exchange models. First, we adopt a simple two-class society consisting of the rich and the poor where the agents in the same class engage in random exchanges while the agents in the different classes perform a wealth-dependent winner-takes-all trading. This modification leads the system to an extreme polarized society with preserving the Pareto exponent. Second, we incorporate a solidarity formation among agents belonging to the lower class in our model, in order to confront a super-rich agent. This modification leads the system to a drastic bimodal distribution of wealth with a varying Pareto exponent over varying the solidarity parameter, that is, the Pareto-regime becomes narrower and the Pareto exponent gets larger as the solidarity parameter increases. We argue that the solidarity formation is the key ingredient in the varying Pareto exponent and the polymodal distribution. Lastly, we take two approaches to evaluate the level of inequality of wealth such as Gini coefficients and the entropy measure. According to the numerical results, the increasing solidarity parameter leads to a decreasing Gini coefficient not linearly but nonlinearly, whereas the entropy measure is robust over varying solidarity parameters, implying that there is a trade-off between the intermediate party and the high end.

Highlights

  • Frequency distributions of a variety of statistics in social systems—such as income, wealth, city sizes, price-fluctuation of stock markets, and so on—show a power-law behavior

  • In order to obtain the steady-state distributions for each simulation, we perform 103 Monte Carlo (MC) time steps, where one MC time step is defined as 1000 times random exchanges among 1000 agents

  • We have presented a modified agent-based stochastic model by introducing a two-class society with wealth-dependent trading rules and a solidarity formation, in order to explain the dynamic aspects of the Pareto regime and the polymodal behavior of income/wealth distributions observed in some cases [27,28]

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Summary

Introduction

Frequency distributions of a variety of statistics in social systems—such as income, wealth, city sizes, price-fluctuation of stock markets, and so on—show a power-law behavior. To explain the observed features of distributions of income and wealth, several agent-based models have been proposed on the basis of stochasticity and statistical mechanics. For the former, the variations of income and wealth are described in terms of stochastic terms, namely additive and multiplicative [6,16,17]. An additive term represents salaries while a multiplicative term represents a premium from investment proportionate to invested wealth Their distribution is quite different from Gibbs and Gamma distributions and shows a power-law tail at large wealth and a sharp cutoff at small wealth. When saving propensity is distributed heterogeneously to agents, a power-law tail appears in distribution functions as done by a multiplicative term in the stochastic wealth process [25]

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