Finding the Impact of Market Visibility and Monopoly on Wealth Distribution and Poverty Using Computational Economics

Kashif Zia (), Umar Farooq and Sakeena Al Ajmi
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Kashif Zia: Sohar University
Umar Farooq: University of Science and Technology Bannu
Sakeena Al Ajmi: Sohar University

Computational Economics, 2023, vol. 61, issue 1, No 5, 113-137

Abstract: Abstract The complexity science, with the help of, agent based modeling has recently claimed that the free market economy is producing wealth inequality—a totally opposite perception, which is in practice for more than 10 decades. It is capable of investigating the distribution of money in the market economy and finding solution for unfair gap between the wealth and, thus, overcoming poverty. This paper is an attempt to investigate this claim. This work is inspired from Gooding’s work and it, therefore, reproduces his toy trader model, which claims to offer a fair trading environment. This model is extended towards a more human-oriented economy by introducing two possible biases: the variation of market visibility between the traders (by introducing the social networks of traders) and monopoly. The basic aim was to find out the impact of market visibility and monopoly on wealth distribution and poverty. It was learnt through simulations performed, in NetLogo, that the accessibility of traders, when taken as an important factor of a free market economy, positively influences wealth disparity, wealth gap and controls poverty. However, more human-oriented economy, in fact, widens the rich-poor divide and increases poverty. These results suggest that the authorities must control the market and everyone involved in trading should be given equal opportunities. This would also help in controlling the possible monopoly of the traders. The intrinsic physics of the free market would, otherwise, will always result in an unequal distribution of wealth.

Keywords: Computational economics; Wealth inequality; Poverty; Gini coefficient; Agent-based model; Free-market economy (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10614-021-10201-x

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