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Market Behavior and Evolution of Wealth Distribution: A Simulation Model Based on Artificial Agents

Academic Article
Publication Date:
2021
Short description:
Market Behavior and Evolution of Wealth Distribution: A Simulation Model Based on Artificial Agents / Giunta, A., Giunta, G., Marino, D., Oliveri, F.. - In: MATHEMATICAL AND COMPUTATIONAL APPLICATIONS. - ISSN 2297-8747. - 26:12(2021), pp. 1-13. [10.3390/mca26010012]
abstract:
The aim of this work is to simulate a market behavior in order to study the evolution of wealth distribution. The numerical simulations are carried out on a simple economical model with a finite number of economic agents, which are able to exchange goods/services and money; the various agents interact each other by means of random exchanges. The model is micro founded, self-consistent, and predictive. Despite the simplicity of the model, the simulations show a complex and non-trivial behavior. First of all, we are able to recognize two solution classes, namely two phases, separated by a threshold region. The analysis of the wealth distribution of the model agents, in the threshold region, shows functional forms resembling empirical quantitative studies of the probability distributions of wealth and income in the United Kingdom and the United States. Furthermore, the decile distribution of the population wealth of the simulated model, in the threshold region, overlaps in a suggestive way with the real data of the Italian population wealth in the last few years. Finally, the results of the simulated model allow us to draw important considerations for designing effective policies for economic and human development.
Iris type:
1.1 Articolo in rivista
List of contributors:
Giunta, A; Giunta, G; Marino, D; Oliveri, F
Authors of the University:
MARINO Domenico
Handle:
https://iris.unirc.it/handle/20.500.12318/107476
Full Text:
https://iris.unirc.it//retrieve/handle/20.500.12318/107476/205544/Marino_2021_MaCA_Wealth%20Distribution_editor.pdf
Published in:
MATHEMATICAL AND COMPUTATIONAL APPLICATIONS
Journal
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URL

https://www.mdpi.com/2297-8747/26/1/12
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