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Wealth distribution for agents with spending propensity, interacting over a network.

Víctor Muñoz1

  • 1Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, Santiago, Chile.

Chaos (Woodbury, N.Y.)
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Summary
This summary is machine-generated.

Agent-based economic models show that wealth distribution, following Pareto's law, is robust across various network structures. Network topology significantly impacts wealth disparities, especially with higher connectivity exponents.

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Area of Science:

  • Economic modeling
  • Network science
  • Statistical physics

Background:

  • Wealth distribution often follows Pareto's law, indicating a skewed distribution where a small percentage holds a large portion of wealth.
  • Agent-based models are used to simulate complex economic systems and understand emergent phenomena like wealth inequality.
  • Network topology, representing interaction patterns, can influence economic outcomes.

Purpose of the Study:

  • To investigate the impact of network structure on wealth distribution in an agent-based economic model.
  • To determine the robustness of Pareto's law under different network connectivity conditions.
  • To explore the relationship between network topological properties and wealth inequality.

Main Methods:

  • Utilized an agent-based model with agents possessing spending propensities.
  • Simulated interactions over various network types, including random and scale-free networks with different connectivity exponents (α).
  • Analyzed wealth distribution patterns and tail behavior under varying network parameters.

Main Results:

  • Wealth distribution approximates random interaction models when scale-free network exponents (α) are below 1.
  • Scale-free networks with α > 1 significantly alter wealth distribution and tail behavior.
  • Pareto's law for wealth distribution demonstrates high robustness across different network connectivities and spending propensity models.

Conclusions:

  • Pareto's law is a resilient phenomenon in economic systems, largely independent of specific network connectivity details.
  • The topological properties of interaction networks play a crucial role in shaping wealth distribution and inequality.
  • Findings suggest that the prevalence of Pareto's law in real-world economies may be linked to their underlying network structures.