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Agent-based simulations of payoff distribution in economic networks

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Abstract

Simulating the behavior of economic agents fosters the analysis of interconnected markets dynamics. Here, we extend the state of the art by adding realistic details to simulating economic exchange networks. To this end, we use our economic network simulation framework TrEcSim, which is designed to support the following real-life features: complex network topologies, evolution of economic agent roles, dynamic creation of new economic agents, diversity in product types, dynamic evolution of product prices, and investment decisions at agent level. By employing simulation, we determine which topological properties promote meritocracy and fairness. Simulation also allows for analyzing the influence of producers and middlemen distribution in the economic exchange network; similarly, we gain valuable insight regarding the distribution of payoff for each agent role. Moreover, we conclude that economic networks promote fairness throughout their structure, namely that the main determining factor for fairness in payoff distribution is the underlying network topology, not agent role assignment.

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Notes

  1. TrEcSim is freely available at https://github.com/trecsim/trecsim.

  2. Economic agents are represented as network nodes.

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Acknowledgements

Author AT was partly supported by the Romanian National Authority for Scientific Research and Innovation (UEFISCDI), Project Number PN-III-P1-1.1-PD-2016-0193.

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Authors and Affiliations

  1. Department of Computer and Information Technology, Politehnica University of Timişoara, Bd. Vasile Parvan 2, 300223, Timisoara, Romania

    Gabriel Barina, Mihai Udrescu, Alexandra Barina, Alexandru Topirceanu & Mircea Vladutiu

  2. Timişoara Institute of Complex Systems, Timisoara, Romania

    Mihai Udrescu

Authors
  1. Gabriel Barina
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  2. Mihai Udrescu
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  3. Alexandra Barina
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  4. Alexandru Topirceanu
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  5. Mircea Vladutiu
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Correspondence to Gabriel Barina.

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Supplementary material 1 (pdf 1412 KB)

Appendices

Appendix

Appendix 1: The default settings used in TrEcSim for each new simulation

See Table 8.

Table 8 Settings used for each new simulation with TrEcSim
Full size table

Appendix 2: Analysis of ergodicity in economic networks

See Figs. 7, 8, 9 and 10.

Fig. 7
figure 7

Payoff evolution in a mesh network, in relation to both the time spent in each payoff category interval (upper panels) and the number of economic agents—producers (P) and middlemen (M)—in each payoff category (lower panels). The producers were assigned both randomly and preferentially to the agents with the highest degrees in the network

Full size image
Fig. 8
figure 8

Payoff evolution in a small-world network, in relation to both the time spent in each payoff category interval (upper panels) and the number of economic agents—producers (P) and middlemen (M)—in each payoff category (lower panels). The producers were assigned both randomly and preferentially to the agents with the highest degrees in the network

Full size image
Fig. 9
figure 9

Payoff evolution in a random network, in relation to both the time spent in each payoff category interval (upper panels) and the number of economic agents—producers (P) and middlemen (M)—in each payoff category (lower panels). The producers were assigned both randomly and as preferentially to the agents with the highest degrees in the network

Full size image
Fig. 10
figure 10

Payoff evolution in a scale-free network, in relation to both the time spent in each payoff category interval (upper panels) and the number of economic agents—producers (P) and middlemen (M)—in each payoff category (lower panels). The producers were assigned both randomly and preferentially to the agents with the highest degrees in the network

Full size image

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Barina, G., Udrescu, M., Barina, A. et al. Agent-based simulations of payoff distribution in economic networks. Soc. Netw. Anal. Min. 9, 63 (2019). https://doi.org/10.1007/s13278-019-0601-y

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  • DOI: https://doi.org/10.1007/s13278-019-0601-y

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