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Shadow markets and hierarchies: comparing and modeling networks in the Dark Net

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  • NORGAARD, JULIA R.
  • WALBERT, HAROLD J.
  • HARDY, R. AUGUST

Abstract

This paper analyzes the determinants of network structure, as measured by hierarchy and monopolization, by examining various black market networks. We examine structures of networks on the Internet Dark Net (Virtual) and compare it to network structures of traditional black markets (Ground), using agent-based modeling. The purpose of modeling these two different types of illicit markets is to understand the network structure that emerges from the interactions of the agents in each environment. Traditional black markets are relatively hierarchical, with high degree and high betweenness. We compare the density and average length of the shortest path of the simulated Ground black market networks with our simulated Virtual network. We find that hierarchy and monopolization tendencies in networks are products of different transaction costs and information asymmetries. The Internet is an effective way to lower multiple aspects of network structure. We observe that the network structure surrounding the interactions in the Virtual black market is less hierarchical and slightly more monopolistic than the network structure of the Ground market.

Suggested Citation

  • Norgaard, Julia R. & Walbert, Harold J. & Hardy, R. August, 2018. "Shadow markets and hierarchies: comparing and modeling networks in the Dark Net," Journal of Institutional Economics, Cambridge University Press, vol. 14(5), pages 877-899, October.
  • Handle: RePEc:cup:jinsec:v:14:y:2018:i:05:p:877-899_00
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    Cited by:

    1. Harwick, Cameron & Caton, James, 2022. "What’s holding back blockchain finance? On the possibility of decentralized autonomous finance," The Quarterly Review of Economics and Finance, Elsevier, vol. 84(C), pages 420-429.
    2. Jason Chan & Shu He & Dandan Qiao & Andrew B. Whinston, 2019. "Shedding Light on the Dark: The Impact of Legal Enforcement on Darknet Transactions," Working Papers 19-08, NET Institute.

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