Economics of Illicit Behaviors:
Exchange in the Internet Wild West
How can there exist robust patterns of cooperation without the overarching control of a centralized enforcement? This is the fundamental question driving my dissertation. In particular, in my research, I investigate the behavioral strategies and institutional features that characterize a recently emerged environment of ungoverned interaction: the internet black market.
My dissertation falls within the fields of political economy and law and economics. The tools I use in my work are those of applied microeconomics –with a strong quantitative bent but also appreciative of qualitative evidence. The primary focus of my research is on the economics of illicit behaviors, and specifically on the topic of exchange institutions in the Internet black market. In the tradition of Virginia Political Economy, my work focuses on individual behavior and institutions in non-market settings.
Reputation in the Internet black market; an empirical and theoretical analysis of the Deep Web
This paper is an analysis of the role reputation plays in the Deep Web using data from the Internet black-market site, The Silk Road. This encrypted online marketplace employed cryptocurrency and functioned over the Tor network. Utilizing a modeling technique, informed by trade auction theory, we investigate the effect of seller reputation. Analysis of the seller's reputation gives us insights into the factors that determine the prices of goods and services in this black marketplace. Data on cannabis listings is parsed from the Silk Road website and covers an 11-month time period, from November 2013 to October 2014. This data demonstrates that reputation acts as a sufficient self-enforcement mechanism to allow transactions. These findings exemplify the robustness of spontaneous order with respect to the Deep Web as an emergent marketplace.
Trust Development and Self-Enforcing Exchange in Anonymous Internet Markets
This paper analyzes and models trust development in anonymous Internet marketplaces. Treating trust development as endogenous to user’s actions, this model demonstrates how trust is a function of site administrator’s and seller’s actions. I show how cost discriminating signals are utilized by heterogeneous anonymous users, both site administrators and sellers, to capture gains from global trade. Ex ante signaling makes trade in these marketplaces self-enforcing, overcoming the complications of a lack of ex post multilateral punishment and third party enforcement. Extensive global trade on Dark Net Internet sites such as The Silk Road and Agora exhibit the manifestation of this mechanism in the real world.
Shadow markets and hierarchies: Comparing and modeling networks in the Dark Net
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.