Effect of network topology and node centrality on trading

Abstract

Global supply networks in agriculture, manufacturing, and services are a defining feature of the modern world. The efficiency and the distribution of surpluses across different parts of these networks depend on the choices of intermediaries. This paper conducts price formation experiments with human subjects located in large complex networks to develop a better understanding of the principles governing behavior. Our first experimental finding is that prices are larger and that trade is significantly less efficient in small-world networks as compared to random networks. Our second experimental finding is that location within a network is not an important determinant of pricing. An examination of the price dynamics suggests that traders on cheapest-and hence active-paths raise prices while those off these paths lower them. We construct an agent-based model (ABM) that embodies this rule of thumb. Simulations of this ABM yield macroscopic patterns consistent with the experimental findings. Finally, we extrapolate the ABM on to significantly larger random and smallworld networks and find that network topology remains a key determinant of pricing and efficiency. Globalization is a prominent feature of the modern economy 1. Nowadays, supply, service and trading chains 2,3,3-6 play a central role in different contexts such as agriculture 7-10 , transport and communication networks 11,12 , international trade 13 and finance 14,15. One key question on these systems is how pricing dynamics by intermediaries of the economy impacts both efficiency and surpluses. The purpose of this paper is to develop a better understanding of the forces that shape intermediary pricing behavior in such complex networks. Game theory constitutes a useful framework to study competition among trading agents 16. In this context, the Nash Bargaining Game 17 studies how two agents share a surplus that they can jointly generate. In the Nash Bargaining Game, two players demand a portion of some good. If the total amount requested by both players is less than the total value of the good, both players get their request; otherwise, no player gets their request. There are many Nash equilibria in this game: any combination of demands whose sum is equal to the total value of the good constitutes a Nash equilibrium. There is also a Nash equilibrium where each player demands the entire value of the good 18. As a generalization of Nash demand game to n players, Choi et al. 19 proposed and tested in the laboratory a model of intermediation pricing. In this model, a good is supposed to go from a source S to a destination D. Intermediaries, which are located in the nodes of a network, may post a price for the passage of the good. Trading occurs if there exists a path between S and D on which the sum of prices is smaller than or equal to the value of the good. The key finding was that the pricing and the surpluses of the intermediaries depends on the presence of "critical" nodes: a node is said to be critical if it lies on all possible paths between S and D. Condo...

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