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The Role of Search Friction in Networked Markets ’ Stationarity

The advent of the Internet and the resulting electronic revolution has resulted in incredible speed-ups in trade and commerce. Many time-consuming and arduous transactions have been greatly simplified and sped-up. In modern electronic financial markets, for example, high frequency trading has become a critical component and has resulted in a greatly increased volume of trade. Given the recent financial crisis, studies on the effect of high frequency trading to the market micro-structure and its dynamics has become an active and important research topic. In this paper, we consider the dynamics of a non-cooperative networked bargaining game as the market trading process and then incorporate search friction into the model. Our goal is to study how search friction influences the market’s stability and efficiency in a network economy. Our starting point is the framework introduced in [2], which considers a non-cooperative bargaining process as a micro-market mechanism and incorporates it into a large, competitive networked market. It is shown in [2] that even in the case of the economy becoming large, with more agents at each location so that each agent has a diminishing influence on the economy, the agent’s strategy need not converge to a stationary equilibrium resulting in endogenous fluctuations. Another important conclusion drawn from [2] is that a small shock in the economy can be amplified through the network to make a “stable” market change to one that does not have a stable outcome. In more detail, the model consists of a line network of middleman agents that allow sellers to sell their product to buyers. The network restricts the trades that are allowed only to local interactions, i.e., a middle-man agent can only buy the good from an agent (could be a seller) closer to the seller and can only sell the good to an agent (could be a buyer) closer to the buyer; a seller can only sell the good to an agent that she is connected to and a buyer can only buy the good from an agent that she is connected to. In the set-up analyzed in [2], an agent is chosen at random and based on whether she possesses the good or not, she either sells or buys the good. In either case, the model is such that she can identify all the agents in the next hop with whom she can trade with, if any exist; in other words, her search procedure is frictionless: extremely fast and reliable.