Predicting Patterns of Exchange in Economic Exchange Networks*

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Abstract
Whereas much theoretical and empirical work concerning exchange networks examines the payoffs to actors in particular positions, a much smaller body of work focuses on exchange patterns (i.e., who exchanges with whom). The problem we address in this paper is that the existing methods to predict patterns of exchange are limited by computational cost to relatively small networks. We develop a computationally efficient method for locating and predicting patterns of exchange. The theory on which we draw argues that each actor’s resistance to unfavorable offers is based on relative position within the exchange network. Using experimental data we first show that the order of exchanges does affect payoffs as the network structure changes over time. We then attempt to predict the ordering of exchanges for a number of networks using three existing methods and one new method derived from our theory. As a test of the predicted orderings, we compare each method’s predictions for six exchange networks against experimental results. In general, the results suggest that our more parsimonious method performs quite well relative to the more computationally complex prediction methods.

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