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Trade requires search, negotiation, and exchange, which are activities thatabsorb resources. Thispaper investigates how different trade networks attend to these activities.An artificial marketis constructed in which autonomous agents endowed with a stock of goods seekout partners,negotiate a price, and then trade with the agent offering the best deal.Different trade networksare imposed on the system by restricting the set of individuals with whom anagent cancommunicate. We then compare the path to the eventual equilibrium as well asthe equilibriumcharacteristics of each trade network to see how each system dealt with thetasks of search,negotiation, and exchange.Initially, all agents are free to trade with any individual in the globalmarket. In such a world,global resources are optimally allocated with few trades, but only after atremendous amount ofsearch and negotiation. If trade is restricted within disjoint localboundaries, search is simple butglobal efficiency elusive. However, a hybrid model in which most agents tradelocally but a fewagents trade globally results in an economy that quickly reaches a Paretooptimal equilibriumwith significantly lower search and negotiation costs. Such `small-world'networks occur innature and may help explain the ease with which most of us acquire goods fromaround theworld. We also show that there are private incentives for such a system toarise.