GALE-SHAPLEY MATCHING IN AN EVOLUTIONARY TRADE NETWORK GAME
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This study investigates the performance of Gale-Shapley matching in an evolutionary market context. Computational experimental findings are reported for an evolutionary match-and-play trade network game in which resource-constrained traders repeatedly choose and refuse trade partners in accordance with Gale-Shapley matching, participate in risky trades modelled as two-person prisoner's dilemma games, and evolve their trade behavior over time. Particular attention is focused on correlations between ex ante market structure and the formation of trade networks, and between trade network formation and the types of trade behavior and social welfare outcomes that these trade networks support.