Abstract:
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 GaleShapley matching, participate in risky trades modelled as two-person prisoner's dilemma games, and evolve their trade strategies 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. Keywords: Evolutionary match-and-play game; Gale-Shapley matching; iterated prisoner's dilemma; trade networks; endogenous interactions; agent-based computational economics.
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