We consider a one-sided assignment market or exchange network with transferable utility and propose a model for the dynamics of bargaining in such a market. Our dynamical model is local, involving iterative updates of \u2018offers\u2019 based on estimated best alternative matches, in the spirit of pairwise Nash bargaining. We establish that when a balanced outcome (a generalization of the pairwise Nash bargaining solution to networks) exists, our dynamics converges rapidly to such an outcome. We extend our results to the cases of (i) general agent \u2018capacity constraints\u2019, i.e., an agent may be allowed to participate in multiple matches, and (ii)\u2018unequal bargaining powers\u2019 (where we also find a surprising change in rate of convergence).<\/p>\n","protected":false},"excerpt":{"rendered":"
We consider a one-sided assignment market or exchange network with transferable utility and propose a model for the dynamics of bargaining in such a market. Our dynamical model is local, involving iterative updates of \u2018offers\u2019 based on estimated best alternative matches, in the spirit of pairwise Nash bargaining. We establish that when a balanced outcome 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