Abstract:

A non-negative function f defined on the class of subsets of a finite set of factors of production describes the production possibilities at each date. The problem of allocating the surplus among the factors is studied in a dynamic learning model. Representatives for the factors (called players) make wage demands naively based on precedent and ignorant of each others' utilities for this good. A global convergence result shows that players learn to reach some (and only a) core allocation in the long run. If players make mistakes however, only a strict subset of the core allocations are likely, i.e., stochastically stable. The main result shows that in the limit, these stable allocations for a particular set of players, converge to the allocation that maximizes the product of all the players' utilities over core allocations.

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