This paper develops an approach to equilibrium selection in game theory based on studying the equilibriating process through which equilibrium is achieved. The differential equations derived from models of interactive learning typically have stationary states that are not isolated. Instead, Nash equilibria that specify the same behavior on the equilibrium path, but different out-of-equilibrium behavior, appear in connected components of stationary states. The stability properties of these components often depend critically on the perturbations to which the system is subjected. We argue that it is then important to incorporate such drift into the model. A sufficient condition is provided for drift to create stationary states with strong stability properties near a component of equilibria. This result is used to derive comparative static predictions concerning common questions raised in the literature on refinements of Nash equlibrium.;

In the economic modeling of bargaining, outside options have often been naively treated by taking them as the disagreement payoffs in an application of the Nash bargaining solution. The paper contrasts this method of predicting outcomes with that obtained from an analysis of optimal strategic behavior in a natural game-theoretic model of the bargaining process. The strategic analysis predicts that the outside options will be irrelevant to the final deal unless a bargainer would then go elsewhere. An experiment is reported which indicates that this prediction performs well in comparison with the conventional predictor.