Log-linear dynamics and local potential - Daijiro Okada; Olivier Tercieux (Rutgers University, Department of Economics, 2008)
We show that local potential maximizer ([15]) with constant weights is stochastically stable in the log-linear dynamics provided that the payoff function or the associated local potential function is supermodular. We illustrate and discuss, through a series of examples, the use of our main results as well as other concepts closely related to local potential maximizer: weighted potential maximizer, p-dominance. We also discuss the log-linear processes where each player's stochastic choice rule converges to the best response rule at different rates. For 2 x 2 games, we examine a modified log-linear dynamics (relative log-linear dynamics) under which local potential maximizer with strictly positive weights is stochastically stable. This in particular implies that for 2 x 2 games a strict (p1,p2)-dominant equilibrium with p1+p2<1 is stochastically stable under the new dynamics.
Keywords: C72; C73; 330; log-linear dynamics; stochastic stability; local potential maximizer; equilibrium selection; comparison of Markov chains; Spieltheorie; Stochastischer Prozess; Markovscher Prozess; Theorie