A Behavioral Study of 'Noise' in Coordination Games

Abstract

Abstract'Noise' in this study, in the sense of evolutionary game theory, refers to deviations from prevailing behavioral rules. Analyzing data from a laboratory experiment on coordination in networks, we tested 'what kind of noise' is supported by behavioral evidence. This empirical analysis complements a growing theoretical literature on 'how noise matters' for equilibrium selection. We find that the vast majority of decisions (96%) constitute myopic best responses, but deviations continue to occur with probabilities that are sensitive to their costs, that is, less frequent when implying larger payoff losses relative to the myopic best response. In addition, deviation rates vary with patterns of realized payoffs that are related to trial-and-error behavior. While there is little evidence that deviations are clustered in time or space, there is evidence of individual heterogeneity.

Local interactions under switching costs

“…Maes and Nax (2014) experimentally assess whether uniform-or logit-noise provides a better fit to actual deviation from best response learning. Noise levels turn out to decrease with the payoff loss implied by a deviation, providing support for logit noise.…”