Abstract: This paper models a dissonance-reducing learner. The learner suffers utility loss when faced with mutually conflicting information and, in response, distorts how she perceives different pieces of information to increase the apparent agreement among them. Relative to Bayesian updating, the learner always appears partisan. In two-sided debates, she champions one side by exaggerating arguments that support it and downplaying opposing arguments. Her choice of favored side is both influenced by objective evidence and skewed by hotly-debated issues. Her posterior belief is inordinately extreme. Applications to dynamic learning, networks, persuasion, and information-seeking further characterize the learner’s behavior.

Bio: Kyle Chauvin is an Assistant Professor of Economics at NYU Shanghai. His research in microeconomic theory and behavioral economics investigates the consequences of imperfect learning for communication, persuasion, discrimination, and social networks.