Bayesian Polarization

Abstract

Discussions of political disagreement emphasize two patterns: polarization, where beliefs diverge toward opposite extremes on each issue dimension; and issue alignment, where individuals' views across issues become more internally consistent. We show that both can simultaneously arise under Bayesian learning from public information. We characterize the public signals that can induce persistent polarization on all dimensions and find that evidence of issue alignment can polarize Bayesian agents. However, we show that even stronger notions of polarization, requiring divergence beyond marginal beliefs, are inconsistent with Bayesian rationality. Whether multidimensional belief polarization translates into divergent aggregate positions depends on cross-issue separability.