Attitude polarization
Inhalt
Psychological evidence suggests that people’s learning behavior is often prone
to a “myside bias” or “irrational belief persistence” in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such
a bias may result in diverging posterior beliefs and attitude polarization even if
agents receive identical information. Such patterns cannot be explained by the
standard model of rational Bayesian learning that implies convergent beliefs. As
our key contribution, we therefore develop formal models of Bayesian learning with
psychological bias as alternatives to rational Bayesian learning. We derive condi-
tions under which beliefs may diverge in the learning process and thus conform
with the psychological evidence. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in
Choquet expected utility theory. As a specific feature of our approach, our models
of Bayesian learning with psychological bias reduce to rational Bayesian learning
in the absence of ambiguity.
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