  We introduce and characterize inertial updating of beliefs. Under inertial
updating, a decision maker (DM) chooses a belief that minimizes the subjective
distance between their prior belief and the set of beliefs consistent with the
observed event. Importantly, by varying the subjective notion of distance,
inertial updating provides a unifying framework that nests three different
types of belief updating: (i) Bayesian updating, (ii) non-Bayesian updating
rules, and (iii) updating rules for events with zero probability, including the
conditional probability system (CPS) of Myerson (1986a,b). We demonstrate that
our model is behaviorally equivalent to the Hypothesis Testing model (HT) of
Ortoleva (2012), clarifying the connection between HT and CPS. We apply our
model to a persuasion game.
