The identified switch in betting preferences is not due to a violation of dynamic consistency or consequentialism.
Rather, it results from MLU’s selection of extreme priors, causing a violation of the stability of set inclusion over the course of the updating process.), there have been attempts to find alternative decision rules reflecting sensitivity to ambiguity, i.e., decision set-ups in which probabilities are not known.
We show that such rules are optimal if agents sufficiently discount the future; while if they are very patient then a time-varying random interpretation rule becomes optimal.
Full Bayesian updating, going back to contributions by Fagin and Halpern (): Bayesian updating is applied only to those priors with maximal likelihood given the observed event.
This paper contributes to the debate about these update rules.
Typical approaches are based on non-additive probabilities, also known as “capacities” (Schmeidler ).
Dynamic extensions of these static ambiguity sensitive preferences are needed, since “almost all potential applications of interest in economics involve some dynamic element.
Antonio Guarino is a Professor of Economics in the Department of Economics at UCL.