Larry Epstein (),
Jawwad Noor () and
Alvaro Sandroni ()
Additional contact information Alvaro Sandroni: Department of Economics, University of Pennsylvania
Abstract:
This paper models an agent in a multi-period setting who does not update according to Bayes' Rule, and who is self-aware and anticipates her updating behavior when formulating plans. Choice-theoretic axiomatic foundations are provided to capture updating biases that reflect excessive weight given to either prior beliefs, or alternatively, to observed data. A counterpart of the exchangeable Bayesian learning model is also described.