【Micro Seminar】Updating Under Imprecise Information
研討會日期 : 2024-01-16
時間 : 10:30
主講人 : Professor Fernando Payró Chew
地點 : Conference Room B110
演講者簡介 : Professor Fernando Payró Chew received his PhD from Boston University in 2021. He is currently an Assistant Professor at Universitat Autònoma de Barcelona. His research interests are Microeconomic Theory, Decision Theory, Behavioral Economics, and Game Theory.
演講摘要 : This paper models an agent that ranks actions that have uncertain payoffs after observing a signal that could have been generated by multiple objective information structures. Under the assumption that the agent's preferences conform to the multiple priors model, we show that a simple behavioral axiom characterizes an updating rule, called Generalized Bayesian updating, an updating rule in which the priors and information structures considered are subjective. Our axiom requires that whenever all the possible sources of information agree that it is more "likely" that an action that has uncertain payoffs is better than one that has certain payoffs, the agent prefers the former. Axiomatizations for several special cases of generalized Bayesian updating are also provided. Finally, we consider the situation where the informational content of a signal is purely subjective. We characterize the existence of a subjective set of information structures under full Bayesian updating for two extreme cases: (i) No ex-ante state ambiguity, and (ii) No signal ambiguity.