Seminar by Yusufcan Masatlıoğlu (University of Maryland)

Abstract:

We introduce a new model of stochastic choice, the "Progressive Random Choice (PRC) model.'' In a PRC model, the decision-maker randomizes over a collection of choice functions which are ordered with respect to some reference order and we call this structure progressiveness. A PRC representation identifies the collection of choices and associated probabilities uniquely, moreover, it can explain a rich set of stochastic choice. We are particularly interested in PRC where each choice function satisfies a well-known bounded rationality structure, namely "less-is-more.'' The characterization of less-is-more-PRC relies on two simple axioms: U-regularity and weak-regularity. We further show that the reference ordering can be endogenously derived in this class.

*joint with Emel Filiz-Ozbay