A Model of Stochastic Choice From Lists

We study stochastic choice from lists. All lists present the same set of alternatives albeit in different orders. Faced with a list, the decision maker makes her choice in two stages. In the first stage she searches through the list up to a random depth capacity k. In the second stage she chooses from the first k alternatives using a stochastic choice function over menus. We show that the underlying primitives (depth probabilities and stochastic choice function over menus) are revealed by choice from lists. We characterize the model and two of its special cases. In the first special case the decision maker deterministically chooses the best observed alternative according to a given preference. In the second, the decision maker maximizes random preferences