We develop a model of the gambler's fallacy -- the mistaken belief that random sequences should exhibit systematic reversals. We show that an individual who holds this belief and observes a sequence of signals can exaggerate the magnitude of changes in an underlying state but underestimate their...

This article explores some conceptual issues in the study of well-being using the traditional economic approach of inferring preferences solely from choice behavior. We argue that choice behavior alone can never reveal which situations make people better off, even with unlimited data and under...

We develop a model that fleshes out, extends, and modifies existing models of reference dependent preferences and loss aversion while accommodating most of the evidence motivating these models. Our approach makes reference-dependent theory more broadly applicable by avoiding some of the ways...

In social-learning environments, we investigate implications of the assumption that people naively believe that each previous person's action reflects solely that person's private information, leading them to systematically imitate all predecessors even in the many circumstances where rational...

Participants in experimental games typically can only choose actions, without making comments about other participants’ future actions. In sequential two-person games, we allow first movers to express a preference between responder choices. We find that responder behavior differs...

Harstad and Selten (this forum) raise interesting questions about the relative promise of optimization models and bounded-rationality models in making progress in economics. This article builds from their analysis by indicating the potential for using neoclassical (broadly defined) optimization...

We study observational learning in environments with congestion costs: an agent's payoff from choosing an action decreases as more predecessors choose that action. Herds cannot occur if congestion on every action can get so large that an agent prefers a different action regardless of his beliefs...

People believe that, even in very large samples, proportions of binary signals might depart significantly from the population mean.  We model this "non-belief in the Law of Large Numbers" by assuming that a person believes that proportions in any given sample might be determined by a rate...