This paper examines the convergence of payoffs and strategies in Erev and Roth`s model of reinforcement learning. When all players use this rule it eliminates iteratively dominated strategies and in two-person constant-sum games average payoffs converge to the value of the game. Strategies...

This paper studies learning in monotone Bayesian games with one-dimensional types and finitely many actions. Players switch between actions at a set of thresholds.  A learning algorithm under which players adjust their strategies in the direction of better ones using payoffs received at...

This paper studies uniqueness of equilibrium in symmetric 2 x 2 bayesian games.  It shows that if signals are highly but not perfectly dependent then players play their risk-dominant actions for all but a vanishing set of signal realizations.  In contrast to the global games literature, noise...

This paper shows that the price of a painting sold at an art auction and the experts' pre-sale valuations are anchored on the price at which the painting previously sold at auction. We are able to separate anchoring from rational learning by using the identifying strategy that the unobservable...

This paper tests for reference dependence, using data from Impressionist and Contemporary Art auctions. We distinguish reference dependence based on ‘rule of thumb’ learning from reference dependence based on ‘rational’ learning. Furthermore, we distinguish pure reference dependence from...

This paper presents an empirical study of paintings that have failed to meet their reserve price at auction. In the art trade it is often claimed that when an advertised item goes unsold at auction, its future value will be affected. We have constructed a new dataset specifically for the purpose...