In a model of incomplete, heterogeneous information, with externalities and strategic interactions, we analyze the possibility for learning to act as coordination device. We build on the framework proposed by Angeletos and Pavan (2007) and extend it to a dynamic multiperiod setting where agents...

We report experiments designed to test the theoretical possibility, first discovered by Shapley (1964), that in some games learning fails to converge to any equilibrium, either in terms of marginal frequencies or of average play. Subjects played repeatedly in fixed pairings one of two 3 × 3...

This paper examines moral hazard in teams over time. Agents are collectively engaged in an uncertain project, and their individual efforts are unobserved. Free-riding leads not only to a reduction in effort, but also to procrastination. The collaboration dwindles over time, but never ceases as...

We study the intergenerational accumulation of knowledge in an infinite-horizon model of communication. Each in a sequence of players receives an informative but imperfect signal of the once-and-for-all realization of an unobserved state. The state affects all players' preferences over present...

This paper extends several existing learning models to investigate their fixed points (their long run predictions of play). The fixed points of the model are not necessarily at the Nash equilibria of the payoff matrices but are a function of both the Nash equilibria and the parameters of the...

Experimental data is used to test a variety of learning models using a model that extends several of the existing learning models. Generally, the parameter estimate are in the expected ranges. Individual agent parameter estimates indicate that there is considerable individual heterogeneity....

We study investment and consumption decisions in a dynamic game under learning. To that end, we present a model in which agents not only extract a resource for consumption, but also invest in technology to improve the future stock. At the same time, the agents learn about the stochastic process...

A counter example to the Grossman and Stiglitz (1980) finding of the impossibility of informationally efficient markets is produced using discrete choice dynamics to govern the evolution of the trader population that choose between being informed or uninformed based on past performance.

Most studies of optimal monetary policy under learning rely on optimality conditions derived for the case when agents have rational expectations. In this paper, we derive optimal monetary policy in an economy where the Central Bank knows, and makes active use of, the learning algorithm agents...

We consider a linear univariate rational expectations model, with a predetermined variable, and study existence and stability of solutions driven by an extraneous finite-state Markov process. We show that when the model is indeterminate there exists a new class of k-state dependent sunspot...