We use an experiment to explore how subjects learn to play against computers which are programmed to follow one of a number of standard learning algorithms. The learning theories are (unbeknown to subjects) a best response process, fictitious play, imitation, reinforcement learning, and a trial...

We introduce a generalized theoretical approach to study imitation and subject it to rigorous experimental testing. In our theoretical analysis we find that the different predictions of previous imitation models are due to different informational assumptions, not to different behavioral rules....

We study optimal capital requirement regulation in a dynamic quantitative model in which nonfinancial firms, as well as households, hold deposits. Firms hold deposits for precautionary reasons and to facilitate the acquisition of production inputs. Our theoretical analysis identifies a novel...

We define tail interdependence as a situation where extreme outcomes for some variables are informative about such outcomes for other variables. We extend the concept of multiinformation to quantify tail interdependence, decompose it into systemic and residual interdependence and measure the...