Recent theoretical research on oligopolistic competition suggests that prices may increase when more firms compete in a market. However, this finding is based on comparative-static analyses of static models, which overlook the possibility that sellers may be able to charge supra-competitive...

Recent theoretical research on oligopolistic competition suggests that prices may increase when more firms compete in a market. However, this finding is based on comparative-static analyses of static models, which overlook the possibility that sellers may be able to charge supra-competitive...

We investigate the role tacit collusion plays in Asymmetric Price Transmission (APT), the tendency of prices to respond more rapidly to positive than to negative cost shocks. Using a laboratory experiment that isolates the effects of tacit collusion, we observe APT pricing behavior in markets...

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 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 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...