Bounded rationality and learning in market competition

This thesis promotes the use of bounded rationality in economic models. The assumption of perfect rationality often imposes high informational and computational burden on economic agents and predictions based on this assumption are not in line with observed behavior in some cases. Models of bounded rationality may better explain actual behavior in such situations.
In the thesis we consider market models where firms are boundedly rational: they do not know the demand for their product and they use different learning methods to determine the optimal price, they have incorrect beliefs about their competitors’ behavior or they do not make use of all the available information. We investigate how bounded rationality affects the market outcome and what the possible welfare effects are.