Most studies of optimal monetary policy under learning rely on optimality conditions derived for the case when agents …, and makes active use of, the learning algorithm agents follow in forming their expectations. In this setup, monetary … policy can influence future expectations through its effect on learning dynamics, introducing an additional tradeoff between …

. In recent years there has been an increasing interest in learning and adaptive behaviour including simulation models. In …

, even though at first sight the markets appear to be only weakly related. We allow for multiple equilibria and learning …

productivity can result from formal R&D effort and from learning by doing. However, during the latter half of the 20th century …, increased technological complexity has made passive learning more difficult. We argue that firms have consequently substituted R …&D for learning and, because skilled workers can overcome the challenges of learning in a more complex environment more …

We examine optimal policy in an open-economy model with uncertainty and learning, where monetary policy actions affect …

intricate learning/evolving process. In this study, an agent-based computational model is employed to look at how a risk …

: recessions "scar" the economy by killing off "potentially good firms". By adding learning to a vintage model, I show that as a … recession arrives and persists, the reduced profitability limits the scope of learning, makes labor less concentrated on good …

network strategy and belief. The learning is modelled as an evolving network process i.e. a local network of agents, with non …