In models of active learning or experimentation, agents modify their actions to affect the distribution of a signal that provides information about future payoffs. A standard result in the experimentation literature is that agents experiment, if at all, to increase information. This finding is a...

We embed learning (without experimentation) in optimal growth. We extend the Mirman-Zilcha results of stochastic optimal growth to the learning case. We use recursive methods to study the effect of learning on the dynamic program by considering the case of iso-elastic utility and linear...

We introduce learning in a Brock-Mirman environment and study the effect of risk generated by the planner's econometric activity on optimal consumption and investment. Here, learning introduces two sources of risk about future payoffs: structural uncertainty and uncertainty from the anticipation...