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...

In this paper, we provide an overview of an emerging class of monotone map methods in analyzing distorted equilibrium in dynamic economies. In particular, we focus on proving the existence and characterization of competitive equilibrium in non-optimal versions of the optimal growth models. We...

Production takes time, and labor supply and profit maximization decisions that relate to current production are typically made before all shocks affecting that production have been realized. In this paper we re-examine the problem of stochastic optimal growth with aggregate risk where the timing...