We study optimal growth under learning. We extend the Mirman-Zilcha stochastic growth results characterizing optimal programs for general utility and production functions to the case of learning. We then use recursive methods to study the effect of learning on the dynamic program by considering...

Over the last decade, isotone recursive methods have provided unified catalog of results on existence, characterization, and computation of Markovian Equilibrium Decision Processes (MEDPs) in infinite horizon economies where the second welfare theorem fails. Such economies include models with...

We prove the existence of a minimal state space recursive equilibrium (RE) for a broad class of infinite horizon dynamic general equilibrium models with positive externalities, dynamic complementarities, public policy, equilibrium indeterminacy and sunspots. These are new "multistep" monotone...

This paper uses lattice programming methods along with the extension of Tarski's fixed point theorem due to Veinott (1992) and Zhou (1994) to establish sufficient conditions for existence of sequential symmetric Markov equilibrium in a large class of dynamic games. Our method is constructive and...

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...