Discrete Time Dynamic Programming with Recursive Preferences: Optimality and Applications
This paper provides an alternative approach to the theory of dynamic programming, designed to accommodate the kinds of recursive preference specifications that have become popular in economic and financial analysis, while still supporting traditional additively separable rewards. The approach exploits the theory of monotone convex operators, which turns out to be well suited to dynamic maximization. The intuition is that convexity is preserved under maximization, so convexity properties found in preferences extend naturally to the Bellman operator.