A Generalized Time Iteration Method for Solving Dynamic Optimization Problems with Occasionally Binding Constraints

摘要

We study a generalized version of Coleman (J Bus Econ Stat 8:27-29, 1990)'s time iteration method (GTI) for solving dynamic optimization problems. Our benchmark framework is an irreversible investment model with labor-leisure choice. The GTI algorithm is simple to implement and provides advantages in terms of speed relative to Howard's (Dynamic Programming and Markov Processes. MIT Press, Cambridge, MA, 1960) improvement algorithm. A second application on a heterogeneous-agents incomplete-markets model further explores the performance of GTI.