The method of endogenous gridpoints for solving dynamic stochastic optimization problems

This paper introduces a solution method for numerical dynamic stochastic optimization problems that avoids rootfinding operations. The idea is applicable to many microeconomic and macroeconomic problems, including life cycle, buffer-stock, and stochastic growth problems. Software is provided.