Multidimensional endogenous gridpoint method: Solving triangular dynamic stochastic optimization problems without root-finding operations

- Certain dynamic stochastic models can be solved without root fining operations.
- The paper describes a class of such models using five conditions.
- The solution method is multidimensional endogenous gridpoint method (EGM).
- Typical member of this class is a model of multiple stock dynamics.

This paper defines the class of triangular dynamic stochastic optimization problems with multiple continuous choices which can be solved by the multidimensional generalization of the method of endogenous gridpoints without costly root-finding operations. The typical member of this class is a model of multiple asset dynamics, with potential applications in wealth, health and human capital accumulation, portfolio problems, multisector growth models, etc.