A Decomposition Method to Deflate the Curse of Dimensionality for Dynamic Stochastic Models

Computing equilibria in dynamic stochastic economies is still a technically difficult task. Economists are aware of the so-call curse of dimensionality and the limits placed on the ability to solve high-dimensional dynamic models. Many of the economic models subjected to the curse of dimensionality present some special structure that can be exploited in a efficient manner. This paper introduces a decomposition method to compute the equilibrium path in dynamic models by breaking the problem into a set of smaller independent subproblems. We illustrate the performance of the method solving a set of dynamic stochastic equilibrium models