A Decomposition Technique for Equilibrium Programming under Uncertainty.

We consider a decomposition technique for solving monotone stochastic Nash equilibrium models based on scenarios and policy aggregation. The algorithm works by splitting the large multi-scenario equilibrium programming problem into separable scenario equilibrium subproblems that are amenable to solution via mixed complementarity problem solvers. We will consider preliminary numerical experience on a small stochastic trade model with two agents, two goods, and two scenarios.