Parallel Krylov Methods for Econometric Model Simulation

This paper investigates parallel solution methods to simulate large-scale macroeconometric models with forward-looking variables. The method chosen is the Newton-Krylov algorithm, and we concentrate on a parallel solution to the sparse linear system arising in the Newton algorithm. We empirically analyze the scalability of the GMRES method, which belongs to the class of so-called Krylov subspace methods. The results obtained using an implementation of the PETSc 2.0 software library on an IBM SP2 show a near linear scalability for the problem tested.