Optimal Control of Large, Forward-Looking Models: Efficient Solutions and Two Examples

Abstract

An optimal control tool is described that is particularly useful for computing rules of large-scale models where users might otherwise have difficulty determining the state vector a priori and where the inversion of large, sparse matrices is involved. A small-scale demonstration is presented, as are data on performance with the Board of Governors large-scale rational expectations macroeconometric model, FRB/US.