A Robust and Efficient Method for Solving Nonlinear Rational Expectations ModelsWP/96/106-EA A Robust and Efficient Method for Solving Nonlinear Rational Expectations Models by Michel Jillard and Douglas Laxton The development and use of forward-looking macro models in policymaking institutions has proceeded at a pace much slower than predicted in the early 1980s. An important reason is that researchers have not had access to robust and efficient solution techniques for solving nonlinear forward-looking models. The numerical complexity of solving a forward-looking macro model is considerably more onerous than solving a traditional backward-looking, reduced-form model of the same size. In many cases, researchers have been forced either to linearize their models or to focus their attention on very small models that could be solved easily with available technology. This paper discusses the development and implementation of a new algorithm based on a Newton-Raphson iterative method. It is used for solving MULTIMOD, the IMF's multicountry model of the world economy. This algorithm is considerably faster and much less prone to simulation failure than traditional algorithms and can also be used to solve individual country models of the same size. |