This paper examines the robustness characteristics of optimal control policies derived under the assumption of rational expectations to alternative models of expectations. We assume that agents have imperfect knowledge about the precise structure of the economy and form expectations using a...

This paper develops the Parameterized Expectations Approach (PEA) for solving nonlinear dynamic stochastic models with rational expectations. The method can be applied to a variety of models, including models with strong nonlinearities, sub-optimal equilibria, and many continuous state...

This paper presents new, computationally efficient algorithms for solution and estimation of nonlinear dynamic rational expectations models. The innovations in the algorithms are as follows: (1) The entire solution path is obtained simultaneously by taking a small number of Newton steps, using...

This paper develops a simple rational expectations model of the inflation process that is used to test the Fisher effect. The model emphasizes the link between money and expected inflation, and hence the monetary regime followed by the central bank. The model is estimated with U.S. data over the...

This paper examines the robustness characteristics of optimal control policies derived under the assumption of rational expectations to alternative models of expectations formation and uncertainty about the natural rates of interest and unemployment. We assume that agents have imperfect...

Nominal interest rates are unlikely to be generated by unit-root processes. Using data on short and long interest rates from eight developed and six emerging economies, we test the expectations hypothesis using cointegration methods under the assumption that interest rates are near integrated....

This paper presents techniques to solve for optimal simple monetary policy rules in rational expectations models, assuming discretion. The techniques described are notable for the flexibility they provide over the structure of the policy rule being solved for. Specifically, not all state...