This paper presents a new numerical algorithm for solving the Sylvester equation involved in higher-order perturbation methods developed for solving stochastic dynamic general equilibrium models. The new algorithm surpasses other methods used so far (including the very popular doubling algorithm) in terms of computational time, memory consumption, and numerical stability. Copyright Springer Science + Business Media, Inc. 2005stochastic dynamic general equilibrium models, high-order permutations, computational algorithms,

Many central banks in emerging and advanced economies have adopted an inflation-forecast targeting (IFT) approach to monetary policy, in order to successfully establish a stable, lowinflation environment. To support policy making, each has developed a structured system of forecasting and policy analysis appropriate to its needs. A common component is a modelbased forecast with an endogenous policy interest rate path. The approach is characterized, among other things, by transparent communications-some IFT central banks go so far as to publish their policy interest rate projection. Some elements of this regime, although a work still in progress, are worthy of consideration by central banks that have not yet officially adopted full-fledged inflation targeting.

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This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. This is the second of a series of papers that are being written as part of a larger project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and crosscountry linkages. In this paper, we estimate a small quarterly projection model of the US, Euro Area, and Japanese economies. The model is estimated with Bayesian techniques, which provide a very efficient way of imposing restrictions to produce both plausible dynamics and sensible forecasting properties. We show how the model can be used to construct efficient baseline forecasts that incorporate judgment imposed on the near-term outlook.

This Working Paper should not be reported as representing the views of the IMF. The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate. This is the first of a series of papers that are being written as part of a project to estimate a small quarterly Global Projection Model (GPM). The GPM project is designed to improve the toolkit for studying both own-country and crosscountry linkages. In this paper, we estimate a small quarterly projection model of the U.S. economy. The model is estimated with Bayesian techniques, which provide a very efficient way of imposing restrictions to produce both plausible dynamics and sensible forecasting properties. After developing a benchmark model without financial-real linkages, we introduce such linkages into the model and compare the results with and without linkages.