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The Anderson-Moore Algorithm AIM Home Page |
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A Reliable and Computationally Efficient Algorithm for Imposing the Saddle Point Property in Dynamic Models
Anderson & Moore describe a powerful method for solving linear saddle point models. The algorithm has proved useful in a wide array of applications including analyzing linear perfect foresight models, providing initial solutions and asymptotic constraints for nonlinear models. The algorithm solves linear problems with dozens of lags and leads and hundreds of equations in seconds. The technique works well for both symbolic algebra and numerical computation. Although widely used at the Federal Reserve, few outside the central bank know about or have used the algorithm. This paper attempts to present the current algorithm in a more accessible format in the hope that economists outside the Federal Reserve may also find it useful. In addition, over the years there have been undocumented changes in approach that have improved the efficiency and reliability of algorithm. This paper describes the present state of development of this set of tools.