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The Anderson-Moore Algorithm AIM Home Page |
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Exploring Dynamic Properties of Non Linear Economic Models Through Asymptotic Linearization
Linearizing non linear models about their steady state makes it possible to apply the Anderson-Moore Algorithm(AIM) to investigate the asymptotic properties of the model. AIM determines whether the non linear model has the saddle point property and provides diagnostics for models which do not. For models that have the saddle point property AIM provides a set of terminal conditions for solving the non linear models that improve upon the traditional approach of setting the end of the trajectory to the steady state values. Using the improved asymptotic constraint typically halves the computational burden associated with solving the nonlinear problem. A suite of Mathematica programs can manipulate nonlinear model equations to provide closed form solutions for many(sometimes all) of the linearization and AIM analysis. These calculations useful for estimating a restricted VAR. Also useful for getting starting values for estimating nonlinear certainty equivalence models. Employs functional programming paradigm to facilitate coherent interactions between numerical and symbolic characterizations of model features.