Abstract: We describe an algorithm for calculating second order approximations to the solutions to nonlinear
stochastic rational expectation models. The paper also explains methods for using such an approximate
solution to generate forecasts, simulated time paths for the model, and evaluations of expected welfare
differences across different versions of a model. The paper gives conditions for local validity of the
approximation that allow for disturbance distributions with unbounded support and allow for
non-stationarity of the solution process.
Keywords: Solving dynamic equilibrium models, second order accurate solution.
Full paper (166 KB PDF)
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Last update: December 3, 2003
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