October 2018

Reliably Computing Nonlinear Dynamic Stochastic Model Solutions: An Algorithm with Error Formulas

Gary S. Anderson


This paper provides a new technique for representing discrete time nonlinear dynamic stochastic time invariant maps. Using this new series representation, the paper augments the usual solution strategy with an additional set of constraints thereby enhancing algorithm reliability. The paper also provides general formulas for evaluating the accuracy of proposed solutions. The technique can readily accommodate models with occasionally binding constraints and regime switching. The algorithm uses Smolyak polynomial function approximation in a way which makes it possible to exploit a high degree of parallelism.

Accessible materials (.zip)

Keywords: Econometric modeling, mathematical and quantitative methods

DOI: https://doi.org/10.17016/FEDS.2018.070

PDF: Full Paper

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Last Update: January 09, 2020