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Reliably Computing Nonlinear Dynamic Stochastic Model Solutions: An Algorithm with Error Formulas
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 ...
Global Dynamics in a Search and Matching Model of the Labor Market
We study global and local dynamics of a simple search and matching model of the labor market. We show that the model can be locally indeterminate or have no equilibrium at all, but only for parameterizations that are empirically implausible. In contrast to the local results, we show that the model exhibits chaotic and periodic dynamics for reasonable parameter values both in backward and forward time. In contrast to earlier work, we establish these results analytically without placing numerical restrictions on the parameters.