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http://hdl.handle.net/10419/31371
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| Title: | | A new algorithm for solving dynamic stochastic macroeconomic models  |
| Authors: | | Salyer, Kevin D. Dorofeenko, Victor Lee, Gabriel |
| Issue Date: | | 2005 |
| Series/Report no.: | | Working papers // University of California, Department of Economics 06,2 |
| Abstract: | | We introduce a new algorithm that can be used to solve stochastic dynamic general equilibrium models. This approach exploits the fact that the equations defining equilibrium can be viewed as a set of differential algebraic equations in the neighborhood of the steady-state. Then a modified recursive upwind Gauss Seidel method can be used to determine the global solution. This method, within the context of a standard real business cycle model, is compared to projection, perturbation, and linearization approaches and demonstrated to be fast and globally accurate. This comparison is done within a discrete state setting with heteroskedasticity in the technology shocks. It is shown that linearization methods perform poorly in this environment even though the unconditional variance of shocks is relatively small. |
| JEL: | | C63 C68 E37 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Working Papers, Department of Economics, UC Davis
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