Dorofeenko, Victor and Lee, Gabriel S. and Salyer, Kevin D. (2010) A new algorithm for solving dynamic stochastic macroeconomic models. JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 34 (3). pp. 388-403. ISSN 0165-1889, 1879-1743
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This paper introduces a new algorithm, the recursive upwind Gauss-Seidel method, and applies it to solve a standard stochastic growth model in which the technology shocks exhibit heteroskedasticity. This method exploits the fact that the equations defining equilibrium can be viewed as a set of algebraic equations in the neighborhood of the steady-state. In a non-stochastic setting, the algorithm, in essence, continually extends a local solution to a globally accurate solution. When stochastic elements are introduced, it then uses a recursive scheme in order to determine the global solution. This method is compared to projection, perturbation, and linearization approaches and is shown to be fast and globally accurate. We also demonstrate that linearization methods perform poorly in an environment of heteroskedasticity even though the unconditional variance of technology shocks is relatively small and similar to that typically used in RBC analysis. (C) 2009 Elsevier B.V. All rights reserved.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | AGGREGATE GROWTH-MODELS; APPROXIMATION; Numerical methods; Gauss Seidel method; Projection methods; Real business cycles; Crash state |
| Subjects: | 300 Social sciences > 330 Economics |
| Divisions: | Business, Economics and Information Systems > Institut für Volkswirtschaftslehre und Ökonometrie > Lehrstuhl für Immobilienökonomie (Prof. Dr. Gabriel Lee) Business, Economics and Information Systems > Institut für Immobilienenwirtschaft / IRE|BS > Lehrstuhl für Immobilienökonomie (Prof. Dr. Gabriel Lee) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 05 Aug 2020 08:46 |
| Last Modified: | 05 Aug 2020 08:46 |
| URI: | https://pred.uni-regensburg.de/id/eprint/25086 |
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