Methods of computing the type II iterations involved in extended path algorithms for the solution of economic models with forward-looking expectations are described. Particular attention is directed at a method involving the application of a Newton algorithm to a 'stacked' equation system that inclu
Krylov methods for solving models with forward-looking variables
✍ Scribed by Manfred Gilli; Giorgio Pauletto
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 174 KB
- Volume
- 22
- Category
- Article
- ISSN
- 0165-1889
No coin nor oath required. For personal study only.
✦ Synopsis
The simulation of large macroeconometric models containing forward-looking variables can become impractical when using exact Newton methods. The difficulties generally arise from the use of direct methods for the solution of the linear system in the Newton step. In such cases, nonstationary iterative methods, also called Krylov methods, provide an interesting alternative. In this paper we apply such methods to simulate a real world econometric model. Our numerical experiments confirm the interesting features of these techniques: low computational complexity and storage requirements. We also discuss a block preconditioner suitable for the particular class of models solved.
📜 SIMILAR VOLUMES
In a recent paper [E. Defez, R. Company, E. Ponsoda, L. Jódar, Aplicación del método CE-SE a la ecuación de adveccióndifusión con coeficientes variables, Congreso de Métodos Numéricos en Ingenierá (SEMNI), Granada, Spain, 2005] a modified space-time conservation element and solution element scheme f