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Sparse Direct Methods for Model Simulation

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Author Info
Manfred Gilli
Giorgio Pauletto

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Abstract

In this paper, different strategies to exploit the sparse structure in the solution techniques for macroeconometric models with forward-looking variables are discussed. First, the stacked model is decomposed into recursive submodels without destroying its original block pattern. Next, we concentrate on how to efficiently solve the sparse linear system in the Newton algorithm. In this frame, a multiple block diagonal LU factorization and a sparse Gaussian elimination are presented. The algorithms are compared by solving the country model for Japan in MULTIMOD.

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Publisher Info
Paper provided by Département d'Econométrie, Université de Genève in its series Cahiers du Département d'Econométrie with number 95.06.

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Length: 21 pages
Date of creation: 1995
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Handle: RePEc:gen:geneem:95.06

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Related research
Keywords: Newton type algorithms; Block LU; Sparse Gaussian Elimination; Forward-looking Models;

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Find related papers by JEL classification:
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Fair, Ray C & Taylor, John B, 1983. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rational Expectations Models," Econometrica, Econometric Society, vol. 51(4), pages 1169-85, July. [Downloadable!] (restricted)
    Other versions:
  2. Paul R. Masson & Guy Meredith & Steven A. Symansky, 1990. "MULTIMOD Mark II: A Revised and Extended Model," IMF Occasional Papers 71, International Monetary Fund.
  3. Jon Faust & Ralph Tryon, 1995. "Block distributed methods for solving multi-country econometric models," International Finance Discussion Papers 516, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
  4. Boucekkine, Raouf, 1995. "An alternative methodology for solving nonlinear forward-looking models," Journal of Economic Dynamics and Control, Elsevier, vol. 19(4), pages 711-734, May. [Downloadable!] (restricted)
  5. Juillard, Michel, 1996. "Dynare : a program for the resolution and simulation of dynamic models with forward variables through the use of a relaxation algorithm," CEPREMAP Working Papers (Couverture Orange) 9602, CEPREMAP. [Downloadable!]
  6. Gilli, M & Pauletto, G & Garbely, M, 1992. "Equation Reordering for Iterative Processes--A Comment," Computer Science in Economics & Management, Springer, vol. 5(2), pages 147-53, May.
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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Franz, Wolfgang & Göggelmann, Klaus & Schellhorn, Martin & Winker, Peter, 1998. "Quasi - Monte Carlo Methods in Stochastic Simulations," ZEW Discussion Papers 98-03, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. [Downloadable!]
  2. Gary S. Anderson, . "An Application of Sparse Methods to Solving a Multi-Country Model With Rational Expectations," Computing in Economics and Finance 1996 _063, Society for Computational Economics. [Downloadable!]
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