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An Application of Nonstationary Iterative Methods for Solving a Multi-Country Model with Rational Expectations

Author

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  • Manfred Gilli
  • Giorgio Pauletto

    () (Department of Econometrics, University of Geneva)

Abstract

In this paper we present an implementation of a Newton method based on iterative Krylov subspace methods such as GMRES, QMR and BiCGSTAB for solving large nonlinear macroeconometric models. These methods are tested for the solution of the model MULTIMOD and the computational costs of the different techniques are compared together with a sparse direct method.

Suggested Citation

  • Manfred Gilli & Giorgio Pauletto, "undated". "An Application of Nonstationary Iterative Methods for Solving a Multi-Country Model with Rational Expectations," Computing in Economics and Finance 1996 _045, Society for Computational Economics.
  • Handle: RePEc:sce:scecf6:_045
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    File URL: http://www.unige.ch/ses/metri/pauletto/ce96.ps
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    References listed on IDEAS

    as
    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 1169-1185, July.
    2. Hall, S G, 1985. "On the Solution of Large Economic Models with Consistent Expectations," Bulletin of Economic Research, Wiley Blackwell, vol. 37(2), pages 157-161, May.
    3. Fisher, P. G. & Holly, S. & Hughes Hallett, A. J., 1986. "Efficient solution techniques for dynamic non-linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 10(1-2), pages 139-145, June.
    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.
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    Cited by:

    1. Peter Hollinger, "undated". "The Stacked-Time Simulator in TROLL: A Robust Algorithm for Solving Forward-Looking Models," Computing in Economics and Finance 1996 _026, Society for Computational Economics.

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