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

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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.

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Bibliographic Info

Paper provided by Society for Computational Economics in its series Computing in Economics and Finance 1996 with number _045.

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Handle: RePEc:sce:scecf6:_045

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Postal: Department of Econometrics, University of Geneva, 102 Bd Carl-Vogt, 1211 Geneva 4, Switzerland
Web page: http://www.unige.ch/ce/ce96/welcome.html
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  1. Boucekkine, Raouf, 1995. "An alternative methodology for solving nonlinear forward-looking models," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 19(4), pages 711-734, May.
  2. Ray C. Fair & John B. Taylor, 1980. "Solution and Maximum Likelihood Estimation of Dynamic Nonlinear RationalExpectations Models," NBER Technical Working Papers 0005, National Bureau of Economic Research, Inc.
  3. Hall, S G, 1985. "On the Solution of Large Economic Models with Consistent Expectations," Bulletin of Economic Research, Wiley Blackwell, vol. 37(2), pages 157-61, May.
  4. 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, Elsevier, vol. 10(1-2), pages 139-145, June.
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Cited by:
  1. Peter Hollinger, . "The Stacked-Time Simulator in TROLL: A Robust Algorithm for Solving Forward-Looking Models," Computing in Economics and Finance 1996, Society for Computational Economics _026, Society for Computational Economics.

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