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Computational Economics

, Volume 31, Issue 2, pp 95–113 | Cite as

Solving Linear Rational Expectations Models: A Horse Race

  • Gary S. AndersonEmail author
Article

Abstract

This paper compares the generality, accuracy and computational speed of alternative approaches to solving linear rational expectations models, including the procedures of Sims (Solving linear rational expectations models, 1996), Anderson and Moore (Unpublished manuscript, 1983), Binder and Pesaran (Multivariate rational expectations models and macroeconometric modelling: A review and some new results, 1994), King and Watson (International Economic review, 39, 1015–1026, 1998), Klein (Journal of Economic Dynamics and Control, 24, 1405–1423, 1999), and Uhlig (A toolkit for analyzing nonlinear dynamic stochastic models easily, 1999). While all six procedures yield equivalent results for models with a unique stationary solution, the algorithm of Anderson and Moore (Unpublished manuscript, 1983) is the fastest and provides the highest accuracy; furthermore, the speed advantage increases with the size of the model.

Keywords

Linear rational expectations Blanchard–Kahn Saddle point solution 

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References

  1. Anderson Gary, Moore George (1985). A linear algebraic procedure for solving linear perfect foresight models. Economics Letters 17(3): 247–252CrossRefGoogle Scholar
  2. Binder, Michael, & Pesaran, M. Hashem (1994). Multivariate rational expectations models and macroeconometric modelling: A review and some new results. Seminar Paper, May 1994.Google Scholar
  3. Blanchard, Olivier Jean, & Kahn, C. (1980). The solution of linear difference models under rational expectations. Econometrica, 48.Google Scholar
  4. Broze Laurence, Gouriéroux Christian, Szafarz Ariane (1995). Solutions of multivariate rational expectations models. Econometric Theory 11: 229–257CrossRefGoogle Scholar
  5. Gantmacher, F. R. (1959). Theory of matrices. Chelsea Publishing.Google Scholar
  6. Golub, Gene H., & van Loan, Charles F. (1989). Matrix computations. Johns Hopkins.Google Scholar
  7. King Robert G., Watson Mark W. (1998). The solution of singular linear difference systems under rational expectations. International Economic Review 39(4): 1015–1026CrossRefGoogle Scholar
  8. Klein Paul (1999). Using the generalized schur form to solve a multivariate linear rational expectations model. Journal of Economic Dynamics and Control 24: 1405–1423CrossRefGoogle Scholar
  9. Sims, Christopher A. (1996). Solving linear rational expectations models. Seminar paper.Google Scholar
  10. Uhlig, Harald (1999). A toolkit for analyzing nonlinear dynamic stochastic models easily. User’s Guide.Google Scholar
  11. Zadrozny Peter A. (1998). An eigenvalue method of undetermined coefficients for solving linear rational expectations models. Journal of Economic Dynamics and Control 22: 1353–1373CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Board of Governors of the Federal Reserve SystemWashingtonUSA

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