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Solving Linear Rational Expectations Models: A Horse Race

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  • Gary Anderson

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Abstract

This paper compares the functionality, accuracy, computational efficiency, and practicalities of alternative approaches to solving linear rational expectations models, including the procedures of (Sims, 1996), (Anderson and Moore, 1983), (Binder and Pesaran, 1994), (King and Watson, 1998), (Klein, 1999), and (Uhlig, 1999). While all six procedures yield similar results for models with a unique stationary solution, the AIM algorithm of (Anderson and Moore, 1983) provides the highest accuracy; furthermore, this procedure exhibits significant gains in computational efficiency for larger-scale models.

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File URL: http://hdl.handle.net/10.1007/s10614-007-9108-0
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Bibliographic Info

Article provided by Society for Computational Economics in its journal Computational Economics.

Volume (Year): 31 (2008)
Issue (Month): 2 (March)
Pages: 95-113

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Handle: RePEc:kap:compec:v:31:y:2008:i:2:p:95-113

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Web page: http://www.springerlink.com/link.asp?id=100248
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Related research

Keywords: Linear rational expectations; Blanchard–Kahn; Saddle point solution;

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References

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  1. Binder,M. & Pesaran,H.M., 1995. "Multivariate Rational Expectations Models and Macroeconomic Modelling: A Review and Some New Results," Cambridge Working Papers in Economics 9415, Faculty of Economics, University of Cambridge.
  2. Broze, L. & Gourieroux, C. & Szafarz, A., . "Solutions of multivariate rational expectations models," CORE Discussion Papers RP -1161, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. Uhlig, H., 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper 1995-97, Tilburg University, Center for Economic Research.
  4. King, Robert G & Watson, Mark W, 1998. "The Solution of Singular Linear Difference Systems under Rational Expectations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1015-26, November.
  5. Anderson, Gary S., 2010. "A reliable and computationally efficient algorithm for imposing the saddle point property in dynamic models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(3), pages 472-489, March.
  6. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-11, July.
  7. Broze, Laurence & Gourieroux Christian & Szafarz A, 1984. "Solutions of dynamic linear rational expectations models," CEPREMAP Working Papers (Couverture Orange) 8421, CEPREMAP.
  8. repec:cup:etheor:v:11:y:1995:i:2:p:229-57 is not listed on IDEAS
  9. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
  10. Zadrozny, Peter A., 1998. "An eigenvalue method of undetermined coefficients for solving linear rational expectations models," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1353-1373, August.
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Citations

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Cited by:
  1. Nikolay Iskrev, 2009. "Local Identification in DSGE Models," Working Papers w200907, Banco de Portugal, Economics and Research Department.
  2. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2013. "Identification-robust analysis of DSGE and structural macroeconomic models," Journal of Monetary Economics, Elsevier, vol. 60(3), pages 340-350.
  3. Heutel, Garth, 2011. "How Should Environmental Policy Respond to Business Cycles? Optimal Policy under Persistent Productivity Shocks," Working Papers 11-8, University of North Carolina at Greensboro, Department of Economics.
  4. Alexander Meyer-Gohde, 2007. "Solving Linear Rational Expectations Models with Lagged Expectations Quickly and Easily," SFB 649 Discussion Papers SFB649DP2007-069, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  5. Hernandez, Kolver, 2013. "A system reduction method to efficiently solve DSGE models," Journal of Economic Dynamics and Control, Elsevier, vol. 37(3), pages 571-576.
  6. Hirokazu Ishise, 2011. "The World Has More Than Two Countries: Implications of Multi- Country International Real Business Cycle Models," IMES Discussion Paper Series 11-E-11, Institute for Monetary and Economic Studies, Bank of Japan.
  7. Ariane Szafarz, 2010. "Financial Crises in Efficient Markets: How Fundamentalists Fuel Volatility," Working Papers CEB 10-052, ULB -- Universite Libre de Bruxelles.
  8. Ariane Szafarz, 2009. "How Did Financial-Crisis-Based Criticisms of Market Efficiency Get It So Wrong?," Working Papers CEB 09-048.RS, ULB -- Universite Libre de Bruxelles.
  9. de Mello, Luiz & Moccero, Diego, 2011. "Monetary policy and macroeconomic stability in Latin America: The cases of Brazil, Chile, Colombia and Mexico," Journal of International Money and Finance, Elsevier, vol. 30(1), pages 229-245, February.
  10. Gary S. Anderson, 2010. "A reliable and computationally efficient algorithm for imposing the saddle point property in dynamic models," Finance and Economics Discussion Series 2010-13, Board of Governors of the Federal Reserve System (U.S.).
  11. Chib, Siddhartha & Ramamurthy, Srikanth, 2010. "Tailored randomized block MCMC methods with application to DSGE models," Journal of Econometrics, Elsevier, vol. 155(1), pages 19-38, March.
  12. Garth Heutel, 2011. "Online Appendix to "How Should Environmental Policy Respond to Business Cycles? Optimal Policy under Persistent Productivity Shocks"," Technical Appendices 10-62, Review of Economic Dynamics.
  13. Alejandro Justiniano & Claudio Michelacci, 2011. "The Cyclical Behavior of Equilibrium Unemployment and Vacancies in the United States and Europe," NBER Chapters, in: NBER International Seminar on Macroeconomics 2011, pages 169-235 National Bureau of Economic Research, Inc.
  14. Alejandro Justiniano & Claudio Michelacci, 2011. "The Cyclical Behavior of Equilibrium Unemployment and Vacancies in the US and Europe," NBER Working Papers 17429, National Bureau of Economic Research, Inc.

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