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Computing Second-Order-Accurate Solutions for Rational Expectation Models Using Linear Solution Methods

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  • Giovanni Lombardo

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  • Alan Sutherland

    ()

Abstract

This paper shows how to compute a second-order accurate solution of a non-linear rational expectation model using algorithms developed for the solution of linear rational expectation models. This result is a state-space representation for the realized values of the variables of the model. This state-space representation can easily be used to compute impulse responses as well as conditional and unconditional forecasts.

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File URL: http://www.st-andrews.ac.uk/economics/CDMA/papers/cp0504.pdf
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Bibliographic Info

Paper provided by Centre for Dynamic Macroeconomic Analysis in its series CDMA Conference Paper Series with number 0504.

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Date of creation: Mar 2005
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Handle: RePEc:san:cdmacp:0504

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Web page: http://www.st-andrews.ac.uk/cdma
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Keywords: Second-order approximation; solution method for rational expectation models.;

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  1. Klein, Paul, 2000. "Using the generalized Schur form to solve a multivariate linear rational expectations model," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1405-1423, September.
  2. Pierpaolo Benigno & Michael Woodford, 2004. "Optimal stabilization policy when wages and prices are sticky: The case of a distorted steady state," Discussion Papers 0405-03, Columbia University, Department of Economics.
  3. Alan Sutherland, 2002. "A Simple Second-Order Solution Method for Dynamic General Equilibrium Models," Discussion Paper Series, Department of Economics 0211, Department of Economics, University of St. Andrews.
  4. Christiano, Lawrence J, 2002. "Solving Dynamic Equilibrium Models by a Method of Undetermined Coefficients," Computational Economics, Society for Computational Economics, vol. 20(1-2), pages 21-55, October.
  5. Jinill Kim & Sunghyun Kim & Ernst Schaumburg & Christopher A. Sims, 2003. "Calculating and using second order accurate solutions of discrete time dynamic equilibrium models," Finance and Economics Discussion Series 2003-61, Board of Governors of the Federal Reserve System (U.S.).
  6. Kim, Jinill & Kim, Sunghyun Henry, 2003. "Spurious welfare reversals in international business cycle models," Journal of International Economics, Elsevier, vol. 60(2), pages 471-500, August.
  7. Harald Uhlig, 1998. "A Toolkit for Analysing Nonlinear Dynamic Stochastic Models Easily," QM&RBC Codes 123, Quantitative Macroeconomics & Real Business Cycles.
  8. King, Robert G & Watson, Mark W, 2002. "System Reduction and Solution Algorithms for Singular Linear Difference Systems under Rational Expectations," Computational Economics, Society for Computational Economics, vol. 20(1-2), pages 57-86, October.
  9. Stephanie Schmitt-Grohe & Martin Uribe, 2002. "Solving Dynamic General Equilibrium Models Using a Second-Order Approximation to the Policy Function," NBER Technical Working Papers 0282, National Bureau of Economic Research, Inc.
  10. 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.
  11. Erik Canton, 2002. "Business cycles in a two-sector model of endogenous growth," Economic Theory, Springer, vol. 19(3), pages 477-492.
  12. Jinill Kim & Sunghyun Kim & Ernst Schaumburg & Christopher A. Sims, 2003. "Calculating and Using Second Order Accurate Solutions of Discrete Time," Levine's Bibliography 666156000000000284, UCLA Department of Economics.
  13. Pierpaolo Benigno & Michael Woodford, 2004. "Optimal Monetary and Fiscal Policy: A Linear-Quadratic Approach," NBER Chapters, in: NBER Macroeconomics Annual 2003, Volume 18, pages 271-364 National Bureau of Economic Research, Inc.
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