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Computing second-order-accurate solutions for rational expectation models using linear solution methods

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  • Lombardo, Giovanni
  • Sutherland, Alan

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. The 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. JEL Classification: C63, E0

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Bibliographic Info

Paper provided by European Central Bank in its series Working Paper Series with number 0487.

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Date of creation: May 2005
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Handle: RePEc:ecb:ecbwps:20050487

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Keywords: Second order approximation; Solution method for rational expectation models;

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  1. Lawrence J. Christiano, 1998. "Solving dynamic equilibrium models by a method of undetermined coefficients," Working Paper 9804, Federal Reserve Bank of Cleveland.
  2. Canton, E.J.F., 1996. "Business Cycles in a Two-Sector Model of Endogenous Growth," Discussion Paper 1996-116, Tilburg University, Center for Economic Research.
  3. 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.
  4. Jinill Kim & Sunghyun Henry Kim, 1999. "Spurious Welfare Reversals in International Business Cycle Models," Virginia Economics Online Papers 319, University of Virginia, Department of Economics.
  5. Henry Kim & Jinill Kim & Ernst Schaumburg & Christopher A. Sims, 2005. "Calculating and Using Second Order Accurate Solutions of Discrete Time Dynamic Equilibrium Models," Discussion Papers Series, Department of Economics, Tufts University 0505, Department of Economics, Tufts University.
  6. 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.
  7. Benigno, Pierpaolo & Woodford, Michael, 2004. "Optimal Stabilization Policy When Wages and Prices are Sticky: The Case of a Distorted Steady State," CEPR Discussion Papers 4740, C.E.P.R. Discussion Papers.
  8. Sutherland, Alan, 2002. "A Simple Second-Order Solution Method For Dynamic General Equilibrium Models," CEPR Discussion Papers 3554, C.E.P.R. Discussion Papers.
  9. Pierpaolo Benigno & Michael Woodford, 2003. "Optimal Monetary and Fiscal Policy: A Linear Quadratic Approach," NBER Working Papers 9905, National Bureau of Economic Research, Inc.
  10. Harald Uhlig, 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper / Institute for Empirical Macroeconomics 101, Federal Reserve Bank of Minneapolis.
  11. 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.
  12. 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.
  13. 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.
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