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A system reduction method to efficiently solve DSGE models

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  • Hernandez, Kolver

Abstract

The paper presents a system reduction method (SRM) to improve the computational time to solve a large class of dynamic stochastic general equilibrium (DSGE) models with the methods of Anderson and Moore (1985), Klein (2000), Sims (2002) or Uhlig (1995). I measure the efficiency gains with seven models ranging from 47 to 333 equations. The time reduction for the Anderson–Moore algorithm aim ranges from 10% to 71%; Klein's function solab reduces its time between 51% and 79%; the time reduction for Sims' function gensys increases from 25% to 59%; Uhlig's function solve reduces its time between 31% and 87%. The time reduction can be crucial for Bayesian estimation of medium to large scale models.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:dyncon:v:37:y:2013:i:3:p:571-576
    DOI: 10.1016/j.jedc.2012.09.013
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    References listed on IDEAS

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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.
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    4. King, Robert G & Watson, Mark W, 2002. "System Reduction and Solution Algorithms for Singular Linear Difference Systems under Rational Expectations," Computational Economics, Springer;Society for Computational Economics, vol. 20(1-2), pages 57-86, October.
    5. Schmitt-Grohe, Stephanie & Uribe, Martin, 2004. "Solving dynamic general equilibrium models using a second-order approximation to the policy function," Journal of Economic Dynamics and Control, Elsevier, vol. 28(4), pages 755-775, January.
    6. Malin Adolfson & Stefan Laséen & Jesper Lindé & Lars E.O. Svensson, 2011. "Optimal Monetary Policy in an Operational Medium‐Sized DSGE Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(7), pages 1287-1331, October.
    7. Harald Uhlig, 1995. "A toolkit for analyzing nonlinear dynamic stochastic models easily," Discussion Paper / Institute for Empirical Macroeconomics 101, Federal Reserve Bank of Minneapolis.
    8. Gary Anderson, 2008. "Solving Linear Rational Expectations Models: A Horse Race," Computational Economics, Springer;Society for Computational Economics, vol. 31(2), pages 95-113, March.
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    10. Blanchard, Olivier Jean & Kahn, Charles M, 1980. "The Solution of Linear Difference Models under Rational Expectations," Econometrica, Econometric Society, vol. 48(5), pages 1305-1311, July.
    11. Anderson, Gary & Moore, George, 1985. "A linear algebraic procedure for solving linear perfect foresight models," Economics Letters, Elsevier, vol. 17(3), pages 247-252.
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    More about this item

    Keywords

    Solution of DSGE models; System reduction algorithm; Solution of linear rational expectation models; Bayesian estimation;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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