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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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    More about this item

    Keywords

    Solution of DSGE models; System reduction algorithm; Solution of linear rational expectation models; Bayesian estimation;
    All these keywords.

    JEL classification:

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

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