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Evaluating Approximate Equilibria of Dynamic Economic Models

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Paul Pichler ()

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Abstract

This paper evaluates the performances of Perturbation Methods, the Parameterized Expectations Algorithm and Projection Methods in finding approximate decision rules of the basic neoclassical stochastic growth model. In contrast to the existing literature, we focus on comparing numerical methods for a given functional form of the approximate decision rules, and we repeat the evaluation for many di®erent parameter sets. We ¯nd that signi¯cant gains in accuracy can be achieved by moving from linear to higher-order approximations. Our results show further that among linear and quadratic approximations, Perturbation Methods yield particularly good results, whereas Projection Methods are well suited to derive higher-order approximations. Finally we show that although the structural parameters of the model economy have a large e®ect on the accuracy of numerical approximations, the ranking of competing methods is largely independent from the calibration.

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Paper provided by University of Vienna, Department of Economics in its series Vienna Economics Papers with number 0510.

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Date of creation: Dec 2005
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Handle: RePEc:vie:viennp:0510

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Find related papers by JEL classification:
C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques
C68 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computable General Equilibrium Models

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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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  12. Alfonso Novales & Javier J. PÈrez, 2004. "Is It Worth Refining Linear Approximations to Non-Linear Rational Expectations Models?," Computational Economics, Springer, vol. 23(4), pages 343-377, 06. [Downloadable!]
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  13. Burkhard Heer & Alfred Maussner, 2004. "Computation of Business Cycle Models: A Comparison of Numerical Methods," CESifo Working Paper Series CESifo Working Paper No. , CESifo Group Munich. [Downloadable!]
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  14. Manuel S. Santos, 2000. "Accuracy of Numerical Solutions using the Euler Equation Residuals," Econometrica, Econometric Society, vol. 68(6), pages 1377-1402, November.
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  16. Sims, Christopher A, 2002. "Solving Linear Rational Expectations Models," Computational Economics, Springer, vol. 20(1-2), pages 1-20, October. [Downloadable!]
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  17. Gary S. Anderson, 2000. "A Systematic Comparison Of Alternative Linear Rational Expectation Model Solution Techniques," Computing in Economics and Finance 2000 142, Society for Computational Economics.
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  19. 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. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Paul Pichler, 2007. "On the accuracy of low-order projection methods," Economics Bulletin, Economics Bulletin, vol. 3(50), pages 1-8. [Downloadable!]
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