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Smolyak Method for Solving Dynamic Economic Models: Lagrange Interpolation, Anisotropic Grid and Adaptive Domain

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Author Info

  • Kenneth L. Judd

    (Hoover Institution, Stanford University)

  • Lilia Maliar

    (Department of Economics, Stanford University)

  • Serguei Maliar

    (Department of Economics, Stanford University)

  • Rafael Valero

    (University of Alicante)

Abstract

First, we propose a more e¢ cient implementation of the Smolyak method for inter- polation, namely, we show how to avoid costly evaluations of repeated basis functions in the conventional Smolyak formula. Second, we extend the Smolyak method to include anisotropic constructions; this allows us to target higher quality of approximation in some dimensions than in others. Third, we show how to e¤ectively adapt the Smolyak hyper- cube to a solution domain of a given economic model. Finally, we advocate the use of low-cost .xed-point iteration, instead of conventional time iteration. In the context of one- and multi-agent growth models, we .nd that the proposed techniques lead to sub- stantial increases in accuracy and speed of a Smolyak-based projection method for solving dynamic economic models.

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File URL: http://economics.byu.edu/Documents/Macro%20Lab/Working%20Paper%20Series/BYUMCL2013-02.pdf
File Function: First version, 2013
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Bibliographic Info

Paper provided by Brigham Young University, Department of Economics, BYU Macroeconomics and Computational Laboratory in its series BYU Macroeconomics and Computational Laboratory Working Paper Series with number 2013-02.

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Length: 47 pages
Date of creation: Aug 2013
Date of revision:
Handle: RePEc:byu:byumcl:201302

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Keywords: Intergenerational Risk Sharing; Government Transfer Policies; Aggregate Shocks; Incomplete Markets; Stochastic Simulation;

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References

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Cited by:
  1. Julien Albertini & Arthur Poirier, 2014. "Unemployment benefits extensions at the zero lower bound on nominal interest rate," SFB 649 Discussion Papers SFB649DP2014-019, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

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