Advanced Search
MyIDEAS: Login to save this paper or follow this series

Solving, Estimating and Selecting Nonlinear Dynamic Economic Models without the Curse of Dimensionality

Contents:

Author Info

  • Viktor Winschel

    (University of Mannheim)

Abstract

A welfare analysis of a risky policy is impossible within a linear or linearized model and its certainty equivalence property. The presented algorithms are designed as a toolbox for a general model class. The computational challenges are considerable and I concentrate on the numerics and statistics for a simple model of dynamic consumption and labor choice. I calculate the optimal policy and estimate the posterior density of structural parameters and the marginal likelihood within a nonlinear state space model. My approach is even in an interpreted language twenty time faster than the only alternative compiled approach. The model is estimated on simulated data in order to test the routines against known true parameters. The policy function is approximated by Smolyak Chebyshev polynomials and the rational expectation integral by Smolyak Gaussian quadrature. The Smolyak operator is used to extend univariate approximation and integration operators to many dimensions. It reduces the curse of dimensionality from exponential to polynomial growth. The likelihood integrals are evaluated by a Gaussian quadrature and Gaussian quadrature particle filter. The bootstrap or sequential importance resampling particle filter is used as an accuracy benchmark. The posterior is estimated by the Gaussian filter and a Metropolis- Hastings algorithm. I propose a genetic extension of the standard Metropolis-Hastings algorithm by parallel random walk sequences. This improves the robustness of start values and the global maximization properties. Moreover it simplifies a cluster implementation and the random walk variances decision is reduced to only two parameters so that almost no trial sequences are needed. Finally the marginal likelihood is calculated as a criterion for nonnested and quasi-true models in order to select between the nonlinear estimates and a first order perturbation solution combined with the Kalman filter.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://128.118.178.162/eps/ge/papers/0507/0507014.pdf
Download Restriction: no

Bibliographic Info

Paper provided by EconWPA in its series GE, Growth, Math methods with number 0507014.

as in new window
Length: 100 pages
Date of creation: 29 Jul 2005
Date of revision:
Handle: RePEc:wpa:wuwpge:0507014

Note: Type of Document - pdf; pages: 100
Contact details of provider:
Web page: http://128.118.178.162

Related research

Keywords: stochastic dynamic general equilibrium model; Chebyshev polynomials; Smolyak operator; nonlinear state space filter; Curse of Dimensionality; posterior of structural parameters; marginal likelihood;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Viktor Winschel & Markus Krätzig, 2008. "JBendge: An Object-Oriented System for Solving, Estimating and Selecting Nonlinear Dynamic Models," SFB 649 Discussion Papers SFB649DP2008-034, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  2. Kenneth L. Judd & Lilia Maliar & Serguei Maliar & Rafael Valero, 2013. "Smolyak Method for Solving Dynamic Economic Models: Lagrange Interpolation, Anisotropic Grid and Adaptive Domain," NBER Working Papers 19326, National Bureau of Economic Research, Inc.
  3. Jesús Fernández-Villaverde & Juan F. Rubio-Ramirez, 2006. "Estimating Macroeconomic Models: A Likelihood Approach," Levine's Bibliography 122247000000000849, UCLA Department of Economics.
  4. Heiss, Florian & Winschel, Viktor, 2008. "Likelihood approximation by numerical integration on sparse grids," Journal of Econometrics, Elsevier, vol. 144(1), pages 62-80, May.
  5. Creel, Michael & Kristensen, Dennis, 2011. "Indirect Likelihood Inference," Dynare Working Papers 8, CEPREMAP.
  6. Christophe Gouel, 2013. "Comparing Numerical Methods for Solving the Competitive Storage Model," Computational Economics, Society for Computational Economics, vol. 41(2), pages 267-295, February.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpge:0507014. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (EconWPA).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.