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Likelihood approximation by numerical integration on sparse grids

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Listed author(s):
  • Heiss, Florian
  • Winschel, Viktor

Abstract

The calculation of likelihood functions of many econometric models requires the evaluation of integrals without analytical solutions. Approaches for extending Gaussian quadrature to multiple dimensions discussed in the literature are either very specific or suffer from exponentially rising computational costs in the number of dimensions. We propose an extension that is very general and easily implemented, and does not suffer from the curse of dimensionality. Monte Carlo experiments for the mixed logit model indicate the superior performance of the proposed method over simulation techniques.

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File URL: http://www.sciencedirect.com/science/article/pii/S0304-4076(07)00255-2
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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 144 (2008)
Issue (Month): 1 (May)
Pages: 62-80

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Handle: RePEc:eee:econom:v:144:y:2008:i:1:p:62-80
Contact details of provider: Web page: http://www.elsevier.com/locate/jeconom

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  1. Kenneth L. Judd, 1998. "Numerical Methods in Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262100711, July.
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  11. repec:pit:wpaper:321 is not listed on IDEAS
  12. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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