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Likelihood approximation by numerical integration on sparse grids

Journal of econometrics. Bd. 144. H. 1. Amsterdam u.a.: Elsevier 2008 S. 62 - 80

Erscheinungsjahr: 2008

ISBN/ISSN: 0304-4076

Publikationstyp: Zeitschriftenaufsatz

Sprache: Englisch

Doi/URN: 10.1016/j.jeconom.2007.12.004

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Inhaltszusammenfassung


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 mi...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. » weiterlesen» einklappen

Autoren


Heiss, Florian (Autor)
Winschel, Viktor (Autor)

Klassifikation


DFG Fachgebiet:
Wirtschaftswissenschaften

DDC Sachgruppe:
Statistik