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USING A LAPLACE APPROXIMATION TO ESTIMATE THE RANDOM COEFFICIENTS LOGIT MODEL BY NONLINEAR LEAST SQUARES *
Author(s) -
Harding Matthew C.,
Hausman Jerry
Publication year - 2007
Publication title -
international economic review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.658
H-Index - 86
eISSN - 1468-2354
pISSN - 0020-6598
DOI - 10.1111/j.1468-2354.2007.00463.x
Subject(s) - laplace's method , curse of dimensionality , mathematics , laplace transform , laplace distribution , logit , nonlinear system , expression (computer science) , extension (predicate logic) , multivariate statistics , mathematical optimization , statistics , computer science , mathematical analysis , physics , quantum mechanics , programming language
Current methods of estimating the random coefficients logit model employ simulations of the distribution of the taste parameters through pseudo‐random sequences. These methods suffer from difficulties in estimating correlations between parameters and computational limitations such as the curse of dimensionality. This article provides a solution to these problems by approximating the integral expression of the expected choice probability using a multivariate extension of the Laplace approximation. Simulation results reveal that our method performs very well, in terms of both accuracy and computational time.