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Journal Articles
November 2007
Article
Using a Laplace approximation to estimate the random coefficients logit model by non-linear least squares
Type: Journal Articles
Authors: Matthew Harding and Jerry Hausman
Volume, issue, pages: Vol. 48, No. 4, pp. 1311-1328
Previous version: cemmap Working Papers [Details]
Previous version: cemmap Working Papers [Details]

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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 paper 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, both in terms of accuracy and computational time.

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