Working Paper

Using a Laplace approximation to estimate the random coefficients logit model by non-linear least squares


Matthew C. Harding, Jerry Hausman

Published Date

5 October 2006


Working Paper (CWP20/06)

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.

This paper is a revised version of CWP01/06.