Matthew Harding (Institute for Fiscal Studies and Stanford University) Jerry Hausman () (Institute for Fiscal Studies and Massachusetts Institute of Technology)
Abstract
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.
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Paper provided by Centre for Microdata Methods and Practice, Institute for Fiscal Studies in its series CeMMAP working papers with number
CWP20/06.
Length: 30 pp. Date of creation: Oct 2006 Date of revision: Handle: RePEc:ifs:cemmap:20/06
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