Estimation of Multinomial Logit Models with Unobserved Heterogeneity Using Maximum Simulated Likelihood

Aufsätze referiert extern - Web of Science

Peter Haan, Arne Uhlendorff

In: The Stata Journal 6 (2006), 2, S. 229-245


In this paper, we suggest a Stata routine for multinomial logit models. - with unobserved heterogeneity using maximum simulated likelihood based on. - Halton sequences. The purpose of this paper is twofold. First, we describe the. - technical implementation of the estimation routine and discuss its properties. Further,. - we compare our estimation routine with the Stata program gllamm, which. - solves integration by using Gauss-Hermite quadrature or adaptive quadrature. For. - the analysis, we draw on multilevel data about schooling. Our empirical findings. - show that the estimation techniques lead to approximately the same estimation. - results. The advantage of simulation over Gauss-Hermite quadrature is a marked. - reduction in computational time for integrals with higher dimensions. Adaptive. - quadrature leads to more stable results relative to the other integration methods.. - However, simulation is more time efficient. We find that maximum simulated likelihood. - leads to estimation results with reasonable accuracy in roughly half the. - time required when using adaptive quadrature.

Peter Haan

Head of Department in the Public Economics Department