moments, and the method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as antithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis– Hastings algorithm and its variant Gibbs

: The simulation variance in the estimation of mixed logit parameters is found, in our application, to be lower with 100 Halton draws than with 1000 random draws. This finding confirms Bhat's (1999a) results and implies significant reduction in run times for mixed logit estimation. Further

We describe the properties of (t,m, s)-nets and Halton draws. Four types of (t,m, s)-nets, two types of Halton draws, and independent draws are compared in an application of maximum simulated likelihood estimation of a mixed logit model. All of the quasi-random procedures are found to perform far

pseudo-random number draws. A popular type of quasi-random sequence in this context is the Halton sequence, in its different forms. In this paper, we compare the performance of standard, scrambled and shuffled Halton sequences in the estimation of various Mixed Logit models. The analysis shows that

for Halton draws is a generalization of some do file code by Arne Uhlendorff (DIW Berlin) which, in turn, uses a program posted on Statalist by Nick Cox (Durham University) in August 2004: see

to transform distributions into others with most of the required characteristics. In essence, a uniform sequence which is transformed into a new sequence with the required distribution. The subject of this article is to consider the well known highly uniform Halton sequence and modifications to it. The intent

of the MSL approach (with 150 scrambled and randomized Halton draws) and the simulation-free CML approach are of about the same order in all panel structures in terms of the absolute percentage bias (APB) of the parameters and econometric efficiency. However, the simulation-free CML approach exhibits

programs- to base test statistics for mixed models on simulations using asymmetric draws (e.g. Halton draws). Problem 1: Inconsistent LR tests due to asymmetric draws: This paper shows that when the estimated likelihood functions depend on standard deviations of mixed parameters this practice is very

Quasi-random number sequences have been used extensively for many years in the simulation of integrals that do not have a closed-form expression, such as Mixed Logit and Multinomial Probit choice probabilities. Halton sequences are one example of such quasi-random number sequences, and various

of Bayesian efficiency for SC designs of various dimensions. The authors conclude that the predominantly employed method of using pseudo Monte Carlo draws is unlikely to result in leading to truly Bayesian efficient SC designs. The quasi Monte Carlo methods analyzed here (Halton, Sobol, and Modified Latin