Before revision: Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to  Markov chain Monte Carlo (MCMC) methods for Bayesian estimation of mixed logit models .
After revision: Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to Markov chain Monte Carlo (MCMC) methods for Bayesian estimation of mixed logit models with unobserved inter-individual taste variation. However, such a model formulation may be too restrictive in panel data settings, as tastes may vary both between individuals as well as across choice tasks by the same individual.