Fitted probabilities from widely used Bayesian multinomial probit models can depend strongly on the choice of a base category, which is to uniquely identify parameters model. This paper proposes novel identification strategy, and associated prior distribution for model parameters, that renders symmetric with respect relabeling outcome categories. The new permits an efficient Gibbs algorithm sam...

The multinomial probit (MNP) model is a popular tool for analyzing choice behavior as it allows correlation between alternatives. Because current specifications employ full covariance matrix of the latent utilities alternatives, they are not scalable to large number This article proposes factor structure on matrix, which makes sets. main challenge in estimating this that parameters require iden...

The multinomial probit model is often used to analyze choice behavior. However, estimation with existing Markov chain Monte Carlo (MCMC) methods computationally costly, which limits its applicability large datasets. This article proposes a variational Bayes method that accurate and fast, even when number of alternatives observations are considered. Variational usually require an analytical expr...

We consider a discrete choice model in which the payoffs to each of an agent’s n actions are subjected to the average of m i.i.d. shocks, and use tools from large deviations theory to characterize the rate of decay of the probability of choosing a given suboptimal action as m approaches infinity. Our model includes the multinomial probit model of Myatt and Wallace (2003) as a special case. We s...

A broad class of models that routinely appear in several fields can be expressed as partially or fully discretized Gaussian linear regressions. Besides including classical response settings, this also encompasses probit, multinomial probit and tobit regression, among others, thereby yielding one the most widely-implemented families routine applications. The relevance such representations has st...

Within the framework of Monte Carlo experiments, this paper systematically compares different versions of the simulated z-test (using the GHK simulator) in oneand multiperiod multinomial probit models. One important finding is that, in the flexible probit models, the tests on parameters of explanatory variables mostly provide robust results in contrast to the tests on variance-covariance parame...