A Bayesian analysis of the multinomial probit model with fully identified parameters

We present a new prior and corresponding algorithm for Bayesian analysis of the multinomial probit model. Our new approach places a prior directly on the identified parameter space. The key is the specification of a prior on the covariance matrix so that the (1,1) element if fixed at 1 and it is possible to draw from the posterior using standard distributions. Analytical results are derived which can be used to aid in assessment of the prior. (C) 2000 Elsevier Science S.A. All rights reserved. JEL classification: C11; C25; C33; C35.