BAYESIAN-ANALYSIS OF LOGIT-MODELS USING NATURAL CONJUGATE PRIORS

This study provides a Bayesian investigation of conditional logit and multinomial logit models based on a conjugate prior which has many appealing computational properties. A one-parameter 'neutral' prior is developed which concentrates prior mass over the region corresponding to equiprobable alternatives. This prior is particularly attractive in sensitivity analysis. An empirical example of occupational choice illustrates the proposed techniques.