Modeling Discrete Choice with Uncertain Data: An Augmented MNL Estimator

摘要: This article introduces a multinomial logit model that uses ancillary information to control for uncertainty in both the observed choices made by respondents, and attributes of respondent's choice set. Simulated data are used compare performance this estimator versus simpler models, under several different kinds uncertainty.