Book Description
A second theoretical contribution of this work relates to efficient estimation of nested logit models for choice-based samples. Currently, the benefit of collecting choice-based samples diminishes when modeling consumers' behavior using NL models because of the need to use consistent estimators that are often inefficient and/or complicated to implement. In contrast, benefits of using choice-based samples are retained when using the simple multinomial logit model because, under conditions that are relatively easy to satisfy in practice, the exogenous sample maximum likelihood estimator can be used. This study shows the exogenous sample maximum likelihood estimator can also be used with choice-based samples for NL models.