DISCRETE SPATIAL CHOICE MODELS FOR AGGREGATE DESTINATIONS*
针对空间选择中聚合目的地存在异质性的问题，推导了基于嵌套Logit模型估计最大效用的新模型，并证明聚合替代项的误差项渐近服从Gumbel分布。
ABSTRACT. In problems of spatial choice, the choice set is typically more aggregated than the one considered by decision‐makers, often because choice data are available only at the aggregate level. These aggregate choice units will exhibit heterogeneity in utility and in size. To be consistent with utility maximization, a choice model must estimate choice probabilities on the basis of the maximum utility within heterogeneous aggregates. The ordinary multinomial logit model applied to aggregate choice units fails this criterion as it is estimated on the basis of average utility. In this paper, we derive and discuss a model which utilizes the theory underlying the nested logit model to estimate the appropriate maximum utilities of aggregates. We also demonstrate that the aggregate alternative error terms are asymptotically Gumbel, thereby relaxing the assumption of extreme value distributed error terms. This is accomplished with help from the asymptotic theory of extremes.