A RANK‐ORDERED LOGIT MODEL WITH UNOBSERVED HETEROGENEITY IN RANKING CAPABILITIES
提出一个能内生描述个体排名能力的模型，当部分受访者能对多个选项排序时，该模型估计的偏好更有效，且不受排名能力不足导致的偏差影响。
Abstract To study preferences, respondents to a survey are usually asked to select their most preferred option from a set. Preferences can be estimated more efficiently if respondents are asked to rank all alternatives. When some respondents are unable to perform the ranking task, using the complete ranking may lead to a substantial bias. We introduce a model which endogenously describes the ranking capabilities of individuals. Estimated preferences based on this model are more efficient when at least some individuals are able to rank more than one item, and they do not suffer from biases due to ranking inabilities of respondents. Copyright © 2010 John Wiley & Sons, Ltd.