EXTENSIONS OF HURDLE MODELS FOR OVERDISPERSED COUNT DATA
基于计数数据文献的最新进展，提出了两种障碍模型的扩展形式，使常用设定更灵活，并通过参数限制检验嵌套模型，以健康经济学实例展示其应用价值。
Hurdle models are frequently used to model count data. Recent developments in the count data literature make it possible to relax commonly imposed assumptions of these models. On the basis of these findings, two extensions of hurdle models that make popular specifications more flexible are developed. Both extensions nest the models that have been used so far, so they can be tested by appropriate parametric restrictions. An example from health economics illustrates the relevance of both model extensions.