RECENT DEVELOPMENTS IN COUNT DATA MODELLING: THEORY AND APPLICATION
综述了处理非负整数因变量的统计方法，包括泊松、负二项等模型，并应用于劳动力流动数据，展示考虑数据结构的优势。
Abstract. This paper deals with statistical methods for modelling individual behavior when the endogenous variable is a nonnegative integer. Examples are the number of children, the number of job changes or the number of shopping trips in a given period. Several approaches—Poisson, robust Poisson, negative binomial (NEGBIN), NEGBIN k , hurdle Poisson, truncated‐at‐zero Poisson—are discussed with a focus on specification, estimation, and testing. An application to labor mobility data illustrates the gain obtained by carefully taking into account the specific structure of the data.