CONSISTENT ESTIMATION OF ZERO‐INFLATED COUNT MODELS
针对健康经济学中常用的零膨胀计数模型，提出泊松拟似然估计量，该估计量在存在过多零值时仍能一致估计，无需指定完整分布，并通过模拟和医疗需求应用验证其优势。
Applications of zero-inflated count data models have proliferated in health economics. However, zero-inflated Poisson or zero-inflated negative binomial maximum likelihood estimators are not robust to misspecification. This article proposes Poisson quasi-likelihood estimators as an alternative. These estimators are consistent in the presence of excess zeros without having to specify the full distribution. The advantages of the Poisson quasi-likelihood approach are illustrated in a series of Monte Carlo simulations and in an application to the demand for health services.