SPECIFICATION AND TESTING OF SOME MODIFIED COUNT DATA MODELS
SPECIFICATION AND TESTING OF SOME MODIFIED COUNT DATA MODELS
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DOI：
10.1016/0304-4076(86)90002-3
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发表时间：
1986-12-01
影响因子：
6.3
通讯作者：
MULLAHY, J
中科院分区：
文献类型：
--
作者：
MULLAHY, J
本文探讨了一些改进的计数数据模型的规范和测试。与熟悉的计数数据模型（例如泊松）相比，这些替代方法允许更灵活地规范数据生成过程（dgp），并为根据基本模型的标准过度分散或不充分分散的数据建模提供了一种自然的方法。在所考虑的情况下，分布的熟悉形式作为提议的修改分布的参数限制版本。因此，提出了仅使用标准模型的易于计算的ML估计的限制的分数测试。还考虑了Hausman（1978）和White（1982）提出的测试。然后将测试应用于使用饮料消费调查微数据估计的计数数据模型。
This paper explores the specification and testing of some modified count data models. These alternatives permit more flexible specification of the data-generating process (dgp) than do familiar count data models (e.g., the Poisson), and provide a natural means for modeling data that are over- or underdispersed by the standards of the basic models. In the cases considered, the familiar forms of the distributions result as parameter-restricted versions of the proposed modified distributions. Accordingly, score tests of the restrictions that use only the easily-computed ML estimates of the standard models are proposed. The tests proposed by Hausman (1978) and White (1982) are also considered. The tests are then applied to count data models estimated using survey microdata on beverage consumption.