ASYMPTOTIC ESTIMATION OF THE E-GINI INDEX
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E-Gini 指数的渐近估计
- 研究问题
- 收入分布只满足较少假设时，经验 E-Gini 指数是否一致且渐近正态，其渐近方差能否方便地估计？
- 方法与思路
- 作者分析经验 E-Gini 指数的渐近性质，推导渐近方差的显式公式，并构造一致且计算简便的方差估计量。
- 材料陈述的贡献
- 摘要称，论文建立该收入不平等指数的一致性与渐近正态性，并为衡量其抽样不确定性提供可计算的方差估计。
- 阅读关注点
- 应核对所谓最小分布假设、指数参数的允许范围、抽样条件，以及方差公式和一致估计量所需的可积性要求。
- 阅读边界
- 所给出版社摘要未列明具体假设、有限样本精度或复杂抽样处理，不能直接推断对所有收入数据均可有效推断。
原文摘要
Under minimal assumptions on the distribution of income, we demonstrate that Chakravarty's empirical (1988, International Economic Review 29, 147–156) E-Gini index is consistent and asymptotically normal. We also derive an explicit formula for the asymptotic variance of the index and then construct a consistent and computationally straightforward estimator for it.Sincere thanks are due to the co-editor Oliver B. Linton and two anonymous referees whose constructive criticism, advice, and queries helped me in reshaping the paper considerably. As advised by a referee, I had the great pleasure of communicating with Garry F. Barrett and Stephen G. Donald and learning about their interesting and closely related results. The starting point of my work on the project was correspondence with Joseph L. Gastwirth in the spring of 2000 that resulted in our joint work on the S-Gini index. I am grateful to Joseph L. Gastwirth for his time, his advice, and his numerous suggestions that followed. The help, in addition to interest in the project, by Ying Zhang of the Statistical Laboratory at the University of Western Ontario is greatly appreciated; the analysis of the dependence of σF,α2 on parameters presented in Table 1 is due to her. This research was partially supported by an NSERC of Canada individual research grant at the University of Western Ontario.