Inference for Generalized Gini Indices Using the Iterated-Bootstrap Method
介绍如何使用迭代自助法对广义基尼指数进行统计推断，解决传统百分位法置信区间名义水平需要调整的问题，帮助经济学家比较不同时期的收入不平等变化。
Inference using the iterated-bootstrap method proposed by Hall is appealing for cases in which the percentile method needs to be used but the nominal level of a confidence interval has to be adjusted. One natural application is for generalized Gini indices of income inequality. When applying these theoretical inequality measures directly to sample data for the purpose of statistical inference, economists must come up with some measure of sampling variation. This is particularly the case when the index estimates are compared over time to infer information on the changes of social welfare and inequality. Although there are difficulties in the existing inferential procedures, a more intuitive approach is to use the iterated-bootstrap method.