Bootstrap Standard Error Estimates and Inference

• 成果类型: Article
• 署名作者: Hahn, Jinyong; Liao, Zhipeng
• 署名单位: University of California System; University of California Los Angeles
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.3982/ECTA17912
• 发表日期: 2021
• 页码: 1963-1977
• 关键词: generalized-method; jackknife; variance

摘要

Asymptotic justification of the bootstrap often takes the form of weak convergence of the bootstrap distribution to some limit distribution. Theoretical literature recognized that the weak convergence does not imply consistency of the bootstrap second moment or the bootstrap variance as an estimator of the asymptotic variance, but such concern is not always reflected in the applied practice. We bridge the gap between the theory and practice by showing that such common bootstrap based standard error in fact leads to a potentially conservative inference.