Finite-sample properties of percentile and percentile-t bootstrap confidence intervals for impulse responses
成果类型：
Article; Proceedings Paper
署名作者：
Kilian, L
署名单位：
University of Michigan System; University of Michigan; Centre for Economic Policy Research - UK
刊物名称：
REVIEW OF ECONOMICS AND STATISTICS
ISSN/ISSBN：
0034-6535
DOI：
10.1162/003465399558517
发表日期：
1999-11
页码：
652-660
关键词：
摘要：
A Monte Carlo analysis of the coverage accuracy and average length of alternative bootstrap confidence intervals for impulse-response estimators shows that the accuracy of equal-tailed and symmetric percentile-t intervals can be poor and erratic in small samples (both in models with large roots and in models without roots near the unit circle). In contrast, some percentile bootstrap intervals may be both shorter and more accurate. The accuracy of percentile-t intervals improves with sample size, but the sample size required for reliable inference can be very large. Moreover, for such large sample sizes, virtually all bootstrap intervals tend to have excellent coverage accuracy.
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