Finite-Sample Properties of Percentile and Percentile-t Bootstrap Confidence Intervals for Impulse Responses
通过蒙特卡洛模拟，比较了脉冲响应估计中多种自助法置信区间的覆盖精度和平均长度，发现百分位-t区间在小样本下表现差且不稳定，而百分位区间更短更准确。
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. © 2000 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology