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Bootstrap confidence intervals for a break date in linear regressions
Journal of Statistical Computation and Simulation ( IF 1.2 ) Pub Date : 2020-06-26 , DOI: 10.1080/00949655.2020.1777998
Seong Yeon Chang 1
Affiliation  

In this article, we consider bootstrap confidence intervals, namely percentile bootstrap for obtaining confidence intervals of a break date in linear regression models. Elliott and Müller [Confidence sets for the date of a single break in linear time series regressions. J Econometrics. 1997;141:1196–1218] point out that the simulated coverage probabilities are below the nominal rate when the limiting distribution is used to form confidence intervals of the break date. This is particularly so if the magnitude of a break is relatively small. We investigate the finite sample performance of bootstrap confidence intervals for the break date in linear regressions with serially correlated errors using Monte Carlo simulations. The simulation results confirm that bootstrap confidence intervals outperform those constructed by the conventional method. An empirical analysis is provided for illustrative purpose.

中文翻译:

线性回归中中断日期的 Bootstrap 置信区间

在本文中,我们考虑自举置信区间,即用于在线性回归模型中获得中断日期的置信区间的百分位自举。Elliott 和 Müller [线性时间序列回归中单个中断日期的置信度集。J 计量经济学。1997;141:1196-1218] 指出,当限制分布用于形成中断日期的置信区间时,模拟覆盖概率低于名义利率。如果中断的幅度相对较小,则尤其如此。我们使用蒙特卡罗模拟研究了具有序列相关误差的线性回归中中断日期的引导置信区间的有限样本性能。模拟结果证实自举置信区间优于传统方法构建的置信区间。
更新日期:2020-06-26
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