Bootstrap confidence intervals for a break date in linear regressions

초록

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. © 2020 Informa UK Limited, trading as Taylor & Francis Group.

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