A new test for common breaks in heterogeneous panel data models
In this paper, we develop a new test to detect whether break points are common in heterogeneous panel data models where the time series dimension T could be large relative to cross-section dimension N. The error process is assumed to be cross-sectionally independent. The test is based on the cumulative sum (CUSUM) of ordinary least squares (OLS) residuals. We derive the asymptotic distribution of the detecting statistic under the null hypothesis, while proving the consistency of the test under the alternative. Monte Carlo simulations and an empirical example show good performance of the test.
|Author(s):||Peiyun Jiang (a), Eiji Kurozumi (b)|
|Affiliation:||(a) Hitotsubashi Institute for Advanced Study, Hitotsubashi University
(b) Department of Economics, Hitotsubashi University
|Issued Date:||May 2021|
|Keywords:||CUSUM test, panel data, structural change, common breaks|
|Links:||PDF, HERMES-IR, RePEc,|