Abstract
The main goal is to develop and, consequently, compare stochastic methods for detecting whether a structural change in panel data occurred at some unknown time or not. Panel data of our interest consist of a moderate or relatively large number of panels, while the panels contain a small number of observations.
Testing procedures to detect a possible common change in means of the panels are established. Ratio and non-ratio type test statistics are considered.
Their asymptotic distributions under the no change null hypothesis are derived. Moreover, we prove the consistency of the tests under the alternative.
The advantage of the ratio statistics compared to the non-ratio ones is that the variance of the observations neither has to be known nor estimated. A simulation study reveals that the proposed ratio statistic outperforms the non-ratio one by keeping the significance level under the null, mainly when stronger dependence within the panel is present.
However, the non-ratio statistic incorrectly rejects the null in the simulations more often than it should, which yields higher power compared to the ratio statistic.