Abstract
The aim of this paper is to develop stochastic methods for detection whether a 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. To this end, we consider several competing ratio type test statistics and derive their asymptotic distributions under the no change null hypothesis.
Moreover, we prove the consistency of the tests under the alternative. The main advantage of the proposed approaches is that the variance of the observations neither has to be known nor estimated.
The results are illustrated through a simulation study. An application of the procedure to actuarial data is presented.