B1273
Title: Detection of changes in panel data models
Authors: Marie Huskova - Charles University (Czech Republic) [presenting]
Abstract: Panel regression models with cross-sectional dimension $N$ are considered. The aim is to test whether the intercept in the model remains unchanged throughout the observation period based on $T$ observations. The test procedure involves using a CUSUM-type statistic derived via a quasi-likelihood argument. Limit behavior under the null distribution of the test under strong mixing and stationarity conditions on the errors and regressors are presented. Both independent panels, as well as the case of mild cross-sectional dependence, are considered. A self-normalized version of the test is also proposed, which is convenient from a practical perspective since the estimation of long-run variances is avoided entirely. The theoretical results are supported by a simulation study that indicates that the test works well in the case of small to moderate sample sizes. An illustrative application of the procedure to US mutual fund data demonstrates the relevance of the proposed procedure in financial settings.
