A0484
Title: Heterogeneous grouping structures in panel data
Authors: Aikaterini Chrysikou - Kings College, University of London (United Kingdom) [presenting]
George Kapetanios - Kings College London (United Kingdom)
Abstract: The existence of heterogeneity is examined within a group, in panels with latent grouping structure. The assumption of within-group homogeneity is prevalent in this literature, implying that the formation of groups alleviates cross-sectional heterogeneity, regardless of the prior knowledge of groups. While the latter hypothesis makes inference powerful, it can often be restrictive. Models with richer heterogeneity that can be found both in the cross-section and within a group are allowed without imposing the simple assumption that all groups must be heterogeneous. The further contribution is to the method proposed in a prior study by showing that the model parameters can be consistently estimated and the groups, while unknown, can be identifiable in the presence of different types of heterogeneity. Within the same framework, the validity of assuming both cross-sectional and within-group homogeneity is considered using testing procedures. Simulations demonstrate the good finite-sample performance of the approach in both classification and estimation, while empirical applications across several datasets provide evidence of multiple clusters, as well as reject the hypothesis of within-group homogeneity.
