Munich Personal RePEc Archive

To pool or not to pool: a partially heterogeneous framework

Sarafidis, Vasilis and Weber, Neville (2009): To pool or not to pool: a partially heterogeneous framework.

This is the latest version of this item.

[thumbnail of MPRA_paper_36155.pdf]

Download (280kB) | Preview


This paper proposes a partially heterogeneous framework for the analysis of panel data with fixed T. In particular, the population of cross-sectional units is grouped into clusters, such that slope parameter homogeneity is maintained only within clusters. Our method assumes no a priori information about the number of clusters and cluster membership and relies on the data instead. The unknown number of clusters and the corresponding partition are determined based on the concept of �partitional clustering�, using an information-based criterion. It is shown that this is strongly consistent, i.e. it selects the true number of clusters with probability one as N approaches unity. Simulation experiments show that the proposed criterion performs well even with moderate N and the resulting parameter estimates are close to the true values. We apply the method in a panel data set of commercial banks in the US and we find five clusters, with significant differences in the slope parameters across clusters.

Available Versions of this Item

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.