Recent Award

This research deals with estimation and inference problems for dynamic panel-data models under time-varying individual heterogeneities and cross-sectional dependence (common shocks). An important aspect of these problems is that the individual heterogeneity and the common shocks are correlated with the explanatory variables. This correlation is fundamental for economic variables. Standard procedures such as within-group estimators will lead to inconsistent inferences. This research explores new estimation procedures and related inference problems. It also presents feasible implementation of the suggested procedures.

The last two decades have witnessed a huge development of panel data econometrics, as panel data techniques can solve issues that are hard to solve by either the cross section or time series procedures alone. With the increasing availability of panel data sets, the associated techniques have become the key tools of empirical researchers. The recent advancement and the importance of the panel techniques are summarized by three excellent monographs: Arellano (2003), Batagi (2006), and Hsiao (2003). Much of this literature has focused on the case of time-invariant individual heterogeneities.