Use of panels can enhance the power of empirical analysis and allows estimation of
parameters that might not have been identified along the time or the cross section dimensions
alone. These benefits come at a cost. In the case of linear panel data models with a
short time span the increased power is usually achieved under assumptions of parameter
homogeneity and error cross section independence. Short panels with autocorrelated disturbances
also pose a new identification problem, namely how to distinguished between
dynamics and state dependence. (Arellano, 2003, ch. 5).