This chapter develops a new limit theory for panel data with large
numbers of cross section, n, and time series, T, observations. The
results apply when n and T tend to infinity simultaneously and provide
useful tools for obtaining convergencies in probability and in
distribution in cases where the panel data may be cross sectionally
heterogenous in a fairly general way. We demonstrate how the new theory
can be applied to derive asymptotics for a panel regression where
regressors are generated by a local to unit root process with
heterogenous localizing coefficients across cross section.