This paper is concerned with various issues related to inference in large dynamic panel data models (where both n and T increase without bound) in the presence of, possibly, strong cross-sectional dependence. Our first aim is to provide a Central Limit Theorem for estimators of the slope...

The iterative least squares method for estimating panel models with unobservable factor structure is extended to cover the case where the number of factors is unknown a priori. The proposed estimation algorithm optimizes a penalized least squares objective function to estimate the factor...