Asymptotically unbiased inference for a dynamic panel model with fixed effects when both n and T are large

We consider a dynamic panel AR(1) model with fixed effects when both "n" and "T" are large. Under the "T fixed n large" asymptotic approximation, the maximum likelihood estimator is known to be inconsistent due to the well-known incidental parameter problem. We consider an alternative asymptotic approximation where "n" and "T" grow at the same rate. It is shown that, although the MLE is asymptotically biased, a relatively simple fix to the MLE results in an asymptotically unbiased estimator. The bias corrected MLE is shown to be asymptotically efficient by a Hajek type convolution theorem. Keywords: dynamic Panel, VAR, large n-large T asymptotics, bias correction, efficiency.