# Dynamic panel data with large $T$

Given a data set with $N=2634$ and $T=92$, I want to estimate a dynamic model. My first though was to use a classic System GMM estimator, however digging through the literature it turned out that there might be problems with biased estimators when using GMM on data sets with large $T$. I read a couple of papers, mostly based on Alvarez and Arrelano (2003) and most claim that it is the relative size that matters, i.e., $T/N$. If $T/N \to 0$, then the bias should be negligible. However, I also found sources that claimed that the absolute length of $T$ was also relevant.

Also, it seems that there is no shortage of analyses on the asymptotic properties of different estimators for dynamic panel models with large $N$ and $T$, but the results seem contradictive and not coherent.

So my question is twofold:

1. is it true that all what matters is $T$ in relation to $N$, or does the absolute length of $T$ matter as well?
2. which estimator shows the best performance in practice for panels with large $N$ and $T$?