Could someone please give an explanation of why two-step dynamic panel data estimator is better then one-step? Can't quiet understand it... For example, from xtabond2 manual in STATA:
"two-step estimator is asymptotically efficient and robust to whatever patterns of heteroskedasticity and cross-correlation the sandwich covariance estimator models. Historically, researchers often reported one-step results as well because of downward bias in the computed standard errors in two-step. But as the next subsection explains, Windmeijer (2005) has greatly reduced this problem".
So, why is two-step estimator is better then one-step estimator with robust option estimator?
