Before revision:  Thanks to several bias-corrections proposed by Fernandez-Val and Weidner (2016) , the incidental parameter bias can be reduced substantially. In order to make the estimation feasible even in panels with many fixed effects, we develop an efficient software routine, embedded in the R -package alpaca, that combines these corrections with an approach called method of alternating projections. Further, we contribute to the existing literature by conducting extensive simulation experiments  in large and even unbalanced panel settings.
After revision:  Thanks to several bias-corrections proposed by Fernandez-Val and Weidner (2016) with an estimation algorithm proposed by Stammann (2018). We conduct extensive simulation experiments in large and even unbalanced panel settings.