Before revision:  Using the example of binary choice models with individual and time fixed effects, we show how both issues can be alleviated by combining the asymptotic bias corrections of Fern\'andez-Val and Weidner (2016) with an estimation algorithm proposed by Stammann (2018). We conduct extensive simulation experiments to analyze the statistical properties of various ( bias-corrected) estimatorsin large and even unbalanced panels.
After revision:  Using the example of binary choice models with individual and time fixed effects, we show how both issues can be alleviated by combining the asymptotic bias corrections with computational advances. Because unbalancedness is often encountered in applied work, we investigate its consequences on the finite sample properties of various ( bias-corrected) estimatorsin large and even unbalanced panels.