abstract: The Common Correlated Effects (CCE) methodology is now well established for the analysis of factor-augmented panel data models. Yet, it is often neglected that the pooled variant is biased unless the cross-section dimension (N) of the dataset dominates the time series length (T). This is problematic for inference with typical macroeconomic datasets where T is often equal or larger than N. In response, we provide in this paper the theoretical foundation for the cross-section bootstrap in large N and T panels with T/N bounded.