Abstract
Many panel data sets used for Pseudo-Poisson estimation of three-way gravity models are implicitly unbalanced because uninformative observations are redundant for the estimation. We show with real data as well as simulations that this phenomenon, which we call latent unbalancedness, amplifies the inference problem recently studied by Weidner and Zylkin (2021). • Many legitimately balanced trade data sets are implicitly unbalanced. • We explain why this is the case and discuss the consequences for inference. • The severity of the inference problem can be easily assessed by a heuristic. • The bias corrections of Weidner and Zylkin (2021) help to improve inference.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have