Footnote:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments September 30, 2018 erstellt
Description:
Accounting for time-varying unobserved heterogeneity poses a fundamental challenge for all empirical finance research. This paper discusses the limitations of two widely-used approaches to model unobserved heterogeneity in finance: two-way fixed effect (TFE) and interacted fixed effect models (IFE). We show how TFE and IFE models can provide inconsistent (biased) estimates and can affect statistical inference in many empirical finance settings. To overcome the bias, we propose the use of the "group fixed effect, GFE" class of models, which produce consistent estimates under unobserved group heterogeneity and even under the two-way fixed effect and interacted fixed effect data generating processes. We study the finite sample properties of GFE through simulations and demonstrate its economic importance through an empirical application. We also extend the GFE class of models to accommodate two-stage least squares estimators (central to empirical finance research) and propose a Hausman-type specification test for model evaluation. Finally, we provide researchers with guidance and user-written functions in statistical packages to overcome the limitations of existing approaches