UPDF AI

Practical Guidance on Using and Interpreting Fixed Effects Models

E. dehaan

2020 · DOI: 10.2139/ssrn.3699777
Social Science Research Network · 223 Citations

TLDR

This manuscript provides plain-English explanations of how fixed effects can eliminate certain omitted variable biases, affect standard errors, and alter how the authors should think about sample composition and the interpretation of coefficient estimates.

Abstract

Fixed effects are ubiquitous in accounting and finance studies, but many new researchers have only a vague understanding of how they function. This manuscript provides plain-English explanations of how fixed effects can eliminate certain omitted variable biases, affect standard errors, and alter how we should think about sample composition and the interpretation of coefficient estimates. I emphasize that, while fixed effects can be a powerful tool, they can come at the cost of efficiency and can introduce subtle but important econometric problems of their own. Better understanding these issues will help us all make better choices about how to design fixed effects models and carefully interpret the results thereof.