Using and Interpreting Fixed Effects Models

2024/06/13 by MATTHIAS BREUER, Matthias Breuer, ED DEHAAN +1 · 8 citations
Mathematics · Economics, Econometrics and Finance · #Advanced Causal Inference Techniques #Spatial and Panel Data Analysis #Housing Market and Economics

paper · pdf · doi:10.1111/1475-679x.12559

Abstract

ABSTRACT Fixed effects (FE) have emerged as a ubiquitous and powerful tool for eliminating unwanted variation in observational accounting studies. Unwanted variation is plentiful in accounting research because we often use rich data to test precise hypotheses derived from abstract theories. By eliminating unwanted variation, FE reduce concerns that omitted variables bias our estimates or weaken test power. FE are not costless, though, so their use should be carefully justified by theoretical and institutional considerations. FE also transform samples and variables in ways that are not immediately apparent, and in doing so affect how we should interpret regression results. This primer explains the mechanics of FE and provides practical guidance for the informed use, transparent reporting, and careful interpretation of FE models.

Citations

• Earnings Management During Import Relief Investigations
• On the Usefulness of Earnings and Earnings Research: Lessons and Directions from Two Decades of Empirical Research
• Risk, Return, and Equilibrium: Empirical Tests
• Biases in Dynamic Models with Fixed Effects
• Abandon Statistical Significance
• Moving to a World Beyond “ p < 0.05”
• Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects

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