Fixed-Effects in Empirical Accounting Research

The fixed-effects specification is often used in panel datasets as a way of dealing with correlated omitted variables. A review of recent accounting publications reveals that while researchers are generally aware of the need to include fixed-effects in empirical models when using panel datasets (firm-time observations), many chose to replace firm fixed-effects with other form of fixed-effects, mainly industry fixed-effects. We examine the consequences of using different model specifications and show analytically and using simulations that replacing firm fixed or omitting them can lead to biased estimates and wrong inferences. To illustrate the importance of properly including firm fixed-effects, we reexamine commonly used regression models in the accounting literature. We show how inferences change when fixed-effects are properly included. Importantly, we identify circumstances where the fixed-effects specification is likely to fail and offer a full differencing model as an alternative specification