Replication data for: Bias in Conditional and Unconditional Fixed Effects Logit Estimation

There are two main estimators for such models: unconditional maximum likelihood and conditional maximum likelihood. Judged on asymptotic properties, the conditional estimator is superior.

However, the unconditional estimator holds several practical advantages, and therefore I sought to determine whether its use could be justified on the basis of finite-sample properties. In a series of Monte Carlo experiments for T is greater than 20, I found a negligible amount of bias in both estimators when T is greater than and equal to 16, suggesting that a researcher can safely use either estimator under such conditions.