Detailed description of the implementation the multinomial logit model with fixed effects (femlogit)

Abstract

Fixed effect models have become increasingly popular in the field of sociology. The possibility to control for unobserved heterogeneity makes these models a prime tool for causal analysis. As of today, fixed effects models have been derived and implemented for many statistical software packages for continuous, dichotomous and count-data dependent variables. Chamberlain (1980) derived the multinomial logistic regression with fixed effects. However, this model has not been implemented in any statistical software package, yet. Possible applications would be analyses of effects on employment status with special consideration of part-time or irregular employment, and analyses of the effects on voting behavior, that implicitly control for long-time party identification rather than having to measure it directly. This paper introduces an implementation of this model with the new command femlogit. I show its application with British election panel data and multi-level data about the effect of smoking on pre-term, full term, and post-term birth.