femlogit—Implementation of the multinomial logit model with fixed effects
Klaus Pforr
GESIS–Leibniz–Institute for the Social Sciences
Mannheim, Germany
[email protected]
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Abstract. Fixed-effects models have become increasingly popular in social-science
research. The possibility to control for unobserved heterogeneity makes these
models a prime tool for causal analysis. Fixed-effects models have been derived and
implemented for many statistical software packages for continuous, dichotomous,
and count-data dependent variables. Chamberlain (1980, Review of Economic
Studies 47: 225–238) derived the multinomial logistic regression with fixed effects.
However, this model has not yet been implemented in any statistical software
package. Possible applications would be analyses of effects on employment status,
with special consideration of part-time or irregular employment, and analyses of
effects on voting behavior that implicitly control for long-time party identification
rather than measuring it directly. This article introduces an implementation of
this model with the new command femlogit. I show its application with British
election panel data.
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Klaus Pforr
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femlogit, multinomial logit, fixed effects, panel data, multilevel data, unobserved heterogeneity, discrete choice, random effects, conditional logit
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