Regression models for proportions are frequently encountered in applied work. The conditional expectation function is bounded between 0 and 1 and therefore must be non-linear, requiring nonstandard panel data extensions. One possible approach is the binomial panel logit model with fixed effects (Machado, 2004). We propose a new and simple implementation of the conditional maximum likelihood estimator for standard software. We investigate the properties of the estimator under misspecification and derive a new test for overdispersion. Estimator and test are applied in a study of contracted working volumes, measured as proportion of full-time work, for women in Switzerland.
proportions data unobserved heterogeneity conditional maximum likelihood overdispersion