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Testing the binomial fixed effects logit model, with an application to female labour supply

Regression models for proportions are frequently encountered in applied work. The conditional expectation function is bounded between 0 and 1 and therefore must be nonlinear, requiring nonstandard panel data extensions. One possible approach is the binomial panel logit model with fixed effects (Mach...

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Detalles Bibliográficos
Autores principales: Winkelmann, Rainer, Xu, Lin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818013/
https://www.ncbi.nlm.nih.gov/pubmed/35210694
http://dx.doi.org/10.1007/s00181-021-02034-2
Descripción
Sumario:Regression models for proportions are frequently encountered in applied work. The conditional expectation function is bounded between 0 and 1 and therefore must be nonlinear, requiring nonstandard panel data extensions. One possible approach is the binomial panel logit model with fixed effects (Machado in J Econom 119:73–98, 2004). We propose a new and simple implementation of this 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.