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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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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 |
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. |
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