Semiparametric stochastic frontier models for clustered data. (English) Zbl 1247.62114
Summary: The mixed model approach to semiparametric regression is considered for stochastic frontier models, with focus on clustered data. Standard assumptions about the model component representing the inefficiency effect lead to a closed skew normal distribution for the response. Model parameters are estimated by a generalization of restricted maximum likelihood, and random effects are estimated by an orthodox best linear unbiased prediction procedure. The method is assessed by means of Monte Carlo studies, and illustrated by an empirical application on hospital productivity.
MSC:
| 62G08 | Nonparametric regression and quantile regression |
| 62G05 | Nonparametric estimation |
| 65C05 | Monte Carlo methods |
| 62H30 | Classification and discrimination; cluster analysis (statistical aspects) |
Keywords:
efficiency evaluation; flexible frontier; random effect; semiparametric regression; skew normalityReferences:
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