Bias-corrected estimators for monotone and concave frontier functions |
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| Affiliation: | 1. Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan;2. Department of Mathematical and Computing Science, Tokyo Institute of Technology, Tokyo, Japan;3. Department of Mental Health and Psychiatric Nursing, School of Nursing, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan;4. Graduate School of Public Health, St. Luke''s International University, Tokyo, Japan;5. Institute for Business and Finance, Waseda University, Tokyo, Japan;6. Department of Sustainable Health Science, Center for Preventive Medical Sciences, Chiba University, Chiba, Japan;7. Department of Global Health Policy, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan |
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| Abstract: | For the estimation of a monotone and concave support-boundary the data envelopment analysis (DEA) estimator is popular. Recently, under the assumption that the density at boundary is bounded away from zero, Gijbels et al. (J. Amer. Statist. Assoc. 94 (445) 220) derives the limit distribution of the DEA estimator and gives a bias-corrected estimator.In this paper, we generalize the results in Gijbels et al. (1999) by allowing the density at boundary to be infinite, bounded away from zero or zero. |
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