Publication in refereed journal
香港中文大学研究人员 ( 现职)
| 姚?博士 (经济学系) |
全文
| 数位物件识别号 (DOI) http://dx.doi.org/10.1016/j.jeconom.2007.10.004 |
引用次数
Web of Sciencehttp://aims.cuhk.edu.hk/converis/portal/Publication/9WOS source URL
其它资讯
摘要Traditional estimators for nonparametric frontier models (DEA, FDH) are very sensitive to extreme values/outliers. Recently, Aragon et al. [2005. Nonparametric frontier estimation: a conditional quantile-based approach. Econometric Theory 21, 358-38http://aims.cuhk.edu.hk/converis/portal/Publication/9] proposed a nonparametric alpha-frontier model and estimator based on a suitably defined conditional quantile which is more robust to extreme values/outliers. Their estimator is based on a nonsmooth empirical conditional distribution. In this paper, we propose a new smooth nonparametric conditional quantile estimator for the alpha-frontier model. Our estimator is a kernel based conditional quantile estimator that builds on early work of Azzalini [1http://aims.cuhk.edu.hk/converis/portal/Publication/981. A note on the estimation of a distribution function and quantiles by a kernel method. Biometrika 68, 326-328]. It is computationally simple, resistant to outliers and extreme values, and smooth. In addition, the estimator is shown to be consistent and root n asymptotically normal under mild regularity conditions. We also show that our estimator's variance is smaller than that of the estimator proposed by Aragon et al. A simulation study confirms the asymptotic theory predictions and contrasts our estimator with that of Aragon et al. (C) 2007 Elsevier B.V. All rights reserved.
着者Martins-Filho C, Yao F
期刊名称Journal of Econometrics
出版年份2008
月份4
日期1
卷号143
期次2
出版社Elsevier
页次317 - 333
国际标準期刊号0304-4076
电子国际标準期刊号1872-68http://aims.cuhk.edu.hk/converis/portal/Publication/95
语言英式英语
关键词conditional quantile estimation; nonparametric frontier; production function
Web of Science 学科类别Business & Economics; Economics; ECONOMICS; Mathematical Methods In Social Sciences; Mathematics; Mathematics, Interdisciplinary Applications; MATHEMATICS, INTERDISCIPLINARY APPLICATIONS; Social Sciences, Mathematical Methods; SOCIAL SCIENCES, MATHEMATICAL METHODS
