A flexible stochastic production frontier model with panel data

被引:0
作者
Wang, Taining [1 ]
Yao, Feng [2 ]
Kumbhakar, Subal C. [3 ,4 ]
机构
[1] Capital Univ Econ & Business, Int Sch Econ & Management, Beijing, Peoples R China
[2] West Virginia Univ, Dept Econ, Morgantown, WV USA
[3] SUNY Binghamton, Dept Econ, Binghamton, NY 13902 USA
[4] Czech Univ Life Sci Prague, Fac Econ & Management, Dept Econ, Prague, Czech Republic
关键词
interaction; one-step backfitting; semiparametric additive model; technical efficiency; NONPARAMETRIC-ESTIMATION; PROFILE LIKELIHOOD; REGRESSION; EXPORTS; CHINA;
D O I
10.1002/jae.3033
中图分类号
F [经济];
学科分类号
02 ;
摘要
We propose a flexible stochastic production frontier model with fixed effects for the panel data in which the semiparametric frontier is additive with bivariate interactions. To avoid potential misspecification and/or "wrong skew problem" due to distributional assumptions, we model the conditional mean of the inefficiency to depend on environmental variables and to be known up to a vector of parameters. We propose a difference-based estimator for parameters characterizing the conditional mean of the inefficiency term, a profile series estimator, and a kernel-based one-step backfitting estimator for the frontier to facilitate inference. We establish their asymptotic properties and show that each component in the frontier estimated by the kernel-based backfitting has the same asymptotic distribution as the one estimated with the true knowledge on the other components in the frontier (i.e., the oracle property). Through a Monte Carlo study, we demonstrate that the proposed estimators perform well in finite samples. Utilizing a panel of Chinese firm-level data in 2000-2006, we apply our method to estimate the frontier and efficiency scores and conclude that export plays a significant role in reducing the efficiency of firms.
引用
收藏
页码:564 / 588
页数:25
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