关键词: 随机前沿模型, 内生性, Copula函数, 极大模拟似然估计, 数值积分

Abstract: Endogeneity is a common econometric problem. Ignoring Endogeneity will result in biased and inconsistent estimators. Some researches study the estimation methods for endogeneous stochastic frontier models, and these methods all need to find the instrumental variables for endogeneous independent variables. However the proper instrumental variables are usually hard to get. This paper aims at the situation when it’s hard to find the proper instrumental variables. Copula method and maximum simulated likelihood method are used to get the estimation of endogeneous stochastic frontier models and construct the new point estimation for technical inefficiencies. The new point estimation absorbs the information of endogeneous variables and is more efficient than the point estimation of JLMS. The numerical simulations show that the method in this paper gets higher accuracies compared with the existing methods.

Key words: Stochastic Frontier Model, Endogeneity, Copula Function, Maximum Simulated Likelihood Estimation, Numerical Integration