A Zero Inefficiency Stochastic Frontier Estimator
针对传统随机前沿模型假设所有企业都无效率的缺陷，提出零无效率随机前沿模型，允许样本中同时存在完全有效和无效率的企业，并给出估计和检验方法。
Traditional stochastic frontier models impose inefficient behavior on all firms in the sample of interest. If the data under investigation represent a mixture of both fully efficient and inefficient firms then off-the-shelf frontier models are statistically inadequate. We introduce the zero inefficiency stochastic frontier model which can accommodate the presence of both efficient and inefficient firms in the sample. We derive the corresponding log-likelihood function, conditional mean of inefficiency to estimate observation-specific inefficiency and discuss testing for the presence of fully efficient firms. We provide both simulated evidence as well as an empirical example which demonstrates the applicability of the proposed method. JEL Classification No.: C13, C23, C33