B1889
Title: Recent development on stochastic frontier models
Authors: Zheng Wei - Texas A&M University (United States) [presenting]
Abstract: The stochastic frontier model is widely used in economics, finance, and management to estimate the production function and efficiency of a firm or industry. The classical frontier model proposed the use of a normal distribution for the noise term and a half-normal distribution for the one-sided inefficiency term. In addition, parametric forms of production functions, such as Cobb-Douglas and translog, are often assumed a priori without validation and may suffer from model misspecification and lead to biased estimates of efficiency. To address these issues, a new set of models is proposed for frontier analysis. Various estimation methods are developed including the Bayesian inference tool and ECM algorithm. The performance of the proposed methods is illustrated through simulation studies and real data applications.
