Volume 4 • Issue 3 | November 2020
A closer look at stochastic frontier analysis in economics
Hung T. Nguyen
Abstract:
Purpose – While there exist many surveys on the use stochastic frontier analysis (SFA), many important issues and techniques in SFA were not well elaborated in the previous surveys, namely, regular models, copula modeling, nonparametric estimation by Grenander’s method of sieves, empirical likelihood and causality issues in SFA using regression discontinuity design (RDD) (sharp and fuzzy RDD). The purpose of this paper is to encourage more research in these directions.
Design/methodology/approach – A literature survey.
Findings – While there are many useful applications of SFA to econometrics, there are also many important open problems.
Originality/value – This is the first survey of SFA in econometrics that emphasizes important issues and techniques such as copulas.