Abstract
This paper shows that the Data Envelopment Analysis (or Farrell) method is not nonparametric in the sense that the method implicitly employs linear production functions (frontiers) to measure efficiency. Deriving positive-multiplier linear production frontiers and grouping the DMUs by their corresponding frontiers can simplify the estimation procedures when there are new DMUs included, and can easily determine how many inputs should be reduced or/and how many outputs should be increased to make an inefficient DMU efficiently. This procedure can also circumvent the problems of the non-Archimedean infinitesmal in the CCR literature. It is also shown that, because of the linear production functions, both Banker's and the Banker-Charnes-Cooper methods fail in testing for returns-to-scale.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
