Abstract
In this paper, we address the problem of assessing the influence of a given unit in the sample when evaluating efficiency by using both radial and nonradial DEA models. According to the values of some new measures we define, the efficient units exhibiting a higher deal of influence will be classified for a further checking. Then the analyst will have to decide whether they are contaminated by data errors or not. The interest of these techniques lies in that they provide rules to detect influential observations which may avoid data checking, which is often costly (particularly with large samples).
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.
