Sensitivity and Stability of the Classifications of Returns to Scale in Data Envelopment Analysis

Lawrence Seiford and Joe Zhu

Journal of Productivity Analysis, 1999, vol. 12, issue 1, 55-75

Abstract: Sensitivity of the returns to scale (RTS) classifications in data envelopment analysis is studied by means of linear programming problems. The stability region for an observation preserving its current RTS classification (constant, increasing or decreasing returns to scale) can be easily investigated by the optimal values to a set of particular DEA-type formulations. Necessary and sufficient conditions are determined for preserving the RTS classifications when input or output data perturbations are non-proportional. It is shown that the sensitivity analysis method under proportional data perturbations can also be used to estimate the RTS classifications and discover the identical RTS regions yielded by the input-based and the output-based DEA methods. Thus, our approach provides information on both the RTS classifications and the stability of the classifications. This sensitivity analysis method can easily be applied via existing DEA codes. Copyright Kluwer Academic Publishers 1999

Keywords: Data envelopment analysis (DEA); returns to scale (RTS); sensitivity; stability (search for similar items in EconPapers)
Date: 1999
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (15)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1007803207538 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:jproda:v:12:y:1999:i:1:p:55-75

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11123/PS2

DOI: 10.1023/A:1007803207538

Access Statistics for this article

Journal of Productivity Analysis is currently edited by William Greene, Chris O'Donnell and Victor Podinovski

More articles in Journal of Productivity Analysis from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().