Efficiency evaluation under uncertainty: a stochastic DEA approach

P. Beraldi () and M. E. Bruni ()
Additional contact information
P. Beraldi: University of Calabria
M. E. Bruni: University of Calabria

Decisions in Economics and Finance, 2020, vol. 43, issue 2, No 6, 519-538

Abstract: Abstract In conventional data envelopment analysis (DEA) models, the efficiency measurement is carried out by using deterministic data typically referring to past observations. However, in many operative contexts, decision makers are called to predict the future performance for planning and control purposes. In these situations, ignoring the stochastic nature of data might lead to misleading results. The paper proposes a stochastic DEA approach based on the chance constrained paradigm and accounts for risk measured in terms of tail $$\gamma $$ γ -mean. A deterministic equivalent reformulation is presented under the assumption of discrete distributions. The computational experiments are carried out on an empirical case study related to the evaluation of the credit risk. The results demonstrate the validity of the proposed approach as proactive evaluation technique.

Keywords: Data envelopment analysis; Probabilistic constraints; Firm efficiency evaluation; Tail measures (search for similar items in EconPapers)
JEL-codes: C6 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10203-020-00295-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:decfin:v:43:y:2020:i:2:d:10.1007_s10203-020-00295-7

Ordering information: This journal article can be ordered from
http://www.springer. ... ry/journal/10203/PS2

DOI: 10.1007/s10203-020-00295-7

Access Statistics for this article

Decisions in Economics and Finance is currently edited by Paolo Ghirardato

More articles in Decisions in Economics and Finance from Springer, Associazione per la Matematica
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().