Testing over-representation of observations in subsets of a DEA technology

Mette Asmild, Jens Hougaard () and Ole B. Olesen

European Journal of Operational Research, 2013, vol. 230, issue 1, 88-96

Abstract: This paper proposes a test for whether data are over-represented in a given production zone, i.e. a subset of a production possibility set which has been estimated using the non-parametric Data Envelopment Analysis (DEA) approach. A binomial test is used that relates the number of observations inside such a zone to a discrete probability weighted relative volume of that zone. A Monte Carlo simulation illustrates the performance of the proposed test statistic and provides good estimation of both facet probabilities and the assumed common inefficiency distribution in a three dimensional input space. Potential applications include tests for whether benchmark units dominate more (or less) observations than expected.

Keywords: Data Envelopment Analysis (DEA); Over-representation; Data density; Binomial test; Benchmarks (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221713002713
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Testing over-representation of observations in subsets of a DEA technology (2011)
Working Paper: Testing over-representation of observations in subsets of a DEA technology (2010)
Working Paper: Testing over-representation of observations in subsets of a DEA technology (2010)
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:eee:ejores:v:230:y:2013:i:1:p:88-96

DOI: 10.1016/j.ejor.2013.03.038

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().