Data Envelopment Analysis With Missing Data

Chiang Kao () and Shiang-Tai Liu ()
Additional contact information
Chiang Kao: National Cheng Kung University
Shiang-Tai Liu: Vanung University

Chapter Chapter 16 in Modeling Data Irregularities and Structural Complexities in Data Envelopment Analysis, 2007, pp 291-304 from Springer

Abstract: Abstract In data envelopment analysis (DEA), the input and output data from all of the decision making units (DMUs) to be compared are required. If, for any reason, some data are missing, then the associated DMU must be eliminated to make the approach applicable. This study proposes a fuzzy set approach to deal with missing values. The value of a DMU in an input (or output) which is missing is represented by a triangular fuzzy number constructed from the values of other DMUs in that input (or output). A fuzzy DEA model is then used to calculate the efficiencies, which are usually also fuzzy numbers. We use a problem with complete data to investigate the effect of this approach when 1%, 2%, and 5% of the values are missing. While the conventional DMU-deletion method will overestimate the efficiencies of the remaining DMUs, the fuzzy set approach produces results which are very close to those calculated from complete data. The average error in estimating the true efficiency is less than 0.3%. Most importantly, the fuzzy set approach is able to calculate the efficiencies of all DMUs, including those with some values missing.

Keywords: Data envelopment analysis; efficiency; missing data; fuzzy set (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (2)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-0-387-71607-7_16

Ordering information: This item can be ordered from
http://www.springer.com/9780387716077

DOI: 10.1007/978-0-387-71607-7_16

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().