Measuring Environmental Efficiency: An Application to U.S. Electric Utilities

Chien-Ming Chen () and Sheng Ang ()
Additional contact information
Chien-Ming Chen: Nanyang Technological University
Sheng Ang: University of Science and Technology of China

Chapter Chapter 11 in Data Envelopment Analysis, 2016, pp 345-366 from Springer

Abstract: Abstract This chapter highlights limitations of some DEA (data envelopment analysis) environmental efficiency models, including directional distance function and radial efficiency models, under weak disposability assumption and various return-to-scale technology. It is found that (1) these models are not monotonic in undesirable outputs (i.e., a firm’s efficiency score may increase when polluting more, and vice versa), (2) strongly dominated firms may appear efficient, and (3) some firms’ projection points derived from the optimal environmental efficiency scores are strongly dominated, thus they cannot be the right direction for the improvement. To address these problems, we propose a weighted additive model, i.e., the Median Adjusted Measure (MAM) model. An application to measuring the environmental efficiency of 94 U.S. electric utilities is presented to illustrate the problems and to compare the existing models with our MAM model. The empirical results show that the directional distance function and radial efficiency models may generate spurious efficiency estimates, and thus it must be with caution.

Keywords: Data envelopment analysis; Environmental efficiency; Undesirable outputs; Various return-to-scale; Electric utilities (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (1)

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:isochp:978-1-4899-7684-0_11

Ordering information: This item can be ordered from
http://www.springer.com/9781489976840

DOI: 10.1007/978-1-4899-7684-0_11

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().