Assessing the efficiency of Chilean water and sewerage companies accounting for uncertainty

María Molinos-Senante, Guillermo Donoso and Ramon Sala-Garrido

Environmental Science & Policy, 2016, vol. 61, issue C, 116-123

Abstract: Efficiency assessment of water and sewerage companies (WaSCs) has attracted considerable attention both for water company managers and water regulators. Within the methodological approaches that can be applied to estimate efficiency scores, data envelopment analysis (DEA) is the most widely applied technique. In spite of the positive features of DEA, it presents a major drawback which is its deterministic nature. In other words, conventional DEA models do not account for uncertainty in the data. To overcome this limitation, we assess, for the first time, the efficiency of a sample of Chilean WaSCs by using a DEA model with statistical tolerance in the data. Hence, 81 efficiency scores are estimated for each WaSC rather than a single score as with conventional DEA models. The results illustrate that outputs exhibit larger uncertainty than inputs. Moreover, WaSCs efficiency scores change significantly under the best-case and worst-case scenarios. The ranking of the WaSCs allows for the identification of which of them has the highest performance based on their efficiency scores. This information is essential to enhance efficiency and innovation in the water industry. Moreover, the introduction of uncertainty in the efficiency assessment allows for the prediction and ranking of future performance of WaSCs.

Keywords: Data envelopment analysis (DEA); Efficiency; Ranking; Uncertainty; Water utilities (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1462901116300831
Full text for ScienceDirect subscribers only

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:eee:enscpo:v:61:y:2016:i:c:p:116-123

DOI: 10.1016/j.envsci.2016.04.003

Access Statistics for this article

Environmental Science & Policy is currently edited by M. Beniston

More articles in Environmental Science & Policy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().