Assessing the efficiency of Chilean water and sewerage companies accounting for uncertainty. Issue 61 (July 2016)

• Record Type: Journal Article
• Authors: Molinos-Senante, María; Donoso, Guillermo; Sala-Garrido, Ramon
• Is Part Of: Environmental science & policy. Issue 61(2016:Jul.)
• Page Start: 116
• Page End: 123
• Publication Date: 2016-07
• Subjects: Data envelopment analysis (DEA) -- Efficiency -- Ranking -- Uncertainty -- Water utilities; Environmental policy -- Periodicals; Environmental sciences -- Periodicals; Environnement -- Politique gouvernementale -- Périodiques; Sciences de l'environnement -- Périodiques; Environmental policy; Environmental sciences; Periodicals; Electronic journals; 363.70561
• DOI: 10.1016/j.envsci.2016.04.003
• Languages: English
• ISSNs: 1462-9011

Abstract

Highlights: Assessment of the efficiency of water companies accounting for uncertainty. Ranking of Chilean water companies based on efficiency scores. Quality-adjusted outputs exhibit larger uncertainty than inputs. 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.