Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes

Mark A. Andor, Christopher Parmeter, Stephan Sommer

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Data envelopment analysis (DEA) and stochastic frontier analysis (SFA), as well as combinations thereof, are widely applied in incentive regulation practice, where the assessment of efficiency plays a major role in regulation design and benchmarking. Using a Monte Carlo simulation experiment, this paper compares the performance of six alternative methods commonly applied by regulators. Our results demonstrate that combination approaches, such as taking the maximum or the mean over DEA and SFA efficiency scores, have certain practical merits and might offer a useful alternative to strict reliance on a singular method. In particular, the results highlight that taking the maximum not only minimizes the risk of underestimation, but can also improve the precision of efficiency estimation. Based on our results, we give recommendations for the estimation of individual efficiencies for regulation purposes and beyond.

Original languageEnglish (US)
Pages (from-to)240-252
Number of pages13
JournalEuropean Journal of Operational Research
Volume274
Issue number1
DOIs
StatePublished - Apr 1 2019
Externally publishedYes

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Keywords

  • Data envelopment analysis
  • Efficiency analysis
  • Network operators
  • Regulation
  • Stochastic frontier analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management

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