Ruhr Economic Papers

Ruhr Economic Papers #770

Combining Uncertainty with Uncertainty to Get Certainty? Efficiency Analysis for Regulation Purposes

by Mark A. Andor, Christopher Parmeter and Stephan Sommer

RWI, 09/2018, 92 S./p., 12 Euro, ISBN 978-3-86788-898-1 DOI: 10.4419/86788898



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 an 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.

JEL-Classification: C10, C50, D24, L50

Keywords: Data envelopment analysis; stochastic frontier analysis; efficiency analysis; regulation; network operators