Authors: | Andor, Mark Parmeter, Christopher Sommer, Stephan |
Title: | Combining uncertainty with uncertainty to get certainty? Efficiency analysis for regulation purposes |
Language (ISO): | en |
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 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. |
Subject Headings: | data envelopment analysis network operators regulation efficiency analysis stochastic frontier analysis |
Subject Headings (RSWK): | Data Envelopment Analysis Frontier-Funktion Effizienzanalyse Regulierung |
URI: | http://hdl.handle.net/2003/37146 http://dx.doi.org/10.17877/DE290R-19142 |
Issue Date: | 2018 |
Appears in Collections: | Sonderforschungsbereich (SFB) 823 |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
DP_2318_SFB823_Andor_Parmeter_Sommer.pdf | DNB | 1.19 MB | Adobe PDF | View/Open |
This item is protected by original copyright |
This item is protected by original copyright rightsstatements.org