Robustness, outliers and Mavericks in network regulation
AbstractBenchmarking methods, primarily non-parametric techniques such as Data Envelopment Analysis, have become well-established and informative tools for economic regulation, in particular in energy infrastructure regulation. The axiomatic features of the non-parametric methods correspond closely to the procedural and economic criteria for good practice network regulation. However, critique has been voiced against the robustness of best-practice regulation in presence of uncertainty regarding model specification, data definition and collection. This paper investigates the foundation of the critique both conceptually and by describing the actual state-of-the-art used in energy network regulation using frontier analysis models in Sweden (2000-2003) and in Germany (2007-). A principal component of the applied frontier regulation is the systematic use of outlier detection models to define homogeneous reference sets and to exclude maverick reports. We review two families of outlier detection methods in terms of their function and application using a data set from Swedish electricity distribution, illustrating the different types of outliers. Finally, the paper concludes on the role of outlier detection as a mean to implement regulation with higher robustness.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2013007.
Date of creation: 26 Apr 2013
Date of revision:
Contact details of provider:
Postal: Voie du Roman Pays 34, 1348 Louvain-la-Neuve (Belgium)
Fax: +32 10474304
Web page: http://www.uclouvain.be/core
More information through EDIRC
regulation; energy networks; outlier detection;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-04 (All new papers)
- NEP-EFF-2013-06-04 (Efficiency & Productivity)
- NEP-ENE-2013-06-04 (Energy Economics)
- NEP-REG-2013-06-04 (Regulation)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Alain GILLIS).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.