Structural and behavioral robustness in applied best-practice regulation
Benchmarking 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. Incorrect data may result from structural sources, such as heterogeneous technologies; deterministic approaches applied to stochastic data generation processes or poorly defined scope of activity. Specifically within regulation, reporting may also be biased through individual gaming or collusive behavior, including the intentional provision of absurd data in order to stall or perturb regulatory process (here called maverick reporting). We review three 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, contrasting with the actual analysis ex post. 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-). Finally, the paper concludes on the role of outlier detection as a mean to implement regulation with higher robustness.
If 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.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
- Léopold Simar, 2003. "Detecting Outliers in Frontier Models: A Simple Approach," Journal of Productivity Analysis, Springer, vol. 20(3), pages 391-424, November.
- Cazals, Catherine & Florens, Jean-Pierre & Simar, Leopold, 2002. "Nonparametric frontier estimation: a robust approach," Journal of Econometrics, Elsevier, vol. 106(1), pages 1-25, January.
- Emmanuel Thanssoulis, 1999. "Setting Achievement Targets for School Children," Education Economics, Taylor & Francis Journals, vol. 7(2), pages 101-119.
- Burns, Phil & Jenkins, Cloda & Riechmann, Christoph, 2005. "The role of benchmarking for yardstick competition," Utilities Policy, Elsevier, vol. 13(4), pages 302-309, December.
- Norton, Ronald N. & Sexton, Thomas R. & Silkman, Richard H., 2002. "Firm-Specific Productive Efficiency Offsets in the Development of a Price Cap Formula," The Electricity Journal, Elsevier, vol. 15(10), pages 43-52, December.
- John Watson, 2011. "The value of Morningstar ratings: evidence using stochastic data envelopment analysis," Managerial Finance, Emerald Group Publishing, vol. 37(2), pages 94-116, March.
- Haney, Aoife Brophy & Pollitt, Michael G., 2009.
"Efficiency analysis of energy networks: An international survey of regulators,"
Elsevier, vol. 37(12), pages 5814-5830, December.
- Brophy Haney, A. & Pollitt, M.G., 2009. "Efficiency Analysis of Energy Networks : An International Survey of Regulators," Cambridge Working Papers in Economics 0926, Faculty of Economics, University of Cambridge.
- Tangeras, Thomas P., 2002.
"Collusion-proof yardstick competition,"
Journal of Public Economics,
Elsevier, vol. 83(2), pages 231-254, February.
- Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-44, June.
- Peter Bogetoft, 2000. "DEA and Activity Planning under Asymmetric Information," Journal of Productivity Analysis, Springer, vol. 13(1), pages 7-48, January.
- Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
- Kuosmanen, Timo, 2012. "Stochastic semi-nonparametric frontier estimation of electricity distribution networks: Application of the StoNED method in the Finnish regulatory model," Energy Economics, Elsevier, vol. 34(6), pages 2189-2199.
- Pastor, Jesus T. & Ruiz, Jose L. & Sirvent, Inmaculada, 1999. "A statistical test for detecting influential observations in DEA," European Journal of Operational Research, Elsevier, vol. 115(3), pages 542-554, June.
- Per Agrell & Jørgen Tind, 2001. "A Dual Approach to Nonconvex Frontier Models," Journal of Productivity Analysis, Springer, vol. 16(2), pages 129-147, September.
- Lawrence M. Seiford & Joe Zhu, 1999. "Profitability and Marketability of the Top 55 U.S. Commercial Banks," Management Science, INFORMS, vol. 45(9), pages 1270-1288, September.
- Dusansky, Richard & Wilson, Paul W., 1995. "On the relative efficiency of alternative modes of producing a public sector output: The case of the developmentally disabled," European Journal of Operational Research, Elsevier, vol. 80(3), pages 608-618, February.
- Wisnowski, James W. & Montgomery, Douglas C. & Simpson, James R., 2001. "A Comparative analysis of multiple outlier detection procedures in the linear regression model," Computational Statistics & Data Analysis, Elsevier, vol. 36(3), pages 351-382, May.
- Timo Kuosmanen & Mika Kortelainen, 2012. "Stochastic non-smooth envelopment of data: semi-parametric frontier estimation subject to shape constraints," Journal of Productivity Analysis, Springer, vol. 38(1), pages 11-28, August.
- AGRELL, Per J. & BOGETOFT, Peter & TIND, Jorgen, .
"DEA and dynamic yardstick competition in Scandinavian electricity distribution,"
CORE Discussion Papers RP
1837, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- PER AGRELL & Peter Bogetoft & Jørgen Tind, 2005. "DEA and Dynamic Yardstick Competition in Scandinavian Electricity Distribution," Journal of Productivity Analysis, Springer, vol. 23(2), pages 173-201, 05.
- Banker, Rajiv D. & Chang, Hsihui, 2006. "The super-efficiency procedure for outlier identification, not for ranking efficient units," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1311-1320, December.
- R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
- Joseph Paradi & Mette Asmild & Paul Simak, 2004. "Using DEA and Worst Practice DEA in Credit Risk Evaluation," Journal of Productivity Analysis, Springer, vol. 21(2), pages 153-165, March.
- Wilson, Paul W, 1993. "Detecting Outliers in Deterministic Nonparametric Frontier Models with Multiple Outputs," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(3), pages 319-323, July.
- AGRELL, Per & HATAMI-MARBINI, Adel, 2011. "Frontier-based performance analysis models for supply chain management; state of the art and research directions," CORE Discussion Papers 2011069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Shuttleworth, Graham, 2005. "Benchmarking of electricity networks: Practical problems with its use for regulation," Utilities Policy, Elsevier, vol. 13(4), pages 310-317, December.
- Andrei Shleifer, 1985. "A Theory of Yardstick Competition," RAND Journal of Economics, The RAND Corporation, vol. 16(3), pages 319-327, Autumn.
- Kumbhakar,Subal C. & Lovell,C. A. Knox, 2003. "Stochastic Frontier Analysis," Cambridge Books, Cambridge University Press, number 9780521666633, October.
- Rossi, Martin Antonio & Ruzzier, Christian Alejandro, 2000. "On the regulatory application of efficiency measures," Utilities Policy, Elsevier, vol. 9(2), pages 81-92, June.
- Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
- Lowry, Mark Newton & Getachew, Lullit, 2009. "Statistical benchmarking in utility regulation: Role, standards and methods," Energy Policy, Elsevier, vol. 37(4), pages 1323-1330, April.
- Simar, Leopold & Wilson, Paul W., 2002. "Non-parametric tests of returns to scale," European Journal of Operational Research, Elsevier, vol. 139(1), pages 115-132, May.
- Jamasb, T. & Pollitt, M., 2000. "Benchmarking and regulation: international electricity experience," Utilities Policy, Elsevier, vol. 9(3), pages 107-130, September.
- Fare, Rolf & Grosskopf, Shawna, 2000. "Network DEA," Socio-Economic Planning Sciences, Elsevier, vol. 34(1), pages 35-49, March.
- Bogetoft, Peter, 1995. "Incentives and productivity measurements," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 67-77, April.
- Shuttleworth, Graham, 2003. "Firm-Specific Productive Efficiency: A Response," The Electricity Journal, Elsevier, vol. 16(3), pages 42-50, April.
- John Vickers & George Yarrow, 1991. "Economic Perspectives on Privatization," Journal of Economic Perspectives, American Economic Association, vol. 5(2), pages 111-132, Spring.
- Wilson, Paul W., 2008. "FEAR: A software package for frontier efficiency analysis with R," Socio-Economic Planning Sciences, Elsevier, vol. 42(4), pages 247-254, December.
- Peter Bogetoft, 1994. "Incentive Efficient Production Frontiers: An Agency Perspective on DEA," Management Science, INFORMS, vol. 40(8), pages 959-968, August.
When requesting a correction, please mention this item's handle: RePEc:eee:soceps:v:48:y:2014:i:1:p:89-103. See general 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: (Shamier, Wendy)
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.