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Incorporating quality in economic regulatory benchmarking

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  • Heesche, Emil
  • Asmild, Mette

Abstract

The Danish water regulator uses, amongst other things, Data Envelopment Analysis to create a pseudo-competitive environment for the water companies. The benchmarking results are used to set an individual revenue cap for each company. The benchmarking model is currently criticised for not including the companies’ supply quality and thereby having an omitted variable bias problem. One problem the regulator has encountered when trying to incorporate supply quality in the benchmarking model is that it tends to increase the revenue caps more than desired. The regulator does, however, not have any prior information about the marginal rates of substitution between the quality variables and costs, which makes it challenging to reduce the supply quality's impact on the revenue caps.

Suggested Citation

  • Heesche, Emil & Asmild, Mette, 2022. "Incorporating quality in economic regulatory benchmarking," Omega, Elsevier, vol. 110(C).
    • Handle: RePEc:eee:jomega:v:110:y:2022:i:c:s0305048322000391
    DOI: 10.1016/j.omega.2022.102630
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    as
    1. Timo Kuosmanen, 2005. "Weak Disposability in Nonparametric Production Analysis with Undesirable Outputs," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1077-1082.
    2. 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, May.
    3. V V Podinovski, 2004. "Production trade-offs and weight restrictions in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(12), pages 1311-1322, December.
    4. Yang, Hongliang & Pollitt, Michael, 2009. "Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1095-1105, September.
    5. Rita Martins & Fernando Coelho & Adelino Fortunato, 2012. "Water losses and hydrographical regions influence on the cost structure of the Portuguese water industry," Journal of Productivity Analysis, Springer, vol. 38(1), pages 81-94, August.
    6. Ole B. Olesen & Niels Chr. Petersen, 2015. "Facet Analysis in Data Envelopment Analysis," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 6, pages 145-190, Springer.
    7. O. B. Olesen & N. C. Petersen, 1996. "Indicators of Ill-Conditioned Data Sets and Model Misspecification in Data Envelopment Analysis: An Extended Facet Approach," Management Science, INFORMS, vol. 42(2), pages 205-219, February.
    8. S P Santos & C A F Amado & J R Rosado, 2011. "Formative evaluation of electricity distribution utilities using data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(7), pages 1298-1319, July.
    9. Ramanathan, Ramakrishnan & Ramanathan, Usha & Bentley, Yongmei, 2018. "The debate on flexibility of environmental regulations, innovation capabilities and financial performance – A novel use of DEA," Omega, Elsevier, vol. 75(C), pages 131-138.
    10. Sahoo, Biresh K. & Luptacik, Mikulas & Mahlberg, Bernhard, 2011. "Alternative measures of environmental technology structure in DEA: An application," European Journal of Operational Research, Elsevier, vol. 215(3), pages 750-762, December.
    11. Atakelty Hailu & Terrence S. Veeman, 2001. "Non-parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(3), pages 605-616.
    12. María Molinos-Senante & Manuel Mocholi-Arce & Ramón Sala-Garrido, 2016. "Efficiency Assessment of Water and Sewerage Companies: a Disaggregated Approach Accounting for Service Quality," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4311-4328, September.
    13. 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.
    14. Emil Heesche & Mette Asmild, 2020. "Controlling for environmental conditions in regulatory benchmarking," IFRO Working Paper 2020/03, University of Copenhagen, Department of Food and Resource Economics.
    15. Seiford, Lawrence M. & Zhu, Joe, 2002. "Modeling undesirable factors in efficiency evaluation," European Journal of Operational Research, Elsevier, vol. 142(1), pages 16-20, October.
    16. Podinovski, Victor V. & Kuosmanen, Timo, 2011. "Modelling weak disposability in data envelopment analysis under relaxed convexity assumptions," European Journal of Operational Research, Elsevier, vol. 211(3), pages 577-585, June.
    17. Asmild, Mette & Paradi, Joseph C. & Reese, David N., 2006. "Theoretical perspectives of trade-off analysis using DEA," Omega, Elsevier, vol. 34(4), pages 337-343, August.
    18. Hubert, M. & Vandervieren, E., 2008. "An adjusted boxplot for skewed distributions," Computational Statistics & Data Analysis, Elsevier, vol. 52(12), pages 5186-5201, August.
    19. Serge Garcia & Alban Thomas, 2001. "The Structure of Municipal Water Supply Costs: Application to a Panel of French Local Communities," Journal of Productivity Analysis, Springer, vol. 16(1), pages 5-29, July.
    20. Fare, R. & Grosskopf, S. & Pasurka, C., 1986. "Effects on relative efficiency in electric power generation due to environmental controls," Resources and Energy, Elsevier, vol. 8(2), pages 167-184, June.
    21. Ole Olesen & N. Petersen, 2003. "Identification and Use of Efficient Faces and Facets in DEA," Journal of Productivity Analysis, Springer, vol. 20(3), pages 323-360, November.
    22. Peter Bogetoft & Lars Otto, 2011. "Benchmarking with DEA, SFA, and R," International Series in Operations Research and Management Science, Springer, number 978-1-4419-7961-2, April.
    23. 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 435-444, June.
    24. 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.
    25. Zhou, P. & Ang, B.W. & Poh, K.L., 2008. "Measuring environmental performance under different environmental DEA technologies," Energy Economics, Elsevier, vol. 30(1), pages 1-14, January.
    26. Podinovski, Victor V., 2019. "Direct estimation of marginal characteristics of nonparametric production frontiers in the presence of undesirable outputs," European Journal of Operational Research, Elsevier, vol. 279(1), pages 258-276.
    27. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    28. Scheel, Holger, 2001. "Undesirable outputs in efficiency valuations," European Journal of Operational Research, Elsevier, vol. 132(2), pages 400-410, July.
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    4. Heesche, Emil & Asmild, Mette, 2022. "Controlling for environmental conditions in regulatory benchmarking," Utilities Policy, Elsevier, vol. 77(C).

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