Improving the econometric precision of regulatory models |
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Authors: | Subal C. Kumbhakar Alan P. Horncastle |
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Affiliation: | 1.Department of Economics,State University of New York–Binghamton,Binghamton,USA;2.Oxera Consulting Ltd,Oxford,UK |
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Abstract: | Regulatory regimes often attempt to introduce quasi-competitive pressures by undertaking comparative efficiency assessments between the regulated companies and setting company-specific cost reduction targets based on those comparisons. The UK water industry is one example of such a regime—indeed, it has emphasized the importance of maintaining the number of independent companies in order to preserve the robustness of the modeling. For example, in 2007, the Competition Commission considered whether the merger between Mid Kent Water and South East Water might prejudice the ability of the regulator (Ofwat) to make comparisons across water companies for the purposes of assessing performance and setting price controls. In this paper, we examine this issue and provide specific recommendations to regulators. Our cross-sectional results show that the impact of this merger is not significant. We demonstrate that joint estimation of all the sub-models using the ‘seemingly unrelated regression’ (SUR) procedure in a cross-section and/or panel data framework can dramatically improve the accuracy of the modeling. Moreover, the merger does not affect the confidence intervals significantly under such approaches, which still remain far superior to those under Ofwat’s cross-sectional approach. Based on these results, we recommend that Ofwat and other regulators adopt SUR and/or panel data analysis and thereby reduce their reliance on having sufficient numbers of independent companies. |
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