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Regulatory Reform in Ontario
Successes, shortcomings and unfinished business.
while the working group didn’t accept the menu approach, it did agree there should be a degree of flexibility in how PBR is implemented in Ontario. Flexibility is important due to the large number of distributors in the province. These companies vary in a number of ways, including differences in their cost efficiencies, economic activities and customer growth, and expected capital-replacement expenditures. In order to accommodate these diverse circumstances, the OEB-approved PBR framework has several modules added to a core PBR plan. These modules are optional regulatory mechanisms that companies may access according to pre-established rules. In contrast, the core plan is designed to be a stable and rigorous PBR mechanism that applies to all distributors, although this plan is tailored to certain individual company conditions.
The core PBR plan has the following key features:
• A term of four years (one “rebasing” year and three years of index-based rate adjustments);
• No earnings-sharing mechanism;
• An inflation minus X rate-adjustment formula, where inflation is measured by the growth in an economy-wide inflation index;
• An X factor with two components: 1) a productivity factor based on industry TFP trends, which is common for all distributors in Ontario; and 2) a differentiated productivity stretch factor, where companies are assigned one of three possible stretch factor values based on benchmarking evaluations of their operations and maintenance (O&M) cost efficiency;
• The approved value for the industry TFP trend and productivity factor is 0.72 percent; and
• The stretch factors are determined through benchmarking studies; the initial studies undertaken by Pacific Economics Group identified three efficiency cohorts, determined based on two benchmarking models developed by PEG: a unit cost model that directly compared each distributor’s unit cost performance with the unit costs of a selected peer group; and an econometric cost model, which generated cost predictions for each company based on a variety of business conditions beyond its control. Each company’s actual costs then were compared to its predicted costs, and statistical tests were performed to determine whether the difference between actual and predicted costs was statistically significant. If a company’s actual costs were less than the predicted value and the difference was statistically significant, the company was identified as a significantly superior performer. If a company’s actual costs were greater than the predicted value and the difference was statistically significant, the company was identified as a significantly inferior performer. If the difference between actual and predicted costs was not statistically significant, then the company was an average cost performer. Both benchmarking models applied to companies’ operation, maintenance and administration expenses since it was not possible to obtain reliable capital cost measures for all companies in the sample in the available time.
The first cohort was populated by all distributors that were in the top third on the unit cost benchmarking study, and were statistically superior cost performers on the econometric benchmarking model. The third cohort was given by all distributors in the bottom third on the unit cost benchmarking study that were statistically inferior cost performers on the econometric benchmarking model. All other