"We view the [Entergy-ITC] transaction [as] an attempt to extract excess value."-Mississippi PSC
a greater degree than down-side costs, the IR scheme will be asymmetric, and the probability distribution of earnings will be skewed downward. Figure 3 compares two distributions of realized ROE directly. As drawn, the expected ROE under COS regulation, ECOS, is less than the expected ROE under incentive regulation, E IR. The actual volatility of ROE under incentive regulation, however, is greater than the volatility under COS regulation, as measured by the overall "spread" of the probability distributions. This risk-return relationship can hold the key to setting a baseline ROE under an incentive regulation scheme.
Measuring Risk vs. Reward
When a baseline ROE is set by regulators, whether under COS or incentive regulation, little attention may be paid to the likely volatility of the realized ROE that will result. Instead, weighing the usual empirical and anecdotal evidence presented by cost-of-capital witnesses like myself, the utility regulator determines an allowed ROE that supposedly provides investors with an expected return that is similar to other firms having the same overall risk.
To truly determine where a utility's baseline ROE should be set under incentive regulation, however, it is critical to evaluate earnings volatility relative to traditional COS regulation. This requires several steps. First, earnings volatility is evaluated under COS regulation. This fairly straightforward exercise can be accomplished by constructing a utility income model that first identifies the factors having the largest impacts on earnings (, fuel prices, weather, etc.) and then randomizes those factors to create an overall probability distribution of earnings and ROE 6. The utility should determine annual earnings variability over the proposed lifetime of the IR scheme, and also examine the overall probability distribution of the present value of those earnings, based on the utility's current discount rate.
Next, the same exercise can be performed for the proposed incentive regulation scheme. Although measuring ROE volatility associated with the incentive regulation will be less straightforward, as it will depend on the structure of that incentive regulation scheme, an income model tied to the incentive structure can be constructed. For example, suppose the proposed incentive regulation scheme is a price cap with earnings sharing. The utility's ROE will depend on random factors, but also its effectiveness in reducing costs and the specific sharing percentages between customers and shareholders. A given price plus sharing proposal will result in a probability distribution of realized ROE, just as under COS regulation.
The next step is to compare the two probability distributions in order to assess the risk-return tradeoffs for each regulatory scheme, as well as determine whether the incentive scheme is symmetric. Suppose, for example, that the proposed incentive regulation leads to the situation in Figure 3 (see p. 21), in which both expected ROE and the volatility of ROE is higher than it would be under COS regulation. While such a result would be consistent with the mean-variance tradeoffs familiar to stock analysis, it doesn't reveal whether the tradeoff is reasonable. For that, a more sophisticated but very doable analysis is required. This analysis evaluates the relative positions of the cumulative distribution function