Should the power industry adapt its approach to capital markets in this environment? The answer, of course, is yes. Multiple frameworks are necessary to establish a power company’s or project’s...
increased only slightly (em from 45 percent of variance to 48 percent. Overall (combining the results for ROE and stranded-cost estimates), the Moody's estimates, the S&P "reasonable" case, and the S&P "severe" case estimates have each improved in their capability to explain variance in M/B ratios (em from 51 to 58 percent, 55 to 66 percent, and 55 to 67 percent, respectively.
(Compare these findings with the earlier study published last May, %n4%n in which we found that the three stranded-cost estimates were statistically significant and could explain roughly 20 percent of M/B variance.)
The differing methods for calculating stranded costs provide some insight into investor preferences. For example, the variance explained by S&P's estimates is almost double that of the Moody's estimates. Because the S&P calculations focus on potential revenue loss, as opposed to above-market investment in generation, the S&P correlation may indicate that investors are gravitating more toward cash flow in a competitive environment rather than any particular recovery of investment in plant prescribed by regulators.
Competitive Indicators: Some Useful, Some Not
Though helpful in understanding investor preferences and stock performance, the stranded-cost estimates calculated by Moody's and S&P are not readily updated or easily calculated. This drawback prompted us to look for standardized categories of data that might prove more easily available for testing as electric utility equity value drivers.
In addition to ROE, we tested five other financial variables, fourteen competitive or operational factors, and two variables that reflect regulatory policy.
Financial Variables: %n5%n
1) dividend payout ratio,
2) common equity ratio,
3) pre-tax interest coverage,
4) fixed-charge coverage, and
5) cash-flow dividend coverage.
Competitive/operational Factors: %n6%n
1) production costs, measured in dollars per kilowatt-hour ($/kWh),
2) non-production costs ($/kWh),
3) purchased power expenses ($/kWh),
4) total electric operating expenses ($/kWh),
5) load factor,
6) reserve margin,
7) average industrial price,
8) percent of load accounted for by industrial customers,
9) percent of fuel mix (in megawatt-hours, or MWh) accounted for by nuclear generation,
10) generation capacity cost, measured in dollars per kilowatt ($/kW),
11) generation assets as a percent of total assets;
12) five-year growth in total MWh sales;
13) capacity factor; and
14) customer density (customers per square mile).
1) Relative perceived regulatory risk of investing in utilities in a particular state, as ranked by state, %n7%n and
2) Relative progress of state toward industry restructuring, as ranked by state. %n8%n
Only three of these 21 possible new independent variables make a significant contribution in explaining the variance in M/B ratios. These three new variables account for a little over one-fourth of the total explained variance (with ROE explaining almost one-half). As to be expected, and as in the initial study of 1995 year-end M/B ratios, the key equity driver is a financial variable, return on equity, which explains 48.4 percent of total variance in M/B ratios. The new model, using more easily accessible data than the stranded-cost calculations of Moody's and S&P, finds nearly 23 percent of variance explained by competitive factors.
Industrial electric price levels account for 15 percent, while the capital