The Fortnightly 100 Revisited: Do Utility Stock Prices Reflect Operational Efficiency?
is poised for competition, and how effectively it communicates these to the public, this perception may or may not be favorable. This variable is represented in this analysis in the form of an index of deregulation activity. The index ranges from one to four based on the following designation:
retail choice approved for all customers, index value = 4;
retail choice approved for some customers, index value = 3;
retail choice under consideration, index value = 2;
little or no regulatory action on retail choice, index value = 1.
For utilities with operations in more than one jurisdiction, we weighted the index values, based on total megawatt-hour sales. Given the uncertainty inherent in the dynamics of competitive markets, we expect deregulation and open access to affect adversely market value. Figure 1 shows the M/B ratio for the various NERC regions.
4. Capacity mix: Fuel diversity provides flexibility in a changing environment. Potential supply disruptions and price fluctuations can raise rates and ignite political and regulatory pressure that ultimately may lead to erosion of financial performance. We hypothesize that the ability to alter generating sources and take advantage of lower cost fuels would be viewed favorably by financial markets. Fuel diversity in this analysis is represented in terms of a modified measure of entropy, the "G" index with a range of zero to one.fn6 It measures how generation of power is distributed among hydro, steam, nuclear and other fuel sources. The less concentrated is the power output, the higher the value of "G." Thus, if all of a utility's power were generated from a single source, the value of "G" would take the value of zero. Conversely, if generation were distributed evenly among four fuels, the value would be unity.
5. Operational Efficiency: For this category we relied on the universe of utilities and their efficiency ranks used for The Fortnightly 100, as published in Sept. 1, 1998. The method there employed Data Envelopment Analysis. DEA uses a mathematical optimization to construct a convex production frontier, tracking the input/output ratios of the most efficient companies. Companies that form the production frontier are considered efficient and receive a score of 1.0. All other utilities receive an efficiency score between 0 and 1.0, based on distance from the production frontier.
Other Miscellaneous Factors. The operation of nuclear plants poses a special challenge for electric utilities. While a nuclear plant can offer significant opportunities in resource flexibility, the aging stock of nuclear plants is likely to increase financial exposure resulting from higher maintenance expenses and uncertain costs of decommissioning. More stringent environmental restrictions also can add significantly to operation and maintenance costs and in disposal fees for spent fuel. To test this hypothesis, we included nuclear plant ownership as a separate variable in our analysis.
By contrast, we ignored consideration of several other variables, known to have a bearing on perceptions of performance and value in the financial community, particularly management and prices. Surely a utility's management is of paramount importance to its market performance, since management's decisions affect all areas of the utility's operations. But