Imagine That!
A Stock-price Premium for DSMA rise in DSM spending (as a percentage of total expenditures) indicated an increase in market-to-book ratio.
For electric utilities, financial and managerial attributes such as rate of return or the dividend payout ratio often exert a strong positive effect on the market-to-book (M/B) ratio (em the ratio of the company's stock price divided by book value. Other factors may carry a negative impact, and these items typically might include the extent of debt financing, nuclear power plant construction, or the percentage of total costs paid in taxes or for fuels.
But what about demand-side management (DSM) programs?
We examined how utility investment in DSM affected M/B ratios, analyzing four years of data collected and made available by the U.S. Energy Information Agency (EIA) for the period 1990-93, which saw the enactment of the Energy Policy Act of 1992, allowing monopoly utilities to own unregulated generating companies and the Federal Energy Regulatory Commission (FERC) to order transmission access (em two developments suggesting that capital markets during that period would have been efficient and would have incorporated the impact of future competition in utility stock market prices. (Nevertheless, the full impact of retail competition may not have been totally felt in the capital markets until the California Blue Book came out in April 1994.)
Findings
Importantly, and perhaps surprisingly, our model indicated that investors viewed utilities investing in DSM more favorably than those that did not. Based on the coefficient of a variable defined as "DSM as a Percentage of Total Expenses," our model indicated that a one-percent increase in the share of total expenditures made up by DSM was associated with a 1.9-point increase in M/B ratio.
The graph compares actual M/B ratios over the four-year study period to hypothetical utilities spending 0 percent and 5 percent of total expenditures on DSM.
Of course, DSM expenses may act as a proxy for other variables, such as innovative market strategies or greater levels of customer service. And the fact that DSM expenses may indicate a deferral of new construction might also serve as an explanation for our findings.
In general the market appeared to favor utilities not investing heavily in new construction. That the market put a higher valuation on utilities deferring capital expenditures was also revealed by the parameter estimate of the average plant age. Part of this impact on the M/B ratio is also due to a plant's depreciation lowering a firm's book value. If stock values decrease at a rate lower than asset values due to depreciation, M/B ratios will increase.
Nevertheless, the model appeared to perform very well, with a 64-percent overall explanatory power and statistically significant estimates for most parameters. The parameters estimated in the equation also had the expected signs. The annual intercepts (em YEAR91, YEAR92, and YEAR93 (em captured much of the steady rise that utility stocks experienced over this four-year period.
Other variables with a very significant impact on the M/B ratio included the rate of return and the dividend pay-out ratio, as one would expect. Increased stock prices should be associated with utilities having greater earnings and providing greater annual incomes to their stockholders. The equity-debt ratio also positively affected the M/B ratio, indicating more leveraged utilities tended to have lower M/B ratios. In turn, this showed the market penalized the use of debt financing.
Interestingly, the presence of least-cost planning requirements exerted a significant negative impact on M/B ratios. In fact, utilities with mandated least-cost planning averaged M/B ratios nearly 9 points lower than those that did not.
Model and Sample
Our model drew the hypothesis that successful and unsuccessful corporate strategies typically are rewarded or penalized by an increase or decrease in stock values, and that DSM investment should affect a utility's stock value. The simple equation used in modeling this information is quite similar to those used in earlier studies measuring the effects of such factors as rate of return on regulatory climate:
M/B Ratio = _(DSM, Financial, Managerial,
Operating, Regulatory)
Utilities pursuing a corporate strategy favored by the market can expect their M/B ratios to rise as stock prices are bid up relative to their book values.
The EIA collects a large volume of annual data on the financial and operating characteristics of private and public utilities. Fairly detailed information is available for approximately 180 of the largest investor-owned utilities. At the end of 1989, these utilities represented 99 percent of investor-owned utility sales and comprised just under 79 percent of total electricity revenues.
The Value Line Investment Survey also proved very valuable in the sample for the study. Value Line data included a various financial information, load factors, peak loads, capacities, rates of return, dividend pay-out ratios, and average ages of plants. Value Line also reported merger activities and bankruptcies. Utilities were dropped if they had merged with another utility during the four-year analysis period. (Merger year data are often inconsistent.) Other utilities were
omitted if they were not covered by Value Line or Moody's Utilities. A few utilities were removed from the sample due to significant foreign operations, or because most of their business activities were outside the electric utility industry. The final sample of holding companies, with complete data for the 4-year study period, included 81 holding companies representing 119 utility operating companies.
T.Pp
able 1. Samples
Sample Utilities
Operating companies reported by EIA 1990-1993 190
Operating companies dropped 71
Operating companies used in the analysis 119
Number of holding companies used in the analysis 81
Using the final sample (em electric holding companies (em provided a good indication of overall DSM impacts in the models estimated. In 1990, these electric utilities sold 60.7 percent of all electricity sold in the United States (em and 78.6 percent of the electricity sold by U.S. investor-owned utilities. In the same year, these utilities represented 83.5 percent of the total, nationally-reported DSM expenditures and 92 percent of DSM expenditures reported by all investor-owned utilities.
Available variables included detailed information on the companies' financial and operating characteristics, approximate demographic data on each utility's customer base, information on each utility's regulatory environment, weather variables, and prices for competing fuels.
Running the regression model using 1990 to 1993 data produced results indicating effects on M/B ratio and the significance of such effects:
T
able 2. Parameters and Significance
Variable Parameter Estimate t-Statistic
INTERCEPT 4.01 0.46
YEAR91 8.09 3.19
YEAR92 22.56 8.60
YEAR93 32.48 10.59
Average Plant Age 1.23 1.34
Equity to Debt Ratio 1.21 8.07
Percentage of Industrial Sales 0.27 3.08
Rate of Return 3.11 5.38
Dummy Variable
(l=favorable regulatory environ.) 5.16 1.48
Dummy Variable
(l=least-cost planning required) -8.93 -3.08
Dividend PayOut Ratio 1.82 4.03
CWIP (% of plant & equipment) -0.43 -4.48
Sales to Other Utilities (%) -0.13 -1.90
DSM (% of total expenses) 1.90 2.05
Parameter estimates show the impact of a marginal change in the associated variable on the M/B ratio. For example, the M/B ratio increased by 0.27 points for each percentage point increase in industrial sales. The t-statistic indicates the statistical significance of the estimated relationship. The larger the t-statistic, the more significant the relationship (e.g., the more confidence we have in the validity of the finding). t
Philipp Degens and M. Sami Khawaja are economists in the Portland, OR, offices of Barakat & Chamberlin, Inc., and provide services to the utilities industry.
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