Market Model Stationarity of Individual Public Utilities

Abstract

The search for an economically sound procedure for estimating an appropri? ate rate of return on equity consistent with the Supreme Court's ruling in the Hope case [13] has Ied many economists, financial experts, and public service commissions to estimate the rate of return on equity with the capital asset pricing model (CAPM) (see [30], [19], and [21]). The popularity of the CAPM in regu? latory proceedings was reported by Harrington [15] who, in a survey of public service commissions, found that 38 states were considering or had seen the CAPM used, two jurisdictions preferred the CAPM, Oregon required the CAPM, and South Carolina would require the CAPM in all future cases. Hence, given the popularity of the CAPM and the tremendous economic impact that out? comes of regulatory proceedings have on the financial well-being of both the regulated firm and the consumer, it is critical that if the CAPM is used in regula? tory proceedings that it be applied in the best manner possible and that any limitations associated with the CAPM be recognized fully. A prime factor in the application of the CAPM is the estimation of the mar? ket model [29] to obtain an estimate of the ex ante beta (p), the systematic risk, of both the regulated firm in question and comparable nonregulated firms. Since the market model usually is estimated on the basis of ex post data, a necessary condition for an accurate estimate of (3 is that the market model is stationary or unchanging over time. Hence, the ability to assess systematically and accurately the stationarity of the market model is critical to the proper application of the CAPM. The objectives of this study are: (1) to use a more powerful statistical test, the cusum of squares of recursive residuals, to determine the stationarity of the market model of individual securities in a specified time period; (2) to provide empirical evidence of the stationarity of the market model for regulated firms; (3) to provide empirical evidence concerning the stationarity of the market model by industry; and (4) to use Quandt's log likelihood ratio for identifying when a secu