Risk and Return for Regulated Industries provides a much-needed, comprehensive review of how cost of capital risk arises and can be measured, how the special risks regulated industries face affect fair return, and the challenges that regulated industries are likely to face in the future. Rather than following the trend of broad industry introductions or textbook style reviews of utility finance, it covers the topics of most interest to regulators, regulated companies, regulatory lawyers, and rate-of-return analysts in all countries. Accordingly, the book also includes case studies about various countries and discussions of the lessons international regulatory procedures can offer. - Presents a unified treatment of the regulatory principles and practices used to assess the required return on capital - Addresses current practices before exploring the ways methods play out in practice, including irregularities, shortcomings, and concerns for the future - Focuses on developed economies instead of providing a comprehensive global reviews - Foreword by Stewart C. Myers

The paper uses a standard principal agent model to study the merits of separating operational responsibilities and performance reporting. The two tasks are either allocated jointly to one agent or a second agent is hired and tasks are separated. In the latter case, one agent undertakes operational tasks and one agent reports on performance. A joint task allocation is optimal if the reservation wage of the monitoring agent is high or if the substitution between exogenous productivity and effort is low. The value of separating tasks increases with the agents' ability to divert resources to personal consumption and with the probability of realizing a high productivity. Under constant absolute risk aversion, the value of separating tasks increases in the monitoring agent's ability to observe the realized productivity and in her risk aversion. Finally, the value of separating tasks decreases if the two agents collude, but it may still have value.

The paper describes the numerical results obtained when solving an infinitely repeated agency model with strategic income reporting. The model distinguishes itself from previous models of infinitely repeated agency problems on two accounts. First, due to the accrual nature of income reporting, the uncertainty cannot be modeled as independent, identically distributed noise terms. Second, the 'state' is not fully observed by the principal. A consequence of the correlation over time is that the problem has to be solved as a non-linear dynamic programming problem. Using a modified version of Gauss-Seidel value iteration, the computations show that the stock price of a firm fluctuates around a constant. The fluctuations depend on the company's retained earnings and a summary statistic of previous signals. The firm's dividends depend on retained earnings, the firm's accounting reporting strategy, and a summary statistic for previous signals.