Optimal Regulation addresses the central issue of regulatory economics—how to regulate firms in a way that induces them to produce and price "optimally." It synthesizes the major findings of an extensive theoretical literature on what constitutes optimality in various situations and which regulatory mechanisms can be used to achieve it. It is the first text to provide a unified, modern, and nontechnical treatment of the field.
The book includes models for regulating optimal output, tariffs, and surplus subsidy schemes, and presents all of the material graphically, with clear explanations of often highly technical topics.
Topics include: The cost structure of natural monopoly (economies of scale and scope). Characterization of firsthand second-best optimality. Surplus subsidy schemes for attaining first-best optimality. Ramsey prices and the Vogelsang-Finsinger mechanism for attaining them. Time-ofuse (TOU) prices and Riordan's mechanisms for attaining the optimal TOU prices' Multipart and self-selecting tariffs, and Sibley's method for using self-selecting tariffs to achieve optimality. The Averch-Johnson model of how rate-of-return regulation induces inefficiencies. Analysis of regulation based on the firm's return on Output, costs, or sales. Price-cap regulation. Regulatory treatment of uncertainty and its impact on the firm's behavior. Methods of attaining optimality without direct regulation (contestability, auctioning the monopoly franchise.)
This book addresses two significant research areas in an interdependent fashion. It is first of all a comprehensive but concise text that covers the recently developed and widely applicable methods of qualitative choice analysis, illustrating the general theory through simulation models of automobile demand and use. It is also a detailed study of automobile demand and use, presenting forecasts based on these powerful new techniques.The book develops the general principles that underlie qualitative choice models that are now being applied in numerous fields in addition to transportation, such as housing, labor, energy, communications, and criminology. The general form, derivation, and estimation of qualitative choice models are explained, and the major models - logit, probit, and GEV - are discussed in detail. And continuous/discrete models are introduced. In these, qualitative choice methods and standard regression techniques are combined to analyze situations that neither alone can accurately forecast.Summarizing previous research on auto demand, the book shows how qualitative choice methods can be used by applying them to specific auto-related decisions as the aggregate of individuals' choices. The simulation model that is constructed is a significant improvement over older models, and should prove more useful to agencies and organizations requiring accurate forecasting of auto demand and use for planning and policy development.The book concludes with an actual case study based on a model designed for the investigations of the California Energy Commission.Kenneth Train is Visiting Associate Professor in Economics at the University of California, Berkeley, and Director of Economic Research at Cambridge Systematics, Inc., also in Berkeley. Qualitative Choice Analysis is included in The MIT Press Transportation Studies Series, edited by Marvin L. Manheim.