Regulatory decisions to approve, restrict development, or halt the marketing of new pharmaceuticals require evaluating the balance between benefits and risks, given the available evidence at a point in time. In response to concerns about how such decisions are reached, there is increasing interest in using patients' perceptions of the benefits of treatment features and their tolerance for possible risks to help inform regulatory decisions. Stated-choice methods, which measure stated preferences and are sometimes called discrete-choice experiments or conjoint analysis, are often the most valid and reliable techniques available for quantifying patient preferences because data on actual choices are limited. This introduction discusses how to adapt and apply stated-choice methods to quantitative benefit-risk analysis. We outline the conceptual framework for measuring patient preferences and the requirements for developing and administering a valid survey instrument. We also provide a numerical example illustrating how stated-choice data can be used to quantify benefit-risk tradeoff preferences. Finally, we discuss some limitations and practical considerations involving its use for regulatory and clinical decision making.

This second edition of Measuring Nonuse Damages Using Conjoint Valuation is essentially a reprint of a 1992 monograph that has been in steady demand since its original appearance. The RTI Press edition, which is intended to meet continued inquiries and requests for the monograph, contains a Foreword and a Preface to the second edition that put the original work into historical perspective. These studies of ways to value stated preferences, as applied then to the Exxon Valdez oil spill, continue to be a timely and still-rigorous examination of such methods; even with the passage of time and statistical advances from the past two decades, the conclusions and insights as to whether and how these techniques might still be employed in valuing use or nonuse losses from similar events remain valid.

The transfer study, a technique used in cost-benefit analysis, is an increasingly important tool used by government agencies to assess environmental regulatory policy. This innovative book develops protocols for using the transfer method to approach environmental problems and introduces several significant conceptual and methodological advances that refine the transfer process. The transfer approach to quantitative policy analysis adapts information and data from existing studies and so provides an economical way to assess potential benefits and costs for projects. The book presents a detailed framework for examining the transfer of information, outlines the basic steps of the method, and discusses solutions to frequently encountered problems. It then illustrates the method with an extensive case study of environmental externalities from electricity generation. This case study provides the opportunity to discuss salient aspects of the transfer method in more detail, including conceptual principles, the quality of original studies, empirical difficulties and estimation techniques. It also demonstrates the use of state-of-the-art techniques such as meta analysis to synthesise and transfer information from multiple studies and assesses the reliability of the transfer estimates with repeated computer simulations, a technique known as Monte Carlo analysis. Environmental Policy Analysis with Limited Informationwill appeal to environmental policy analysts and managers as well as environmental economists.

This paper reports the first test of how exogenous health shocks impact people's longevity expectations. The analysis exploits the panel structure of the Health and Retirement Study and tests whether smokers, former smokers and those who never smoked react differently to serious, smoking related health shocks. The results support the conclusion that smokers have a different risk perception process. Smokers were only sensitive to their own smoking related illnesses while former smokers and those who never smoked react to a wider range of health related signals. These findings, along with related research on how smokers react to information messages, suggest that generalized messages about the hazards of smoking may be less effective than information about personal activity restrictions associated with smoking related diseases.

Note: The following text is a description of the paper and not the text of the abstract as printed in the Journal of Health Economics. Placing dollar values on human health has long been a controversial aspect of policy analysis and remains difficult, given the relatively small number of morbidity-valuation studies available. By combining both the economic and health literature, this paper offers an alternative approach to morbidity valuation and provides estimates for a wide range of short-term health conditions.