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This primer highlights both the strengths and the limitations of benefit-cost analysis in the development, design, and implementation of regulatory reform.
Why policies should be based on careful consideration of their costs and benefits rather than on intuition, popular opinion, interest groups, and anecdotes. Opinions on government policies vary widely. Some people feel passionately about the child obesity epidemic and support government regulation of sugary drinks. Others argue that people should be able to eat and drink whatever they like. Some people are alarmed about climate change and favor aggressive government intervention. Others don't feel the need for any sort of climate regulation. In The Cost-Benefit Revolution, Cass Sunstein argues our major disagreements really involve facts, not values. It follows that government policy should not be based on public opinion, intuitions, or pressure from interest groups, but on numbers—meaning careful consideration of costs and benefits. Will a policy save one life, or one thousand lives? Will it impose costs on consumers, and if so, will the costs be high or negligible? Will it hurt workers and small businesses, and, if so, precisely how much? As the Obama administration's “regulatory czar,” Sunstein knows his subject in both theory and practice. Drawing on behavioral economics and his well-known emphasis on “nudging,” he celebrates the cost-benefit revolution in policy making, tracing its defining moments in the Reagan, Clinton, and Obama administrations (and pondering its uncertain future in the Trump administration). He acknowledges that public officials often lack information about costs and benefits, and outlines state-of-the-art techniques for acquiring that information. Policies should make people's lives better. Quantitative cost-benefit analysis, Sunstein argues, is the best available method for making this happen—even if, in the future, new measures of human well-being, also explored in this book, may be better still.
Illustrated by case studies from Europe, North America and the Middle East, this book examines how non-market values can be identified, measured and incorporated into planning evaluation methodologies. The traditional means of assessing planning options, benefit-cost analysis, requires that all effects be expressed in monetary terms and this volume offers alternative approaches. It presents strategies for accomplishing the major purposes of planning evaluation - including the provision of an explicit, replicable basis for public assessment - in alternative ways. Growing demand for public involvement and for accountability in decision making requires better means for accommodating a broad range of concerns in planning evaluation. Methodologies examined include effectiveness-cost and multicriteria analysis, and the book explores how these have been applied in practice in developing special-issue plans, complex regional development strategies, and efforts to analyze the environmental justice implications of major infrastructure projects. Use of scenarios and problem structuring methods by stakeholder groups are also explored.
The U.S. Environmental Protection Agency (EPA) is one of several federal agencies responsible for protecting Americans against significant risks to human health and the environment. As part of that mission, EPA estimates the nature, magnitude, and likelihood of risks to human health and the environment; identifies the potential regulatory actions that will mitigate those risks and protect public health1 and the environment; and uses that information to decide on appropriate regulatory action. Uncertainties, both qualitative and quantitative, in the data and analyses on which these decisions are based enter into the process at each step. As a result, the informed identification and use of the uncertainties inherent in the process is an essential feature of environmental decision making. EPA requested that the Institute of Medicine (IOM) convene a committee to provide guidance to its decision makers and their partners in states and localities on approaches to managing risk in different contexts when uncertainty is present. It also sought guidance on how information on uncertainty should be presented to help risk managers make sound decisions and to increase transparency in its communications with the public about those decisions. Given that its charge is not limited to human health risk assessment and includes broad questions about managing risks and decision making, in this report the committee examines the analysis of uncertainty in those other areas in addition to human health risks. Environmental Decisions in the Face of Uncertainty explains the statement of task and summarizes the findings of the committee.
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The past decade has seen increased attention to cost-effectiveness and benefit-cost analysis in education as administrators are being asked to accomplish more with the same or even fewer resources, philanthropists are keen to calculate their "return on investment" in social programs, and the general public is increasingly scrutinizing how resources are allocated to schools and colleges. Economic Evaluation in Education: Cost-Effectiveness and Benefit-Cost Analysis (titled Cost-Effectiveness Analysis: Methods and Applications in its previous editions) is the only full-length book to provide readers with the step-by-step methods they need to plan and implement a benefit-cost analysis in education. Authors Henry M. Levin, Patrick J. McEwan, Clive Belfield, Alyshia Brooks Bowden, and Robert Shand examine a range of issues, including how to identify, measure, and distribute costs; how to measure effectiveness, utility, and benefits; and how to incorporate cost evaluations into the decision-making process. The updates to the Third Edition reflect the considerable methodological development in the evaluation literature, and the greater empiricism practiced by education researchers, to help readers learn to apply more advanced methods to their own analyses.
This book contains a selection of the papers presented at the XVII SIGEF Congress. It presents fuzzy logic, neural networks and other intelligent techniques applied to economic and business problems. This book is very useful for researchers and graduate students aiming to introduce themselves to the field of quantitative techniques for overcoming uncertain environments. The contributors are experienced scholars of different countries who offer real world applications of these mathematical techniques.
Reducing flood damage is a complex task that requires multidisciplinary understanding of the earth sciences and civil engineering. In addressing this task the U.S. Army Corps of Engineers employs its expertise in hydrology, hydraulics, and geotechnical and structural engineering. Dams, levees, and other river-training works must be sized to local conditions; geotechnical theories and applications help ensure that structures will safely withstand potential hydraulic and seismic forces; and economic considerations must be balanced to ensure that reductions in flood damages are proportionate with project costs and associated impacts on social, economic, and environmental values. A new National Research Council report, Risk Analysis and Uncertainty in Flood Damage Reduction Studies, reviews the Corps of Engineers' risk-based techniques in its flood damage reduction studies and makes recommendations for improving these techniques. Areas in which the Corps has made good progress are noted, and several steps that could improve the Corps' risk-based techniques in engineering and economics applications for flood damage reduction are identified. The report also includes recommendations for improving the federal levee certification program, for broadening the scope of flood damage reduction planning, and for improving communication of risk-based concepts.
With the expansion of new technologies, materials, and the design of complex systems, the expectations of society upon engineers are becoming larger than ever. Engineers make critical decisions with potentially high adverse consequences. The current political, societal, and financial climate requires engineers to formally consider the factors of uncertainty (e.g., floods, earthquakes, winds, environmental risks) in their decisions at all levels. Uncertainty Modeling and Analysis in Civil Engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in real-world situations. Topics include Neural networks Genetic algorithms Numerical modeling Fuzzy sets and operations Reliability and risk analysis Systems control Uncertainty in probability estimates This compendium is a considerable reference for civil engineers as well as for engineers in other disciplines, computer scientists, general scientists, and students.