1. ENVIRONMENTAL POLICY ANALYSIS: WHAT AND WHY? Why environmental policy analysis? Environmental issues are growing in visibility in local, national, and world arenas, as a myriad of human activities leads to increased impacts on the natural world. Issues such as climate change, endangered species, wilderness protection, and energy use are regularly on the front pages of newspapers. Governments at all levels are struggling with how to address these issues. Environmental policy analysis is intended to present the environmental and social impacts of policies, in the hope that better decisions will result when people have better information on which to base those decisions. Conducting environmental policy analysis requires people who understand what it is and how to do it. Interpreting it also requires those skills. We hope that this book will increase the abilities, both of analysts and of decision-makers, to understand and interpret the impacts of environmental policies. Policy analysis books almost invariably begin by pointing out that policy analysis can take many forms. This book is no different. As you will see in Chapter 1, we consider policy analysis to be information provided for the policy process. That information can take many forms, from sophisticated empirical analysis to general theoretical results, from summary statistics to game theoretic strategies.

Pressing environmental challenges are frequently surrounded with stakeholders on all sides of the issues. Opinions expressed by government agencies, the private sector, special interests, nonprofit communities, and the media, among others can quickly cloud the dialogue, leaving one to wonder how policy decisions actually come about. In Environmental Policy Analysis and Practice, Michael R. Greenberg cuts through the complicated layers of bureaucracy, science, and the public interest to show how all policy considerations can be broken down according to six specific factors: 1) the reaction of elected government officials, 2) the reactions of the public and special interests, 3) knowledge developed by scientists and engineers, 4) economics, 5) ethical imperatives, and 6) time pressure to make a decision. The book is organized into two parts, with the first part defining and illustrating each one of these criteria. Greenberg draws on examples such as nuclear power, pesticides, brownfield redevelopment, gasoline additives, and environmental cancer, but focuses on how these subjects can be analyzed rather than exclusively on the issues themselves. Part two goes on to describe a set of over twenty tools that are used widely in policy analysis, including risk assessment, environmental impact analysis, public opinion surveys, cost-benefit analysis, and others. These tools are described and then illustrated with examples from part one. Weaving together an impressive combination of practical advice and engaging first person accounts from government officials, administrators, and leaders in the fields of public health and medicine, this clearly written volume is poised to become a leading text in environmental policy.

With the growing number, complexity, and importance of environmental problems come demands to include a full range of intellectual disciplines and scholarly traditions to help define and eventually manage such problems more effectively. Decision Making for the Environment: Social and Behavioral Science Research Priorities is the result of a 2-year effort by 12 social and behavioral scientists, scholars, and practitioners. The report sets research priorities for the social and behavioral sciences as they relate to several different kinds of environmental problems.

The primary aim of this reference volume is to provide an accessible and comprehensive review of current methods used to address resource evaluation and environmental as well as climate issues, and in a manner easily understood by decision-makers and the non-economists interested in environmental policy matters. Theoretical insight and empirical observations from various countries will be presented and recommendations on sustainable environmental decision-making will be given. Natural resource managers, environmental and climate decision-makers, government policy makers, and economics scholars will all find this volume to be an essential reference.

This book argues in favor of using cost-benefit analysis globally and examines the positive impact it can have in developing countries using relevant case studies. The book discusses the potential for cost-benefit analysis to provoke a global shift toward stronger and more effective economic policies.

Many regulations issued by the U.S. Environmental Protection Agency (EPA) are based on the results of computer models. Models help EPA explain environmental phenomena in settings where direct observations are limited or unavailable, and anticipate the effects of agency policies on the environment, human health and the economy. Given the critical role played by models, the EPA asked the National Research Council to assess scientific issues related to the agency's selection and use of models in its decisions. The book recommends a series of guidelines and principles for improving agency models and decision-making processes. The centerpiece of the book's recommended vision is a life-cycle approach to model evaluation which includes peer review, corroboration of results, and other activities. This will enhance the agency's ability to respond to requirements from a 2001 law on information quality and improve policy development and implementation.

This report discusses how policymakers should deal with economic distortions on the cost-side of cost-benefit analysis in the area of environmental policies, and assesses the existing Nordic guideline recommendations. The two types of economic distortions are distortions to product markets, which are almost by definition tied to environmental policy interventions, and distortions to labour supply decisions. Drawing on best practices from the literature, we formulate a number of key principles useful for assessing the impact on labour supply decisions and welfare on product markets from policy interventions. Four analytical examples are included to illustrate the importance of these principles for the correct quantification of distortionary impacts, especially the importance of taking into account pre-existing policy induced distortions.