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Attitudes Toward Managing Hazardous Waste: What Should Be Cleaned Up and Who Should Pay for It?
Authors:Jonathan Baron  Rajeev Gowda  Howard Kunreuther
Institution:1 Department of Psychology, University of Pennsylvania, Philadelphia, Pennsylvania 19104.;2 Science and Public Policy Program, University of Oklahoma.;3 Wharton Risk Management and Decision Processes Center, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania 19104–6366.
Abstract:Hazardous waste policy in the United States uses a liability-based approach, including strict, retroactive, and joint and several liability. To assess attitudes toward these basic principles of liability, and toward priorities for clean-up of wastes, a questionnaire was mailed to legislators, judges, executives of oil and chemical companies, environmentalists, and economists. The questionnaire consisted of abstract, simplified cases, which contrasted basic principles rather than dealing with real-world scenarios. Subjects were asked how they would allocate clean-up costs between companies and government as a function of such factors as adherence to standards, adoption of best available technology (BAT), and influence of penalties on future behavior. Most subjects felt that, if the company followed government standards or used the best available technology (BAT), it should pay for only a portion of the clean-up cost, with the government paying the rest. In general, responses did not support the principles underlying current law–strict, retroactive, and joint-and-several liability. Most subjects were more interested in polluters paying for damages than in deterrence or future benefit–even to the extent that they would have "harmless" waste sites cleaned up. A bias was found toward complete clean-up of some sites, or "zero risk." Different groups of subjects gave similar answers, although more committed environmentalists were more willing to make companies pay and to clean up waste regardless of the cost.
Keywords:Hazardous waste  liability  risk attitudes  decision biases
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