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Efficiently Inefficient: Regulatory Optimization That Cares About Tomorrow’s Lost Civilizations

Abstract

Climate change has been an issue on the global stage for more than 40 years, and regulatory action has evolved as the consequences of climate change become closer to reality. While governmental action during that period has resulted in great reductions in pollution, some nations are beginning to see devastating impacts of climate change. For some island nations, entire cultures will be wiped out within the next few generations. Despite the severity of the climate crisis, the United States has clung to a traditional economic framework to measure and evaluate environmental regulations—one that values cost efficiency over successful conservation, even when vast degrees of uncertainty severely limit the framework’s empirical value. While the international stage has moved on from trying to measure the value of preserving threatened ecosystems, shrinking landmasses, and entire cultures, the United States leans on manipulable and arbitrary assumptions to drive its evaluation of environmental regulation standards. The United Kingdom has adopted a middling approach using marginal abatement costs (MACs)—the total cost necessary to achieve a specific climate goal—which the United States has rejected for exhibiting the same suboptimal tendencies as the international precautionary principle.

The MAC framework removes a significant amount of uncertainty that plagues the traditional cost-benefit model by ensuring that climate goals are met. In the case of the environment, certainty of outcome is an incredibly valuable element of any model. Optimization is also important where administrative resources are scarce and overinvestment in the environment means underinvestment in other areas of public welfare. Recognizing the degree to which the United States values optimization, this Note suggests legislation adopting a modified MAC approach to valuing environmental regulation that provides the outcome security that traditional models lack while maintaining a trend toward optimized cost efficiency.