Based on decades of research by the scientific community, there is now wide recognition that emissions of greenhouse gases are changing our climate and that the future impacts from such changes will largely be harmful. In response, policymakers across the U.S. government are beginning to consider what actions should be taken to limit climate change damages. An important tool used in making such policy choices is cost-benefit analysis (CBA), but this technique has been widely criticized as inadequate as the primary approach to valuing the impacts of climate change.
In March 2009, the Pew Center on Global Climate Change convened an expert workshop to examine the state of the art, limitations, and future development needs for analyzing the benefits of avoided climate change. Approximately 80 people from academe, federal agencies, and nongovernmental organizations participated. This event was motivated by widespread recognition of two developments: First, policy decisions that result in reduced greenhouse gas emissions are becoming more commonplace across the government. Second, one of the key tools used to analyze such policies, CBA, is challenged by the longterm, global, and uncertain nature of climate change.
Drawing from the environmental economics, impacts and vulnerability, and risk analysis communities, the workshop sought to glean insights on how to better quantify the benefits of reducing greenhouse gas emissions. The main objectives were to inform the development of a set of practical recommendations that decision makers could employ in the near-term and to outline new approaches to improve decision-making tools over time. Based on the outcome of the workshop, the Pew Center responded to the Office of Management and Budget’s request for public comments on how to improve the process and principles governing federal regulatory review. In February 2010, the Interagency Working Group on the Social Cost of Carbon issued a report detailing its recommendations for how this metric should be calculated in agency regulatory decisions.