INCORPORATING CLIMATE UNCERTAINTY INTO ESTIMATES OF CLIMATE CHANGE IMPACTS

• 成果类型: Article
• 署名作者: Burke, Marshall; Dykema, John; Lobell, David B.; Miguel, Edward; Satyanath, Shanker
• 署名单位: Stanford University; Harvard University; University of California System; University of California Berkeley; New York University
• 刊物名称: REVIEW OF ECONOMICS AND STATISTICS
• ISSN/ISSBN: 0034-6535
• DOI: 10.1162/REST_a_00478
• 发表日期: 2015-05
• 页码: 461-471
• 关键词: agricultural output; random fluctuations; economic-impacts; MODEL

摘要

Quantitative estimates of the impacts of climate change on economic outcomes are important for public policy. We show that the vast majority of estimates fail to account for well-established uncertainty in future temperature and rainfall changes, leading to potentially misleading projections. We reexamine seven well-cited studies and show that accounting for climate uncertainty leads to a much larger range of projected climate impacts and a greater likelihood of worst-case outcomes, an important policy parameter. Incorporating climate uncertainty into future economic impact assessments will be critical for providing the best possible information on potential impacts.