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Wisdom of the experts: Using survey responses to address positive and normative uncertainties in climate-economic models
Climatic Change ( IF 4.8 ) Pub Date : 2020-07-07 , DOI: 10.1007/s10584-020-02771-w
Peter Harrison Howard , Derek Sylvan

The social cost of carbon (SCC) and the climate-economic models underlying this prominent US climate policy instrument are heavily affected by modeler opinion and therefore may not reflect the views of most climate economists. To test whether differences exist, we recalibrate key uncertain model parameters using formal expert elicitation: a multi-question online survey of individuals who have published scholarship on the economics of climate change, with 165 to 216 respondents, depending on the question. Survey questions on the magnitude of climate impacts and appropriate discount rates revealed that prevailing views differ from prominent IAMs, including DICE. We calibrate the DICE damage functions and discount rates to reflect the mean and median survey responses, respectively, recognizing these two parameters’ differing sources of uncertainty (positive versus normative). We find a 16-fold higher SCC than the base DICE-2013R assumptions, with a range of 11- to 24-fold under alternative modeling assumptions (using the DICE-2016R2 model version and calibrating damages to median rather than mean responses). Our findings support a 7- to 13-fold SCC increase for different respondent subgroups even when we exclude the potential for catastrophic climate impact shocks. Our results reveal a significant disparity between IAMs and the broader community of scholars publishing in this field.

中文翻译:

专家的智慧:利用调查回应解决气候经济模型中积极和规范的不确定性

碳的社会成本 (SCC) 和作为美国这一著名气候政策工具基础的气候经济模型受到建模者意见的严重影响,因此可能无法反映大多数气候经济学家的观点。为了测试是否存在差异,我们使用正式的专家启发重新校准关键的不确定模型参数:一项多问题在线调查,针对发表了气候变化经济学奖学金的个人,根据问题的不同,有 165 到 216 名受访者。关于气候影响程度和适当贴现率的调查问题表明,主流观点与著名的 IAM 不同,包括 DICE。我们校准 DICE 损害函数和贴现率以分别反映平均和中位数调查响应,认识到这两个参数的不同不确定性来源(积极与规范)。我们发现 SCC 比基本 DICE-2013R 假设高 16 倍,在替代建模假设下(使用 DICE-2016R2 模型版本并校准对中值而非平均响应的损害)范围为 11 到 24 倍。我们的研究结果支持不同受访者亚组的 SCC 增加 7 到 13 倍,即使我们排除了灾难性气候影响冲击的可能性。我们的结果揭示了 IAM 与在该领域发表论文的更广泛的学者社区之间存在显着差异。在替代建模假设下(使用 DICE-2016R2 模型版本并校准对中值而不是平均响应的损害)范围为 11 到 24 倍。我们的研究结果支持不同受访者亚组的 SCC 增加 7 到 13 倍,即使我们排除了灾难性气候影响冲击的可能性。我们的结果揭示了 IAM 与在该领域发表论文的更广泛的学者社区之间存在显着差异。在替代建模假设下(使用 DICE-2016R2 模型版本并校准对中值而不是平均响应的损害)范围为 11 到 24 倍。我们的研究结果支持不同受访者亚组的 SCC 增加 7 到 13 倍,即使我们排除了灾难性气候影响冲击的可能性。我们的结果揭示了 IAM 与在该领域发表论文的更广泛的学者社区之间存在显着差异。
更新日期:2020-07-07
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