Dayaratna et al. (Environ Econ Policy Stud 22:433–448, 2020) proposes several improvements to economic- and climate-simulating IAMs and to their input variables. They show that an empirically based ECS estimate, agricultural damage estimates from recent literature, and discount rates as low as 2.5%, when used within the FUND model, yield a negative social cost of carbon through mid-twenty-first century. Five of their propositions, that “fat-tails” of the ECS distribution are improperly simulated by IAMS, FUND does not simulate enough benefits for agriculture, the ECS is near 1.5 °C, DICE and PAGE overestimate the SCC, and the marginal cost of public funds for carbon taxes has a value of at least a few dollars, are more closely analyzed. Estimates of ECS from a recent paper and a 5% discount rate applied to FUND result in an SCC estimated to lie within the range of about −$1 to $2.50 per metric ton CO₂ for the year 2020.

Dayaratna 等人。(Environ Econ Policy Stud 22:433–448, 2020) 对经济和气候模拟 IAM 及其输入变量提出了多项改进。他们表明，当在 FUND 模型中使用基于经验的 ECS 估计、最近文献中的农业损害估计和低至 2.5% 的贴现率时，到 21 世纪中叶碳的社会成本为负。他们的五个命题，即 IAMS 不正确地模拟了 ECS 分布的“肥尾”，FUND 没有模拟足够的农业效益，ECS 接近 1.5 °C，DICE 和 PAGE 高估了 SCC，边际成本碳税的公共资金至少有几美元的价值，需要更仔细地分析。₂为 2020 年。