The uncertainty about the total economic impact of climate change

This paper uses a vote-counting procedure to estimate the probability density function of the total economic impact as a parabolic function of global warming. There is a wide range of uncertainty about the impact of climate change up to 3°C, and the information becomes progressively more diffuse beyond that. Warming greater than 3°C most likely has net negative impacts, and warming greater than 7°C may lead to a total welfare loss. The expected value of the social cost of carbon is about $29/tC in 2015 and rises at roughly 2% per year

Bootstraps for meta-analysis with an application to the total economic impact of climate change

Abstract Bootstrap and smoothed bootstrap methods are used to estimate the uncertainty about the total impact of climate change, and to assess the performance of commonly used impact functions. Kernel regression is extended to include restrictions on the functional form. Impact functions do not describe the primary estimates of the economic impacts very well, and monotonic functions do particularly badly. The impacts of climate change do not significantly deviate from zero until 2.5–3.5 ◦C warming. The uncertainty is large, and so is the risk premium. The ambiguity premium is small, however. The certainty equivalent impact is a negative 1.5 % of income for 2.5 ◦C, rising to 15 % (50 %) for 5.0 ◦C for a rate of risk aversion of 1 (2)