In this issue brief, RFF researchers estimate the global economic benefits of limiting temperature rise to the Paris Agreement targets of 1.5°C and “well below” 2°C above preindustrial levels.
Date Oct. 16, 2023 Authors Jordan Wingenroth , Brian C. Prest , and Kevin Rennert Publication Issue Brief Reading time 6 minutesThe 2023 Global Stocktake (GST) that is scheduled to conclude at COP28 offers an opportunity to not only look back and measure progress toward the Paris Agreement goals but also look ahead and consider the benefits of achieving them. Estimating the economic benefits of reducing climate change requires a model that incorporates both socioeconomic and climatological elements, accounting for both the long-lived repercussions of near-term emissions and uncertainty in future emissions and temperature trajectories. In this issue brief, we use the Greenhouse Gas Impact Value Estimator (GIVE) model (Rennert et al. 2022) to estimate the global economic benefits of limiting temperature rise to the Paris Agreement targets of 1.5°C and “well below” 2°C above preindustrial levels. We construct modified versions of the GIVE model that are calibrated to meet these targets, and we compare them to the baseline model, which combines estimates made by a panel of experts about future population, GDP, and emissions trajectories with a robust climate model to arrive at a central outcome of 2.5°C above preindustrial levels in 2100. This baseline reflects an estimate of anticipated future emissions pathways as of the date of the elicitation, which was conducted in 2021. This sets it apart from business-as-usual scenarios because it captures the benefits that experts estimated would be achieved with the knowledge that they possessed at the time. We find that mitigation efforts that reduce expected warming from that scenario with a 2.5°C central temperature outcome to instead remain well below 2°C would generate cumulative expected economic benefits of $467 trillion in present value through 2300, equivalent to 1.5 percent of the cumulative expected present value of global GDP over the same time frame. In equivalent annual terms, this $467 trillion figure corresponds to $5.2 trillion in annual benefits. Holding the temperature increase to below 1.5°C would generate an additional $138 trillion, bringing the total benefits to $605 trillion or 2 percent of cumulative GDP. $605 trillion amounts to $6.8 trillion in equivalent annual terms. These estimated benefits incorporate the societal impacts of climate change that research suggests are most significant, but many other impacts have yet to be accounted for. Furthermore, our estimates represent incremental benefits from increasingly ambitious scenarios, but even the baseline scenario reflects some of the progress made since the Paris Agreement was signed and how such progress influenced our expert panel’s expectations for the future. For both of these reasons, our results should be understood as conservative estimates of the total benefits of achieving the agreement’s goals.
The GIVE model features a detailed, probabilistic representation of uncertainty in future socioeconomic, emissions, and temperature trajectories and the resulting impacts on society in terms of human mortality, agricultural losses, energy use, and coastal effects of sea level rise. The model generates a set of 10,000 randomly sampled scenarios, each representing one possible future of country-level population and GDP, global greenhouse gas emissions, global mean surface temperature, and monetized climate damages. GIVE draws its population, GDP, and emissions scenarios from the Resources for the Future Socioeconomic Projections (RFF-SPs) (Rennert et al. 2021), which are multicentury probabilistic projections of these variables. The RFF-SPs combine econometric and expert-elicitation methods to account for uncertainty about future technology and policy, as we describe in greater detail in a previous issue brief also submitted to the GST (Wingenroth et al. 2023).
To create modified versions of GIVE that reflect the Paris Agreement goals, we imposed an upper bound on the trajectories of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) annual emissions in the RFF-SPs. For both the 1.5°C and 2°C goals, we set the upper bound at the quantile that achieved the respective goal (1.5°C or 2°C) in 2100 with the respective probability (50 or 67 percent) indicated in the Sixth Assessment Report (AR6) (IPCC 2023). We used the same quantiles across all three gases and for all years covered by the model. In other words, we determined two different limits on greenhouse gas emissions: one that achieves exactly a two-thirds chance of staying below 2°C and another, more ambitious, scenario that has a 50 percent chance of staying below 1.5°C.
We then ran the baseline GIVE model and the two modified versions 10,000 times each, randomly sampling other variables tied to socioeconomics, the climate model, and the damage functions from GIVE’s standard probability distributions. We maintained consistency between the three model configurations by setting the same seed for the random number generator used for sampling, thus isolating the benefits of reaching the Paris Agreement goals from the random variance in other factors. We excluded sea-level-rise damages from our estimates for technical reasons, but Rennert et al. (2022) demonstrates that this sector only contributes about 1 percent of the benefits of incremental emissions reductions, suggesting that its inclusion would only slightly increase our estimated benefits.
The GIVE model estimates climate damages for each year from 2020 to 2300, a time frame chosen in light of the long atmospheric residence time of CO2 (NASEM 2017). To convert future climate damages into present-day values, we used GIVE’s default, Ramsey-like discounting approach, which corresponds to a 2 percent annual near-term discount rate (Newell et al. 2022; Rennert et al. 2021).