Climate change affects inequalities between countries in two ways. On the one hand, rising temperatures from greenhouse gas accumulation cause impacts that fall more heavily on low-income countries. On the other hand, the costs of mitigating climate change through reduced emissions could slow down the economic catch-up of poor countries. Whether, and how much the recent decline in between-country inequalities will continue in the twenty-first century is uncertain, and the existing projections rarely account for climate factors. In this study, we build scenarios that account for the joint effects of mitigation costs and climate damages on inequality. We compute the evolution of country-by-country GDP, considering uncertainty in socioeconomic assumptions, emission pathways, mitigation costs, temperature response, and climate damages. We analyze the resulting 3408 scenarios using exploratory analysis tools. We show that the uncertainties associated with socioeconomic assumptions and damage estimates are the main drivers of future inequalities. We investigate under which conditions the cascading effects of these uncertainties can counterbalance the projected convergence of countries’ incomes. We also compare inequality levels across emission pathways and analyze when the effect of climate damages on inequality outweigh that of mitigation costs. We stress the divide between IAM- and econometrics-based damage functions in terms of their effect on inequality. If climate damages are as regressive as the latter suggest, climate mitigation policies are key to limit the rise of future inequalities between countries.
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SSP trajectories are available at https://tntcat.iiasa.ac.at/SspDb/dsd?Action=htmlpage&pages=about(version 2.0).
We are not aware of publicly available regional damage estimates from FUND.
The pairs (pc, i, Ic, i) represent the Lorenz curve: a proportion pc, i of the population earns a proportion Ic, i of global income. Graphically, the Gini coefficient is worth half the area between the Lorenz curve and the first bisector.
Results from the PRIM analysis are provided in the Supplementary Material.
We used rpart function of R (complexity parameter of rpart function is set at 0.02, meaning that a split is retained if it increases the fit by a factor 0.02)
Note that models have not produced this emission pathway under the most pessimistic socioeconomic pathway (SSP 3), where low growth is combined with high challenge to mitigation
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The authors would like to thank three anonymous reviewers for their very valuable feedback. The authors would also like to thank, Stéphane Hallegatte, Eloi Laurent, Louis-Gaëtan Giraudet, and participants to the 2018 EAERE-VIU-FEEM Summer School on Climate Change Assessment in Venice. The authors acknowledge funding provided by the NAVIGATE project (H2020/2019-2023, grant agreement number 821124) of the European Commission.
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Taconet, N., Méjean, A. & Guivarch, C. Influence of climate change impacts and mitigation costs on inequality between countries. Climatic Change 160, 15–34 (2020). https://doi.org/10.1007/s10584-019-02637-w
- Climate change
- Scenario analysis
- Climate mitigation
- Socioeconomic scenario
- Climate change impact