Elsevier

Global Environmental Change

Volume 53, November 2018, Pages 225-232
Global Environmental Change

Social cost of carbon under shared socioeconomic pathways

https://doi.org/10.1016/j.gloenvcha.2018.10.001Get rights and content

Highlights

  • We update the social carbon cost under five shared socioeconomic pathways.

  • This is the first article to address the socioeconomic impact of social carbon cost.

  • The development of regional rivalries will double the present social carbon cost.

  • After 2060, social carbon costs will rise to unbearable levels with continued fossil-fueled development.

Abstract

The Social Carbon Cost (SCC) measures present value of future economic damages caused by an additional ton of carbon emissions, and is widely used by governments to design climate policies. Although the use of SCC is very extensive, its predictions are very difficult. Because the SCC is defined by social welfare associated with economic growth and population, its estimation is necessarily dependent on future assumptions that are difficult to project. Many approaches consider the impact of population or economic growth on the SCC, but these socioeconomic factors must be grounded on solid assumptions concerning political, technological and environmental developments. Over the past seven years, the climate change research community has established five plausible socioeconomic narratives, called ‘Shared Socioeconomic Pathways’ (SSPs), numbered SSP1–SSP5. These scenarios provide descriptions of how the future might unfold in several key areas. To this end, we use the Dynamic Integrated model of Climate and the Economy (DICE) to update the SCC under the five socioeconomic pathways, while also considering alternative damage functions and the social welfare discount rate to address uncertainty. The result of the China Climate Change integrated assessment model (C3IAM) were used to re-estimate parameters in DICE, therefore characterize the SSPs. The results show that, in a world developing towards regional rivalry (SSP3), the SCC today will likely double compared with other scenarios. If emerged developing countries will follow the same path as previous industrializations (SSP5), the SCC will experience a rapid increase after 2060. Inequality (SSP4) will experience low mitigation pressure under a sustainable development scenario (SSP1), while the historical development pattern (SSP2) will have a moderate SCC with higher uncertainty. The results can provide carbon price benchmarks for policy makers who hold different attitudes towards the future and can help address the need to avoid regional rivalries and fossil-fueled development, which may counteract mitigation efforts.

Introduction

After the Paris Agreement, countries have increasingly taken actions to address climate change. Social cost of carbon (SCC), which balances the social costs resulting from emission reductions with the incremental costs of regulation policy has been widely used to provide policy guidance. The US government has relied on the SCC estimates provided by the Interagency Working Group (IWG) as a basis for taxing and implementing regulation policies (Revesz et al., 2017). The IWG SCC estimates started in 2010 and were updated with new scientific developments in 2013 and 2016, resulting in policy benefits of more than $1 trillion (Nordhaus, 2017). The SCC is also increasingly being adopted for regulations at the state level, resulting in regulatory policies in California, New York and Minnesota (California, 2016; Larson, 2016; Minnesota, 2016).

Given the wide range of social and climate interactions included in the calculation, SCC estimation is necessarily complex and highly uncertain (Pindyck, 2013). Damage functions and social welfare discounts are considered the two major contributors to this uncertainty (Cai et al., 2016; Diaz and Moore, 2017; Heal and Millner, 2014; Howarth et al., 2014; Pycroft et al., 2014); however, any discussion of these issues is necessarily based on the underlying socioeconomic assumptions. Economic development can alter emission flow patterns (Mi et al., 2017), and—because the SCC is defined by social welfare—population and economic projections are fundamental determinants in its estimation. Scovronick et al. (2017) investigated the influence of future population growth on the SCC, Dietz and Stern (2015) and Moore and Diaz (2015) considered the impacts of climate on economic growth as the drivers of SCC uncertainty. However, the demographic and economic assumptions are only two aspects of the socioeconomic assumption, which may be associated with a wide range of political, technological and environmental contingencies. If the China-US trade war continues developing and becomes a regional rivalry, it may well alter the long-term and global trends, resulting in different SCC patterns.

The SSP framework was initially proposed by Moss et al. (2010) and Van Vuuren et al. (2012), but the quantified and qualified version was published seven years later by Riahi et al. (2017). It include five SSPs which cover the broad spectrum of future challenges to mitigation and adaptation and translate this into consistent narratives of future developments that are quantified for diverse fields like demography, economic growth and convergence, energy, land-use, air pollution, policies, and trading (O’Neill et al., 2017; Riahi et al., 2017). The SSP framework greatly facilitates integrated analyses of mitigation and adaptation. Pizer et al. (2014) revealed the importance of considering the new SSP framework into SCC estimates. However, the current IWG models are too simple to directly quantify the SSP narratives. Therefore, we choose the SSP characteristics quantified by C3IAM (Wei et al., 2018), and use its result to re-estimate the parameters in DICE, in order to characterize the five SSPs. The C3IAM couples CGE with economic growth theory, which result can be used to update the mitigation function in DICE, while match the GDP trajectory with DICE as they both rooted in the economic growth theory.

Our paper estimates the SCC under the five socioeconomic scenarios; we also extend our research by considering the uncertainty caused by damage functions and the social welfare discount rate. The most important innovation of this study is to extent current research by computing the SCC under different socioeconomic pathways (SSPs), rather than considering the demographic and economic separately. The results demonstrate the need to avoid regional rivalries and fossil-fueled development, which can raise the current SCC or induce much heavier mitigation pressures by the end of this century. The SCC value provides a carbon price benchmark for policy makers who hold different attitudes towards the future and is an important reference for future research under the various SSPs.

Section snippets

Overview of the methodology

Dynamic Integrated Climate Economy model (DICE) is one of the three models used by the U.S. government to provide latest SCC estimation, and also been widely used for SCC discussion by scholars (Crost and Traeger, 2014; Moore and Diaz, 2015; Scovronick et al., 2017). Four parameters in DICE are subjected to the socioeconomic assumptions, namely the population, total factor productivity (TFP), carbon intensity, and the mitigation functions. To characterize the SSPs in DICE, these parameters need

Evaluating the SSP outcomes in DICE

As shown in Fig. 1, the socioeconomic assumption is accompanied by a particular emission trajectory. The emission patterns differentiate under each SSP, leading to increases in atmospheric concentrations, which indicate the long-term temperature trends. Temperature is the direct indicator of climate change and produces different degrees of climate damage, which further determine the SCC. Therefore, we chose emission, concentration and temperature to illustrate the major outcome of SSP in the

Conclusions

Paris Agreement had promoted more countries to implement climate policy, and the cost-benefit of climate policy is a good point for nations to start. As the SCC internalize the CO2 externality, its value will be helpful to provide regulatory policy guidance. The term has been used for carbon tax, tradable obligations or renewable portfolio standards (Burke, 2016). However, SCC estimation relies heavily on future assumptions (e.g., mitigation and adaptation challenges, population growth and

Acknowledgements

The authors gratefully acknowledge the support from the National Key R & D Program (Grant No. 2016YFA0602603), the National Natural Science Foundation of China (Grant Nos. 71521002, 71642004, 71673026). The paper also benefitted from the participants at a seminar at Beijing Institute of Technology.

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