Tipping Points in the Climate System and the Economics of Climate Change

2020 ◽  
Author(s):  
James Rising ◽  
Simon Dietz ◽  
Thomas Stoerk ◽  
Gernot Wagner
Keyword(s):  
Climate Change ◽  
Economic Impact ◽  
Social Cost ◽  
Economic Impacts ◽  
Tipping Point ◽  
Assessment Model ◽  
Tipping Points ◽  
Social Cost Of Carbon ◽  
The Social ◽  
Impacts Of Climate Change

<div>Tipping points in the climate system are a key determinant of future impacts from climate change. Current consensus estimates for the economic impact of greenhouse gas emissions, however, do not yet incorporate tipping points. The last decade has, at the same time, seen publication of over 50 individual research papers on how tipping points affect the economic impacts of climate change. These papers have typically incorporated an individual tipping point into an integrated climate-economy assessment model (IAM) such as DICE to study how the the tipping point affects economic impacts of climate change such as the social cost of carbon (SC-CO2). This literature, has, however, not yet been synthesized to study the joint effect of the large number of tipping points on the SC-CO2. SC-CO2 estimates currently used in climate policy are therefore too low, and they fail to reflect the latest research.</div><div><br><div>This paper brings together this large and active literature and proposes a way to jointly estimate the impact of tipping points. In doing so, we bridge an important gap between climate science and climate economics. To do so, we develop a new integrated assessment model with frontier characteristics: a tractable geophysical module for each tipping point, damage functions based on recent climate econometric advances, and disaggregated climate change impacts at the national level, including from sea-level rise. In this model, we consider the following tipping points: the permafrost carbon feedback, the dissociation of ocean methane hydrates, Amazon forest dieback, the disintegration of the Greenland ice sheet, the disintegration of the West Antarctic ice sheet, the slowdown of the Atlantic Meridional Overturning Circulation, changed patterns of the India summer monsoon, and changes in surface albedo feedback (also referred to as Arctic sea-ice loss).</div> <div> </div> Our preliminary findings show that the geophysical tipping points tend to increase the economic impact of climate change, with a combined effect of increasing the social cost of carbon (SC-CO2) by 14%-43%. The largest contributions to this increase come from methane-related tipping points.</div>

scholarly journals The Influence of the Specification of Climate Change Damages on the Social Cost of Carbon

2012 ◽  
Vol 6 (2012-13) ◽  
pp. 1 ◽  
Author(s):  
Robert E. Kopp ◽  
Alexander Golub ◽  
Nathaniel O. Keohane ◽  
Chikara Onda
Keyword(s):  
Climate Change ◽  
Social Cost ◽  
Social Cost Of Carbon ◽  
The Social ◽  
Climate Change Damages

A RAPID ASSESSMENT MODEL FOR UNDERSTANDING THE SOCIAL COST OF CARBON

2013 ◽  
Vol 04 (01) ◽  
pp. 1350001 ◽  
Author(s):  
STEPHEN C. NEWBOLD ◽  
CHARLES GRIFFITHS ◽  
CHRIS MOORE ◽  
ANN WOLVERTON ◽  
ELIZABETH KOPITS
Keyword(s):  
Monte Carlo ◽  
Social Cost ◽  
Rapid Assessment ◽  
Expected Value ◽  
Assessment Model ◽  
Certainty Equivalent ◽  
Social Cost Of Carbon ◽  
Present Value ◽  
The Social ◽  
Wide Range

The "social cost of carbon" (SCC) is the present value of the stream of future damages from one additional unit of carbon emissions in a particular year. This paper develops a rapid assessment model for the SCC. The model includes the essential ingredients for calculating the SCC at the global scale and is designed to be transparent and easy to use and modify. Our goal is to provide a tool to help analysts and decision-makers quickly explore the implications of various modeling assumptions for the SCC. We use the model to conduct sensitivity analyses over some of the key input parameters, and we compare estimates of the SCC under certainty and uncertainty in a Monte Carlo analysis. We find that, due to the combined effects of uncertainty and risk aversion, the certainty-equivalent SCC can be substantially larger than the expected value of the SCC. In our Monte Carlo simulation, the certainty-equivalent SCC is more than four times larger than the expected value of the SCC, and we show that this result depends crucially on how the uncertain preference parameters are handled. We also compare the approximate present value of benefits estimated using the SCC to the exact value of compensating variation in the initial period for a wide range of hypothetical emission reduction policies.

scholarly journals Estimates of the social cost of carbon have not changed over time

2021 ◽  
Author(s):  
Richard Tol
Keyword(s):  
Climate Change ◽  
Stationary Distribution ◽  
Social Cost ◽  
Meta Analysis ◽  
Kernel Density ◽  
Social Cost Of Carbon ◽  
Almost Everywhere ◽  
The Social ◽  
Carbon Prices ◽  
Over Time

Abstract Some claim that as knowledge about climate change accumulates, the social cost of carbon increases. A meta-analysis of published estimates shows that this is not the case. Correcting for inflation and emission year and controlling for the discount rate, kernel density decomposition reveals a stationary distribution. Actual carbon prices are almost everywhere below the estimated social cost of carbon.

scholarly journals Fat Tails and the Social Cost of Carbon

2014 ◽  
Vol 104 (5) ◽  
pp. 544-546 ◽  
Author(s):  
Martin L. Weitzman
Keyword(s):  
Climate Change ◽  
Relative Risk ◽  
Risk Aversion ◽  
Strong Influence ◽  
Social Cost ◽  
Relative Risk Aversion ◽  
Fat Tails ◽  
Social Cost Of Carbon ◽  
The Social ◽  
Climate Damages

At high enough greenhouse gas concentrations, climate change might conceivably cause catastrophic damages with small but non-negligible probabilities. If the bad tail of climate damages is sufficiently fat, and if the coefficient of relative risk aversion is greater than one, the catastrophe-reducing insurance aspect of mitigation investments could in theory have a strong influence on raising the social cost of carbon. In this paper I exposit the influence of fat tails on climate change economics in a simple stark formulation focused on the social cost of carbon. I then attempt to place the basic underlying issues within a balanced perspective.

scholarly journals Climate-economy feedbacks, temperature variability, and the social cost of carbon

2020 ◽  
Author(s):  
Jarmo Kikstra ◽  
Paul Waidelich ◽  
James Rising ◽  
Dmitry Yumashev ◽  
Chris Hope ◽  
...  
Keyword(s):  
Climate Change ◽  
Social Cost ◽  
Climate Change Impacts ◽  
Climate Impacts ◽  
Temperature Variability ◽  
Policy Implications ◽  
Social Cost Of Carbon ◽  
Intergovernmental Panel ◽  
Country Level ◽  
The Social

<p>A key statistic describing climate change impacts is the “social cost of carbon” (SCC), the total market and non-market costs to society incurred by releasing a ton of CO<sub>2</sub>. Estimates of the SCC have risen in recent years, with improved understanding of the risk of climate change to various sectors, including agriculture [1], mortality [2], and economic growth [3].</p><p>The total risks of climate impacts also depend on the representation of human-climate feedbacks such as the effect of climate impacts on GDP growth and extremes (rather than a focus only on means), but this relationship has not been extensively studied [4-7]. In this paper, we update the widely used PAGE IAM to investigate how SCC distributions change with the inclusion of climate-economy feedbacks and temperature variability. The PAGE model has recently been improved with representations of permafrost thawing and surface albedo feedback, CMIP6 scenarios, and empirical market damage estimates [8]. We study how changes from PAGE09 to PAGE-ICE affected the SCC, increasing it up to 75%, with a SCC distribution with a mean around $300 for the central SSP2-4.5 scenario. Then we model the effects of different levels of the persistence of damages, for which the persistence parameter is shown to have enormous effects. Adding stochastic interannual regional temperature variations based on an analysis of observational temperature data [9] can increase the hazard rate of economic catastrophes changes the form of the distribution of SCC values. Both the effects of temperature variability and climate-economy feedbacks are region-dependent. Our results highlight the importance of feedbacks and extremes for the understanding of the expected value, distribution, and heterogeneity of climate impacts.</p><p> </p><p>[1] Moore, F. C., Baldos, U., Hertel, T., & Diaz, D. (2017). New science of climate change impacts on agriculture implies higher social cost of carbon. Nature communications, 8(1), 1607.</p><p>[2] Carleton, et al. (2018). Valuing the global mortality consequences of climate change accounting for adaptation costs and benefits.</p><p>[3] Ricke, K., Drouet, L., Caldeira, K., & Tavoni, M. (2018). Country-level social cost of carbon. Nature Climate Change, 8(10), 895.</p><p>[4] Burke, M., et al. (2016). Opportunities for advances in climate change economics. Science, 352(6283), 292–293. https://doi.org/10.1126/science.aad9634</p><p>[5] National Academies of Sciences Engineering and Medicine. (2017). Valuing climate damages: updating estimation of the social cost of carbon dioxide. National Academies Press.</p><p>[6] Stiglitz, J. E., et al.. (2017). Report of the high-level commission on carbon prices.</p><p>[7] Field, C. B., Barros, V., Stocker, T. F., & Dahe, Q. (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change (Vol. 9781107025). https://doi.org/10.1017/CBO9781139177245.009</p><p>[8] Yumashev, D., et al. (2019). Climate policy implications of nonlinear decline of Arctic land permafrost and other cryosphere elements. Nature Communications, 10(1). https://doi.org/10.1038/s41467-019-09863-x</p><p>[9] Brierley, C. M., Koch, A., Ilyas, M., Wennyk, N., & Kikstra, J. S. (2019, March 12). Half the world's population already experiences years 1.5°C warmer than preindustrial. https://doi.org/10.31223/osf.io/sbc3f</p>

scholarly journals The Economic Impacts of Climate Change: Evidence from Agricultural Output and Random Fluctuations in Weather

2007 ◽  
Vol 97 (1) ◽  
pp. 354-385 ◽  
Author(s):  
Olivier Deschênes ◽  
Michael Greenstone
Keyword(s):  
Climate Change ◽  
Economic Impact ◽  
Agricultural Land ◽  
Economic Impacts ◽  
Impact Of Climate Change ◽  
Positive Effects ◽  
Temperature And Precipitation ◽  
Random Fluctuations ◽  
Hedonic Approach ◽  
Impacts Of Climate Change

This paper measures the economic impact of climate change on US agricultural land by estimating the effect of random year-to-year variation in temperature and precipitation on agricultural profits. The preferred estimates indicate that climate change will increase annual profits by $1.3 billion in 2002 dollars (2002$) or 4 percent. This estimate is robust to numerous specification checks and relatively precise, so large negative or positive effects are unlikely. We also find the hedonic approach—which is the standard in the previous literature—to be unreliable because it produces estimates that are extremely sensitive to seemingly minor choices about control variables, sample, and weighting. (JEL L25, Q12, Q51, Q54)

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