Valuing the Greenland ice sheet and other complex geophysical phenomena
William A. Pizer
PNAS June 18, 2019 116 (25) 12134-12135
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Figure: Estimated 2015 social cost of carbon with and without GIS melt benefits. Data from table 2 and SI appendix, table J-2 of ref. 4.
For the last 40 y, economists have worked to put monetary values on environmental amenities to facilitate the cost–benefit analysis (CBA) of alternative policies (1⇓–3). The motivation is simple: Policy choices inevitably require trade-offs. Resources devoted to climate change mitigation are resources not spent on curing diseases, improving education, alleviating poverty, or providing for national defense, not to mention enjoying private comforts and consumption. It is natural to hold governments and public policies accountable for ensuring that these trade-offs make sense in a transparent way, which is the essence of CBA.
A key feature in CBA related to climate change mitigation is the social cost of carbon (SCC), the dollar value associated with avoided damages from each ton of reduced carbon dioxide emissions. The SCC multiplied by total tons of CO2 reduced by a given policy determines benefits; subtracting policy costs yields an estimate of net benefits. These net benefits can be compared across policies or even among various arenas of government activity to make choices and prioritize action.
In PNAS, Nordhaus (4) examines the effect of including Greenland ice sheet (GIS) melt in estimates of the SCC. This responds to the common-sense concern that a largely irreversible and complete melting of the GIS would raise mean sea level by 7 m and inundate many of the world’s population centers. It also responds directly to one of the recommendations in a recent consensus study report of the National Academy of Sciences, Engineering, and Medicine (recommendation 4-3 of ref. 5) that a sea-level rise (SLR) component be included in the SCC modeling. More generally, Nordhaus (4) demonstrates how complex geophysical phenomena can be integrated with an economic analysis. He does this by distilling the properties of GIS melt into a simple 2-equation model, which is then included in his Dynamic Integrated model of Climate Economy (DICE). This model already includes both the costs of mitigating climate change and the conventional (non-GIS) damages from global temperature change.
Nordhaus’s (4) methodological approach to integrating GIS melt into the SCC is a valuable guide for the economic analysis of other climate change issues and long-term environmental concerns more broadly. For example, there is debate over the temperature threshold that ultimately leads to GIS disintegration. There is further uncertainty about whether potential multiple stable equilibria exist, as well as the dynamics of moving between them. The author’s 2-equation model captures these features, allows him to match more complex GIS models and available evidence, and permits sensitivity analysis across the important geophysical uncertainties. That is, Nordhaus's implicit guidance is to construct a simple model that mimics the economically relevant features and available evidence from state-of-the-art models, and allows sensitivity analysis across significant uncertainties.
Nordhaus’s (4) quantitative result, perhaps surprisingly, finds an increase of at most 5% (and more typically <1%) in the estimated SCC value under a wide range of assumptions about GIS melt. That is, the direct consequences of including the estimated monetary damages from GIS melt in the SCC calculation is negligible.
What explains this small value? The potential damages from GIS melt are large but not existential. Nordhaus (4) assumes, based on Diaz and Keller’s study (6), that each meter of SLR reduces global income by 1%, so complete disintegration of the GIS implies a 7% loss. In the no-policy baseline, only half of this melt occurs over 2,000 y (see figure 5 of ref. 4). Meanwhile, conventional damages amount to a 12% loss of income in the baseline after 400 y (7). Mechanically, smaller damages that extend over more than a millennium further into the future simply do not matter. Put another way, while the noted effects of GIS melt are large, they pale in comparison with damage estimates from other categories of impacts. Such categories range from health and mortality to agricultural losses, productivity declines, and storm damage (8).
An important next step will be to extend this approach to the Antarctic Ice Sheet—which is nearly ten times larger and could raise mean sea level by nearly 60 meters (9). Other geophysical phenomena could also have larger effects. Indeed, another contribution of the paper by Nordhaus (4) is suggesting ways to filter what other geophysical phenomena will matter for the SCC. Damages will need to be similar in magnitude and timing to conventional climate damages (if not larger and faster).
Of course, the economic analysis and CBA applied to environmental amenities is but one input to policy making, and criticism of such efforts has been around nearly as long as the analysis itself (10⇓–12). Among the concerns is that we simply do not understand the interconnectedness of various outcomes and/or miss important effects. One way to work around the critique is to explore the cost of achieving a particular environmental outcome without regard to benefits of doing so.
How might we use the cost of an environmental target to make policy choices, absent benefit estimates? Ethical, political, precautionary, or other considerations, rather than benefit estimates, may argue for a particular environmental goal such as limiting GIS melt. By translating that goal into an aggregate dollar cost per ton CO2, interpreting that cost as an “implicit benefit,” and then applying that value widely to evaluate individual policies, disparate policies can be harmonized to reduce the cost of achieving the goal. This facilitates what is referred to as cost-effectiveness analysis and is precisely the approach taken in the United Kingdom to value CO2 emission reductions more broadly. They have established a “target-consistent” carbon value based on the estimated aggregate abatement cost necessary to meet their 2050 emission target of 80% below 1990 levels
For the last 40 y, economists have worked to put monetary values on environmental amenities to facilitate the cost–benefit analysis (CBA) of alternative policies (1⇓–3). The motivation is simple: Policy choices inevitably require trade-offs. Resources devoted to climate change mitigation are resources not spent on curing diseases, improving education, alleviating poverty, or providing for national defense, not to mention enjoying private comforts and consumption. It is natural to hold governments and public policies accountable for ensuring that these trade-offs make sense in a transparent way, which is the essence of CBA.
A key feature in CBA related to climate change mitigation is the social cost of carbon (SCC), the dollar value associated with avoided damages from each ton of reduced carbon dioxide emissions. The SCC multiplied by total tons of CO2 reduced by a given policy determines benefits; subtracting policy costs yields an estimate of net benefits. These net benefits can be compared across policies or even among various arenas of government activity to make choices and prioritize action.
In PNAS, Nordhaus (4) examines the effect of including Greenland ice sheet (GIS) melt in estimates of the SCC. This responds to the common-sense concern that a largely irreversible and complete melting of the GIS would raise mean sea level by 7 m and inundate many of the world’s population centers. It also responds directly to one of the recommendations in a recent consensus study report of the National Academy of Sciences, Engineering, and Medicine (recommendation 4-3 of ref. 5) that a sea-level rise (SLR) component be included in the SCC modeling. More generally, Nordhaus (4) demonstrates how complex geophysical phenomena can be integrated with an economic analysis. He does this by distilling the properties of GIS melt into a simple 2-equation model, which is then included in his Dynamic Integrated model of Climate Economy (DICE). This model already includes both the costs of mitigating climate change and the conventional (non-GIS) damages from global temperature change.
Nordhaus’s (4) methodological approach to integrating GIS melt into the SCC is a valuable guide for the economic analysis of other climate change issues and long-term environmental concerns more broadly. For example, there is debate over the temperature threshold that ultimately leads to GIS disintegration. There is further uncertainty about whether potential multiple stable equilibria exist, as well as the dynamics of moving between them. The author’s 2-equation model captures these features, allows him to match more complex GIS models and available evidence, and permits sensitivity analysis across the important geophysical uncertainties. That is, Nordhaus's implicit guidance is to construct a simple model that mimics the economically relevant features and available evidence from state-of-the-art models, and allows sensitivity analysis across significant uncertainties.
Nordhaus’s (4) quantitative result, perhaps surprisingly, finds an increase of at most 5% (and more typically <1%) in the estimated SCC value under a wide range of assumptions about GIS melt. That is, the direct consequences of including the estimated monetary damages from GIS melt in the SCC calculation is negligible.
What explains this small value? The potential damages from GIS melt are large but not existential. Nordhaus (4) assumes, based on Diaz and Keller’s study (6), that each meter of SLR reduces global income by 1%, so complete disintegration of the GIS implies a 7% loss. In the no-policy baseline, only half of this melt occurs over 2,000 y (see figure 5 of ref. 4). Meanwhile, conventional damages amount to a 12% loss of income in the baseline after 400 y (7). Mechanically, smaller damages that extend over more than a millennium further into the future simply do not matter. Put another way, while the noted effects of GIS melt are large, they pale in comparison with damage estimates from other categories of impacts. Such categories range from health and mortality to agricultural losses, productivity declines, and storm damage (8).
An important next step will be to extend this approach to the Antarctic Ice Sheet—which is nearly ten times larger and could raise mean sea level by nearly 60 meters (9). Other geophysical phenomena could also have larger effects. Indeed, another contribution of the paper by Nordhaus (4) is suggesting ways to filter what other geophysical phenomena will matter for the SCC. Damages will need to be similar in magnitude and timing to conventional climate damages (if not larger and faster).
Of course, the economic analysis and CBA applied to environmental amenities is but one input to policy making, and criticism of such efforts has been around nearly as long as the analysis itself (10⇓–12). Among the concerns is that we simply do not understand the interconnectedness of various outcomes and/or miss important effects. One way to work around the critique is to explore the cost of achieving a particular environmental outcome without regard to benefits of doing so.
How might we use the cost of an environmental target to make policy choices, absent benefit estimates? Ethical, political, precautionary, or other considerations, rather than benefit estimates, may argue for a particular environmental goal such as limiting GIS melt. By translating that goal into an aggregate dollar cost per ton CO2, interpreting that cost as an “implicit benefit,” and then applying that value widely to evaluate individual policies, disparate policies can be harmonized to reduce the cost of achieving the goal. This facilitates what is referred to as cost-effectiveness analysis and is precisely the approach taken in the United Kingdom to value CO2 emission reductions more broadly. They have established a “target-consistent” carbon value based on the estimated aggregate abatement cost necessary to meet their 2050 emission target of 80% below 1990 levels
For the last 40 y, economists have worked to put monetary values on environmental amenities to facilitate the cost–benefit analysis (CBA) of alternative policies (1⇓–3). The motivation is simple: Policy choices inevitably require trade-offs. Resources devoted to climate change mitigation are resources not spent on curing diseases, improving education, alleviating poverty, or providing for national defense, not to mention enjoying private comforts and consumption. It is natural to hold governments and public policies accountable for ensuring that these trade-offs make sense in a transparent way, which is the essence of CBA.
A key feature in CBA related to climate change mitigation is the social cost of carbon (SCC), the dollar value associated with avoided damages from each ton of reduced carbon dioxide emissions. The SCC multiplied by total tons of CO2 reduced by a given policy determines benefits; subtracting policy costs yields an estimate of net benefits. These net benefits can be compared across policies or even among various arenas of government activity to make choices and prioritize action.
In PNAS, Nordhaus (4) examines the effect of including Greenland ice sheet (GIS) melt in estimates of the SCC. This responds to the common-sense concern that a largely irreversible and complete melting of the GIS would raise mean sea level by 7 m and inundate many of the world’s population centers. It also responds directly to one of the recommendations in a recent consensus study report of the National Academy of Sciences, Engineering, and Medicine (recommendation 4-3 of ref. 5) that a sea-level rise (SLR) component be included in the SCC modeling. More generally, Nordhaus (4) demonstrates how complex geophysical phenomena can be integrated with an economic analysis. He does this by distilling the properties of GIS melt into a simple 2-equation model, which is then included in his Dynamic Integrated model of Climate Economy (DICE). This model already includes both the costs of mitigating climate change and the conventional (non-GIS) damages from global temperature change.
Nordhaus’s (4) methodological approach to integrating GIS melt into the SCC is a valuable guide for the economic analysis of other climate change issues and long-term environmental concerns more broadly. For example, there is debate over the temperature threshold that ultimately leads to GIS disintegration. There is further uncertainty about whether potential multiple stable equilibria exist, as well as the dynamics of moving between them. The author’s 2-equation model captures these features, allows him to match more complex GIS models and available evidence, and permits sensitivity analysis across the important geophysical uncertainties. That is, Nordhaus's implicit guidance is to construct a simple model that mimics the economically relevant features and available evidence from state-of-the-art models, and allows sensitivity analysis across significant uncertainties.
Nordhaus’s (4) quantitative result, perhaps surprisingly, finds an increase of at most 5% (and more typically <1%) in the estimated SCC value under a wide range of assumptions about GIS melt. That is, the direct consequences of including the estimated monetary damages from GIS melt in the SCC calculation is negligible.
What explains this small value? The potential damages from GIS melt are large but not existential. Nordhaus (4) assumes, based on Diaz and Keller’s study (6), that each meter of SLR reduces global income by 1%, so complete disintegration of the GIS implies a 7% loss. In the no-policy baseline, only half of this melt occurs over 2,000 y (see figure 5 of ref. 4). Meanwhile, conventional damages amount to a 12% loss of income in the baseline after 400 y (7). Mechanically, smaller damages that extend over more than a millennium further into the future simply do not matter. Put another way, while the noted effects of GIS melt are large, they pale in comparison with damage estimates from other categories of impacts. Such categories range from health and mortality to agricultural losses, productivity declines, and storm damage (8).
An important next step will be to extend this approach to the Antarctic Ice Sheet—which is nearly ten times larger and could raise mean sea level by nearly 60 meters (9). Other geophysical phenomena could also have larger effects. Indeed, another contribution of the paper by Nordhaus (4) is suggesting ways to filter what other geophysical phenomena will matter for the SCC. Damages will need to be similar in magnitude and timing to conventional climate damages (if not larger and faster).
Of course, the economic analysis and CBA applied to environmental amenities is but one input to policy making, and criticism of such efforts has been around nearly as long as the analysis itself (10⇓–12). Among the concerns is that we simply do not understand the interconnectedness of various outcomes and/or miss important effects. One way to work around the critique is to explore the cost of achieving a particular environmental outcome without regard to benefits of doing so.
How might we use the cost of an environmental target to make policy choices, absent benefit estimates? Ethical, political, precautionary, or other considerations, rather than benefit estimates, may argue for a particular environmental goal such as limiting GIS melt. By translating that goal into an aggregate dollar cost per ton CO2, interpreting that cost as an “implicit benefit,” and then applying that value widely to evaluate individual policies, disparate policies can be harmonized to reduce the cost of achieving the goal. This facilitates what is referred to as cost-effectiveness analysis and is precisely the approach taken in the United Kingdom to value CO2 emission reductions more broadly. They have established a “target-consistent” carbon value based on the estimated aggregate abatement cost necessary to meet their 2050 emission target of 80% below 1990 levels
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