Challenges for Cost-Benefit Analysis in Supporting and Analyzing the Paris UNFCCC Agreement
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1 Challenges for Cost-Benefit Analysis in Supporting and Analyzing the Paris UNFCCC Agreement Third Annual Campus Sustainability Conference Hartford, CT April 7, 2016 Gary Yohe Wesleyan University, IPCC, and NCA2014
2 The International Context from the United Nations Framework Convention on Climate Change (the UNFCCC) - Original and Approved Language Article 2: stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system. Article 4: The developed country Parties and other developed Parties included in Annex II shall also assist the developing country Parties that are particularly vulnerable to the adverse effects of climate change in meeting costs of adaptation to those adverse effects.
3 Thus the Two Thrusts in Approach - Before and AFTER Paris Countries should commit to mitigation targets and shall, to the extent possible, underwrite an Adaptation Fund for the most vulnerable. Both reflect the underlying advice from the IPCC (Synthesis Report, AR4, 2007, pg 22) [my emphasis in italics and colors]: Responding to climate change involves an iterative risk management process that includes both adaptation and mitigation and takes into account climate change damages, co-benefits, sustainability, equity, and attitudes to risk. To understand the color code: Green highlights critical language. The red text indicates context. The blue text highlights challenges for C-B derived from the red.
4 General Issues for Cost Benefit Analysis, Climate Change, and Understanding the Paris Accord Uncertainty (sometimes enormous uncertainty) Science uncertainties Causal uncertainties (two stage connections of attribution), especially given compounding factors Social science uncertainties Human responses (decision making) uncertainties Economic valuation challenges Time and discounting factors Pure rate of time preference Alternative discounting procedures Government rules Relative aversion to inequality Weighting Cross country (within community) valuation comparisons Relative aversion to risk (relative risk aversion parameter)
5 Issues for Cost Benefit Analysis and Climate Change Short Term Adaptation with Short Term Iterative Adjustments under Article 4 of the UNFCCC and the Paris Accord Uncertainty (sometimes enormous uncertainty) Science uncertainties Causal uncertainties (two stage connections of attribution), especially given compounding factors Social science uncertainties Human responses (decision making) uncertainties Economic valuation challenges and omissions Time and discounting factors (sensitive to value judgements*) Pure rate of time preference* Alternative discounting rules (e.g., hyperbolic, recognizing uncertainty, etc *) Government rules or complementary versus substitutive investment (Arrow and Lind) Relative aversion to inequality* Weighting* (Qualitative recognition of distributional impacts) Cross country down to within community comparisons* Relative aversion to risk (relative risk aversion parameter)* Internal rates of return for investments To understand the color code: Green highlights critical language. The red text indicates context. The blue text highlights challenges for C-B derived from the red.
6 Issues for Cost Benefit Analysis and CC Mitigation with Long Iterative Adjustments in the Medium Term under Article 2 of the UNFCCC and the Paris Accord Uncertainty (sometimes enormous uncertainty) Science uncertainties, including valuation of non-market goods and services Causal uncertainties (two stage connections of attribution), especially given compounding factors Social science uncertainties Human responses (adaptation and mitigation decision making) uncertainties Economic valuations and omissions Time and discounting factors Pure rate of time preference* Alternative discounting rules (e.g., hyperbolic, recognizing uncertainty, etc ) Relative aversion to inequality Weighting (marginal utility based?) (Qualitative recognition of distributional impacts) Cross country (within community) valuation comparisons Relative aversion to risk (relative risk aversion parameter*) Ramsey rule for optimal saving and investment* Internal rates of return over the very long term* To understand the color code: Green highlights critical language. The red text indicates context. The blue text highlights challenges for C-B derived from the red.
7 History of C-B on Mitigation Nordhaus, AER, 1991 We now know that responding to climate change is not a simple dynamic optimization problem. We now know that the benefit side of a C-B approach is at best incomplete and perhaps at worst misleading (from the scientific uncertainties and different valuation perspectives) You can get any answer you want. Hence the essential need for adopting an iterative risk management approach Paris is the FIRST step for BOTH mitigation and adaptation C-B still provides some context, but it is too challenged to be sufficient to support policy decisions on its own. But then, from where did the Paris targets and programs and agreements emerge? The key to understanding Paris: Iterative risk management against acceptable levels or risk reflects a negotiated consensus of a collective, but qualitative, social values.
8 Our Limiting Choices Matter
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11 Global Coverage of Impacts to Human, Biological, and Physical Systems
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13 Figure 1: The enhanced burning embers diagram, providing a global perspective on climate-related risks. Levels of risk associated with 5 different reasons for concern are illustrated for increasing global mean temperature and are the same as those presented in the IPCC Working Group II report. Icons indicate selected risks that played an important role in locating transitions between levels of risks. Colored dots indicate overarching key risk categories that were considered in the assessment for each RFC (see Table 1). Confidence in the judgments of risk transitions is indicated as provided in ref. 39. For example, RFC1 is underpinned by overarching key risks i, vii, and viii from Table 1; there is medium confidence in the location of the transition from Undetectable to Moderate risk, which is informed by impacts to coral reef, Arctic and mountain systems; and there is high confidence in the location of the transition from High to Very High risk, which is informed by impacts to coral reef and Arctic systems as well as to species associated with unique and threatened systems.
14 Economics: The Open-Access, Open-Assessment E-Journal 5 Figure 1: The Kernel Estimate of the Probability Density Function of the Social Cost of Carbon a Gauss, CoV Gauss, SD Fisher-Tippett % 1% 3% all all peer gray < >2001 all a Top left: alternative distributional assumptions; top right: sample split according to pure rate of time preference; bottom left: sample split according to review; bottom right: sample split according to age of study. The Fisher-Tippett distribution is used throughout (except top left). the economic estimates of the impact of climate change have increased since In their words (p. 781): There is some evidence that initial new market benefits from climate change will peak at a lower magnitude and sooner than was assumed for the
15 Adapting in the Long-term: A Risk Management Approach
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17 Immediate References Slides 8 through 10: Mechanics of stabilization and impacts (the NRC Report of the Committee on Stabilization, 2010). Slide 11: Distribution of detected and attributed impacts (Chapter 18 of the Contribution of Working Group II to the Fifth Assessment Report of the IPCC (AR5), 2014). Slides 12 & 13: Reasons for Concern (Chapter 19 of the Contribution of Working Group II to the AR5, 2014) Slide 14: Estimates of the social cost of carbon ($/tonne of CO2 from Tol, 2008). Slide 15: Iterative adaptation (the Adaptation Panel of America s Climate Choices, NRC, 2011, and the US Third National Climate Assessment, 2014). Slides 16: Analysis of the effect of the Paris Accord (Fawcett, et al, Science, December 4, 2015).
18 The Application of Iterative Risk Management The Paris Accord We now know that responding to climate change is not a simple dynamic optimization problem. We now know that the benefit side of a C-B approach is at best incomplete and perhaps at worst misleading (from the scientific uncertainties and different valuation perspectives) You can get any answer you want. Hence, the IPCC and the UNFCCC have appropriately agreed to an essential need for adopting an iterative risk management approach Paris is the FIRST step for BOTH mitigation and adaptation C-B still provides some context about context, but C-B analysis is too challenged to be sufficient to support policy decisions on its own. The key to understanding Paris: Iterative risk management against acceptable levels or risk reflects a negotiated consensus of a collective, but qualitative, social values.
19 Selected Additional References More trouble for cost-benefit analysis GW Yohe - Climatic Change, Springer Poor cost-benefit analysis. It has been the target of so many recent critiques, especially in its application to the mitigation side of the climate issue, that it can hardly stand. Its detractors point to a series of questions that hammer directly at its very foundations. Even if we knew... Infinite uncertainty, forgotten feedbacks, and cost-benefit analysis of climate policy RSJ Tol, GW Yohe - Climatic Change, Springer Tol (2003) questioned the applicability of expected cost-benefit analysis to global mitigation policy when he found evidence that the uncertainty surrounding estimates of the marginal damage of climate change could be infinite even if total damages were finite.... Representing dynamic uncertainty in climate policy deliberations GW Yohe - AMBIO: A Journal of the Human Environment, 2006 BioOne This article highlights three sources of concern about the way that uncertainty in our understanding of the climate system is portrayed to decisionmakers. These concerns include a continued reliance on the cost benefit paradigm to organize their thoughts, the... Adopting a risk based approach G Yohe, R Leichenko - Annals of the New York Academy of Science, 2010 A significant message accompanying the call for greenhouse gas mitigation actions from the Intergovernmental Panel on Climate Change (IPCC) 2007 Fourth Assessment Report is the increasing need to identify a decision framework for climate change that encompasses... Risk assessment and risk management for infrastructure planning and investment G Yohe Bridge, Fall 2014 Greenhouse-gas concentrations reflect on 50 percent of the corresponding equilibrium warming, near-term decisions to mitigate climate change modestly (or not at all) may actually commit the planet to sudden, irreversible changes by the end of the century
20 A Few More References To slow or not to slow: the economics of the greenhouse effect Nordhaus, WD. The Economic Journal, 1991 Over the last decade, scientists have studied extensively the greenhouse effect, which holds that the accumulation of carbon dioxide (CO2) and other greenhouse gases (GHGs) is expected to produce global warming and other significant climatic changes over the nex Uncertainty and the evaluation of public investment decisions Arrow, KJ and RC Lind, American Economic Review, ideas.repec.org The complementarity of public and private capital and the optimal rate of return to government investment Ogura S and G Yohe, The Quarterly Journal of Economics, 1977 The impacts of various imperfections in the capital market on the optimal return to government investment have been the subjects of intense investigation in the recent literature. The distortion caused by corporate profits taxation has, for example, been extensively studied by... The social cost of carbon: trends, outliers and catastrophes R.S.Tol, estimates of the social cost of carbon are included in a meta-analysis. The results confirm that a lower discount rate implies a higher estimate; and that higher estimates are found in the gray literature. It is also found that there is a downward trend in the... Risk management and climate change Kunreuther H, Heal, G, Allen, M, Edenhofer, O, Field, C, and Yohe, G. This Perspective highlights the value of robust decision-making tools designed for situations such as evaluating climate policies where consensus on probability distributions is not available and stakeholders differ in their degrees of risk tolerance.
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