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Integrated assessment of climate change: state of the literature

Published online by Cambridge University Press:  27 May 2015

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Abstract:

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This paper reviews applications of benefit-cost analysis (BCA) in climate policy assessment at the US national and global scales. Two different but related major application types are addressed. First there are global-scale analyses that focus on calculating optimal global carbon emissions trajectories and carbon prices that maximize global welfare. The second application is the use of the same tools to compute the social cost of carbon (SCC) for use in US regulatory processes. The SCC is defined as the climate damages attributable to an increase of one metric ton of carbon dioxide emissions above a baseline emissions trajectory that assumes no new climate policies. The paper describes the three main quantitative models that have been used in the optimal carbon policy and SCC calculations and then summarizes the range of results that have been produced using them. The results span an extremely broad range (up to an order of magnitude) across modeling platforms as well as across the plausible ranges of input assumptions to a single model. This broad range of results sets the stage for a discussion of the five key challenges that face BCA practitioners participating in the national and global climate change policy analysis arenas: (1) including the possibility of catastrophic outcomes; (2) factoring in equity and income distribution considerations; (3) addressing intertemporal discounting and intergenerational equity; (4) projecting baseline demographics, technological change, and policies inside and outside the energy sector; and (5) characterizing the full set of uncertainties to be dealt with and designing a decision-making process that updates and adapts new scientific and economic information into that process in a timely and productive manner. The paper closes by describing how the BCA models have been useful in climate policy discussions to date despite the uncertainties that pervade the results that have been produced.

Type
Research Article
Copyright
Copyright © Society for Benefit-Cost Analysis 2014

References

Ackerman, F., & Stanton, E. A. (2010). The social cost of carbon: A report for the economics for equity and the environment network. Sommerville, MA: Stockholm Environment Institute – U.S. Center. Retrieved from http://www.climate-economics.org/papers/SocialCostOfCarbon_SEI_20100401.pdf.Google Scholar
Ackerman, F., & Stanton, E. (2012). Climate risks and carbon prices: Revising the social cost of carbon. Economics: The Open-Access, Open-Assessment E-Journal, 6 (2012-10), 125. Retrieved from http://dx.doi.org/10.5018/economics-ejournal.ja.2012-10.Google Scholar
Adler, M. (2012). Well-being and fair distribution: Beyond cost-benefit analysis. New York, NY: Oxford University Press.Google Scholar
Anthoff, D., & Tol, R. S. J. (2010). On international equity weights and national decision making on climate change. Journal of Environmental Economics and Management, 60(1), 1420.Google Scholar
Anthoff, D., & Tol, R. S. J. (2013). The uncertainty about the social cost of carbon: A decomposition analysis using FUND. Climatic Change, 117(3), 515530.Google Scholar
Arrow, K. J., Cline, W. R., Maler, K.-G., Munasinghe, M., Squitieri, R., & Stiglitz, J. E. (1995). Intertemporal equity, discounting, and economic efficiency. In Bruce, J., Lee, H. & Haites, E. (Eds.), Climate Change 1995: Economic and social dimensions of climate change, contribution of Working Group III to the Second Assessment Report of the Intergovernmental Panel on Climate Change (pp. 125144). Cambridge, UK: Cambridge University Press. Retrieved from http://www.econ.yale.edu/~nordhaus/Resources/22073-Chap4-Intertemporal%20Equity.pdf.Google Scholar
Arrow, K., Cropper, M., Gollier, C., Groom, B., Heal, G., Newell, R., … Weitzman, M. (2013). Determining benefits and costs for future generations. Science, 341, 349350.Google Scholar
Browne, E. A. (1996). Modeling expert dependency in decision analysis. Ph.D. Dissertation, Department of Engineering Economic Systems, Stanford University.Google Scholar
Cass, D. (1965). Optimum growth in an aggregative model of capital accumulation. Review of Economic Studies, 32(3), 233240.CrossRefGoogle Scholar
Clemen, R. (1984). Modeling dependent information: A Bayesian approach. Ph.D. Dissertation, Indiana University.Google Scholar
Clemen, R. (1985). Extraneous expert information. Journal of Forecasting, 4(4), 329348.Google Scholar
Clemen, R. (1986). Calibration and the aggregation of probabilities. Management Science, 32(3), 312314.Google Scholar
Clemen, R. (1989). Combining forecasts: A review and annotated bibliography. International Journal of Forecasting, 5(4), 559583.CrossRefGoogle Scholar
Clemen, R., & Winkler, R. (1985). Limits for the precision and value of information from dependent sources. Operations Research, 33(2), 427442. doi:10.1287/opre.33.2.427.Google Scholar
Clemen, R., & Winkler, R. (1986). Combining economic forecasts. Journal of Business & Economic Statistics, 4(1), 39. doi:10.2307/1391385.Google Scholar
Clemen, R., & Winkler, R. (1987). Calibrating and combining precipitation probability forecasts. Probability and Bayesian Statistics, 97110. New York: Plenum.Google Scholar
Clemen, R., & Winkler, R. L. (1992). Sensitivity of weights in combining forecasts. Operations Research, 40(3), 609614.Google Scholar
Clemen, R., & Winkler, R. (1993). Aggregating point estimates: A flexible modeling approach. Management Science, 39(4), Sol-SIS.CrossRefGoogle Scholar
Cline, W. (1992). The economics of global warming. Washington, D.C.: Institute of International Economics.Google Scholar
Domike, J., & Zacoroli, A. (Eds.). (2013). The Clean Air Act handbook (3rd ed.). Chicago: American Bar Association.Google Scholar
Gayer, T., & Viscusi, W. (2014). Determining the proper scope of climate change benefits. Working Paper, Brookings Institution.CrossRefGoogle Scholar
Greenstone, M., Kopits, E., & Wolverton, A. (2011). Estimating the social cost of carbon for use in U.S. federal rulemakings: A summary and interpretation. NBER Working Paper 16913.Google Scholar
Greenstone, M., Kopits, E., & Wolverton, A. (2013). Developing a social cost of carbon for US regulatory analysis: A methodology and interpretation. Review of Environmental Economics and Policy, 7(1), 2346.Google Scholar
Hope, C. (2006). The marginal impact of CO2 from PAGE2002: An integrated assessment model incorporating the IPCC’s five reasons for concern. Integrated Assessment Journal, 6(1), 1956.Google Scholar
Hope, C. (2011). The social cost of CO2 from the PAGE09 model. Cambridge, UK: Judge Business School Working Paper.CrossRefGoogle Scholar
Howard, R. A. (1984). Risk preference (paper 34). In: Howard, R. A. & Matheson, J. E. (Eds.), The principles and applications of decision analysis (Vol. II). Menlo Park, CA: Strategic Decisions Group.Google Scholar
Integrated Assessment Modeling Consortium (IAMC). 2014. Last accessed November 6, 2014 @ http://www.globalchange.umd.edu/iamc/.Google Scholar
Interagency Working Group (IWG). (2010). Technical support document: Social cost of carbon for regulatory impact analysis under Executive Order 12866 (p. 51). Washington, DC: Interagency Working Group on Social Cost of Carbon, United States Government. Retrieved from http://www.epa.gov/oms/climate/regulations/scc-tsd.pdf.Google Scholar
Interagency Working Group (IWG). (2013). Technical support document: Technical update of the social cost of carbon for regulatory impact analysis under Executive Order 12866 (p. 21). Washington, DC: Interagency Working Group on Social Cost of Carbon, United States Government. Retrieved from http://www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_update.pdf.Google Scholar
IPCC. (2012). Managing the risks of extreme events and disasters to advance climate change adaptation. In Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. L., … Midgley, P. M. (Eds.), A special report of the Intergovernmental Panel on Climate Change. Cambridge, UK; New York, NY: Cambridge University Press.Google Scholar
IPCC. (2013). Climate change 2013: The physical science basis. In Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., … Midgley, P. M. (Eds.), Contribution of Working Group I to the Intergovernmental Panel on Climate Change Fifth Assessment Report. Cambridge, UK and New York, NY: Cambridge University Press. Retrieved from http://www.ipcc.ch/report/ar5/wg1/#.Ukn99hCBm71.Google Scholar
IPCC. (2014a). Climate change 2014: Impacts, adaptation, and vulnerability. In Field, C. B., Barros, V. R., Dokken, D. J., Mach, K. J., Mastrandrea, M. D., Bilir, T. E., … White, L. L. (Eds.), Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY: Cambridge University Press.Google Scholar
IPCC. (2014b). Climate change 2014: Mitigation of climate change. In Edenhofer, O., Pichs-Madruga, R., Sokona, Y., Farahani, E., Kadner, S., Seyboth, K., … Minx, J. C. (Eds.), Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY: Cambridge University Press.Google Scholar
Johnson, L., & Hope, C. (2012). The social cost of carbon in U.S. regulatory impact analyses: An introduction and critique. Journal of Environmental Studies and Sciences, 2(3), 205221.Google Scholar
Jouini, M. (1992). Combining experts’ opinions: A nonparametric approach using copulas. Ph.D. Dissertation, Dept. of Decision Sciences, University of Oregon.Google Scholar
Jouini, M., & Clemen, R. (1994). Copula models for aggregating expert opinions. Working Paper, College of Business Administration, University of Oregon.Google Scholar
Koopmans, T. C. (1965). On the concept of optimal economic growth. Academiae Scientiarum Scripta Varia, 28(1), 175.Google Scholar
Lempert, R. J. (2014). Embedding (some) benefit-cost concepts into decision support processes with deep uncertainty. The Journal of Benefit-Cost Analysis, 5(3), 487514.Google Scholar
Lenton, T., Held, H., Kriegler, E., Hall, J.,.Lucht, W., Rahmstorf, S., & Schellenhuber, J. (2008). Tipping elements in the Earth’s climate system. Nature, 105(6), 17861793.Google Scholar
Li, J., Mullan, M., & Helgeson J.r. (2014). Improving the practice of economic analysis of climate change adaptation. The Journal of Benefit-Cost Analysis, 5(3), 445467.Google Scholar
Lind, R. (1995). Intergenerational equity, discounting, and the role of cost benefit analysis in evaluating global climate policy. Energy Policy 23, 379389.CrossRefGoogle Scholar
Lind, R., Ruskin, F. (Ends). (1982). Discounting for time and risk in energy policy. Washington, DC.: Resources for the Future.Google Scholar
Marten, A., & Newbold, S. (2012). Estimating the social cost of non-CO2 GHG emissions: Methane and nitrous oxide. Energy Policy, 5, 957972.Google Scholar
Masters, G., & Ela, W. (2007). Introduction to environmental engineering and science (3rd Edition). New York, NY: Prentice Hall.Google Scholar
Meinshausen, M., Raper, S. C. B., & Wigley, T. M. L. (2011). Emulating coupled atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 - Part 1: Model description and calibration. Atmospheric Chemistry and Physics, 11(4), 14171456. doi:10.5194/acp-11-1417-2011.Google Scholar
Morgan, G., & Keith, D. (1995). Subjective judgments by climate experts. Environmental Science & Technology, 29, A468A476.Google Scholar
Morin, J., & Orsini, A. (Eds.) (2015). The essential guide to global environmental governance. New York, NY: Routledge.Google Scholar
Morris, P. A. (1971). Bayesian expert resolution. Ph.D. Dissertation, Dept. of Engineering-Economic Systems, Stanford University.Google Scholar
Morris, P. A. (1974). Decision analysis expert use. Management Science, 20(9), 12331241.Google Scholar
Morris, P. A. (1977). Combining expert judgments: A bayesian approach. Management Science, 23(7), 679693.Google Scholar
Morris, P. (1983). An axiomatic approach to expert resolution. Management Science, 29(1), 2432.Google Scholar
Morris, P. (1986). Observations of expert aggregation. Management Science, 32(3), 321328.Google Scholar
National Research Council, Committee on Abrupt Climate Change. (2002). Abrupt climate change: Inevitable surprises. Washington, DC: National Academy Press.Google Scholar
Neumann, J. E., & Strzepek, K. (2014). State of the literature on the economic impacts of climate change in the United States. The Journal of Benefit-Cost Analysis, 5(3), 411443.Google Scholar
Nordhaus, W. D. (1992). An optimal transition path for controlling greenhouse gases. Science, 258(5086), 13151319.Google Scholar
Nordhaus, W. D. (1994a). Managing the global commons: the economics of climate change. Cambridge, MA: MIT Press.Google Scholar
Nordhaus, W. D. (1994b). Expert opinion on climatic change. American Scientist, 82, 4551.Google Scholar
Nordhaus, W. D. (2007). A review of the stern review on the economics of climate change. Journal of Economic Literature 45(3), 686702.Google Scholar
Nordhaus, W. D. (2008). A question of balance: Weighing the options on global warming policies. New Haven, CT: Yale University Press.Google Scholar
Nordhaus, W. D. (2010). Economic aspects of global warming in a post-Copenhagen environment. Proceedings of the U.S. National Academy of Sciences, 107(26), 1172111726.Google Scholar
Nordhaus, W. D. (2013). Integrated economic and climate modeling. In Dixon, P. B. & Jorgenson, D. W. (Eds.), Handbook of Computable General Equilibrium Modeling. Amsterdam, The Netherlands: North Holland.Google Scholar
Nordhaus, W. D. (2014). Estimates of the social cost of carbon: concepts and results from the DICE-2013R model and alternative approaches. Journal of the Association of Environmental and Resource Economists, 1(1/2), 273312.Google Scholar
Nordhaus, W., & Yang, Z. (1996). A regional dynamic general-equilibrium model of alternative climate-change strategies. American Economic Review, 86(4), 741765.Google Scholar
Nordhaus, W., & Boyer, J. (2000). Warming the world: Economic modeling of global warming. Cambridge, MA: MIT Press.Google Scholar
Nordhaus, W., & Sztorc, P. (2013). DICE 2013R: Introduction and user’s manual. Retrieved from http://www.econ.yale.edu/~nordhaus/homepage/documents/DICE_Manual_100413r1.pdf.Google Scholar
OMB. (2003). Office of Management and Budget. Circular A-4. Retrieved from http://www.whitehouse.gov/omb/circulars_a004_a-4.Google Scholar
Pindyck, R. (2013). Climate change policy: What do the models tell us? Journal of Economic Literature, 51(3), 860872.Google Scholar
Portney, P., & Weyant, J. (Eds.). (1999). Discounting and intergenerational equity. Washington, DC: Resources for the Future Press.Google Scholar
Pratt, J., Raiffa, H., & Schlaifer, R. (1995). Introduction to statistical decision theory. Cambridge, MA: Washington, DC.Google Scholar
Raiffa, H. (1968). DECISION ANALYSIS: Introductory Lectures on Choices under Uncertainty. New York, NY: Addison-Wesley.Google Scholar
Ramsey, F. (1928). A mathematical theory of saving. Economic Journal, 38, 543559.CrossRefGoogle Scholar
Reagan, R. (1981). Federal regulation. Presidential Executive Order 12291. Signed: February 17, Federal Register page and date: 46 FR 13193; February 19.Google Scholar
Rose, S., Turner, D., Blanford, G., Bistline, J., de la Chesnaye, F., & Wilson, T. (2014). Understanding the social cost of carbon: A technical assessment. Palo Alto, CA: Electric Power Research Institute, Report #3002004657.Google Scholar
Schaeffer, M., Gohar, L., Kriegler, E., Lowe, J., Riahi, K., & van Vuuren, D. (2013). Mid- and long-term climate projections for fragmented and delayed-action scenarios. Technological Forecasting and Social Change. doi:10.1016/j.techfore.2013.09.013.Google Scholar
Stern, N. (2007). The economics of climate change: The Stern review. Cambridge, UK: Cambridge University Press.Google Scholar
Stern, N. (2008). The economics of climate change. American Economic Review, 98(2), 137.Google Scholar
Stern, N. (2013). The structure of economic modeling of the potential impacts of climate change: Grafting gross underestimation of risk onto already narrow science models. Journal of Economic Literature, 51(3), 838859.Google Scholar
Tol, R. (2008). The social cost of carbon: Trends, outliers and catastrophes, economics. The Open-Access, Open-Assessment E-Journal, 2(25), 122.Google Scholar
Tol, R. (2009). The economic impact of climate change. Journal of Economic Perspectives, 23(2), 2951.Google Scholar
Toman, M. (2014). The need for multiple types of information to inform climate change assessment. The Journal of Benefit-Cost Analysis, 5(3), 469485.Google Scholar
van Vuuren, D., Lowe, J., Stehfest, E., Gohar, L.Hof, A., Hope, C., … Plattner, G. K. (2011). How well do integrated assessment models simulate climate change? Climatic Change, 104(2011), 255285.Google Scholar
Washington, W. & Parkinson, C. (2005). An introduction to three-dimensional climate modeling (2nd ed.). Sausalito, CA: University Scientific Books.Google Scholar
Weitzman, M. (2009). On modeling and interpreting the economics of catastrophic climate change. The Review of Economics and Statistics, 91(1), 119.Google Scholar
Weitzman, M. (2013). Tail-hedge discounting and the social cost of carbon. Journal of Economic Literature, 51(3), 873882.Google Scholar
Weyant, J. (2001). Economic models: How they work and why their results differ. In Claussen, E. (Ed.), Climate Change: Science, Strategies and Solutions. The Pew Center on Global Climate Change. Boston, MA: Brill Academic Publishers Inc.Google Scholar
Wolverton, A., Kopits, E., Moore, C., Marten, A., Newbold, S., & Griffiths, C. (2012). The social cost of carbon: Valuing carbon reductions in policy analysis. In Parry, I., Keen, M., de Mooij, R. (Eds.), Fiscal policy to mitigate climate change: A guide for policymakers. Washington, DC: International Monetary Fund.Google Scholar
Zhimin, L., & Nordhaus, W. (2013). The social cost of carbon: Methods and a survey of estimates. Berkeley, CA: University of California.Google Scholar