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Part II - Some Widely Used Analysis Tools and Topics

Published online by Cambridge University Press:  24 August 2017

M. Granger Morgan
Affiliation:
Carnegie Mellon University, Pennsylvania
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Theory and Practice in Policy Analysis
Including Applications in Science and Technology
, pp. 207 - 342
Publisher: Cambridge University Press
Print publication year: 2017

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References

References

Casman, E.A., Morgan, M.G., and Dowlatabadi, H. (1999). “Mixed Levels of Uncertainty in Complex Policy Models,” Risk Analysis, 19(1), pp. 3342.Google Scholar
Clark, H.H. (1990). “Comment,” Statistical Science, 5, pp. 1216.Google Scholar
Clark, W.C. (1980). “Witches, Floods and Wonder Drugs,” in Schwing, R.C. and Albers, W.A., Jr. (eds.), Societal Risk Assessment, Plenum, pp. 287318.CrossRefGoogle Scholar
Cliff, N. (1990). “Comment,” Statistical Science, 5, pp. 1618.Google Scholar
Cyert, R.M. and DeGroot, M.H. (1987). Bayesian Analysis and Uncertainty in Economic Theory, Rowman & Littlefield, 206pp.Google Scholar
Dawes, R.M. (1988). Rational Choice in an Uncertain World, Harcourt Brace Jovanovich, 346pp.Google Scholar
DeKay, M.L., Small, M.J., Fischbeck, P.S., Farrow, R.S., Cullen, A., Kadane, J.B., Lave, L.B., Morgan, M.G., and Takemura, K. (2002). “Risk-Based Decision Analysis in Support of Precautionary Policies,” Journal of Risk Research, 5(4), pp. 391417.CrossRefGoogle Scholar
Dieckmann, N.F., Peters, E. and Gregory, R. (2015). “At Home on the Range? Lay Interpretations of Numerical Uncertainty Ranges,” Risk Analysis, 35(7), pp. 12811295.Google Scholar
Dowlatabadi, H. and Morgan, M.G. (1993). “A Model Framework for Integrated Studies of the Climate Problem,” Energy Policy, 21(3), pp. 209221.Google Scholar
Ellsberg, D. (1961). “Risk, Ambiguity, and the Savage Axioms,” Quarterly Journal of Economics, 75, pp. 643669.Google Scholar
EPA (1996). Proposed Guidelines for Cancer Risk Assessment, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC, EPA/600P-92/003C.Google Scholar
Fischhoff, B. (1991). “Value Elicitation: Is There Anything in There?,” American Psychologist, 46, pp. 835847.Google Scholar
Fischhoff, B. (2005). “Chapter 18: Cognitive Processes in Stated Preference Methods,” in Mäleer, K.-G. and Vincent, J.R. (eds.), Handbook of Environmental Economics, Elsevier, Vol. II, pp. 938968.Google Scholar
Fischhoff, B. (2012). “Communicating Uncertainty: Fulfilling the Duty to Inform,” Issues in Science and Technology, 28(4), pp. 6370.Google Scholar
Fischhoff, B., Bostrom, A., and Jacobs-Quadrel, M. (2002). “Risk Perception and Communication,” in Detels, R., McEwen, J., Reaglenhole, R., and Tanaka, H. (eds.), Oxford Textbook of Public Health, 4th ed., Oxford University Press, Vol. III, pp. 11051123.Google Scholar
Franklin, B. (1789). Letter to Jean-Baptiste Leroy.Google Scholar
Friedman, S.M., Dunwoody, S., and Rogers, C.L. (1999). Communicating Uncertainty: Media Coverage of New and Controversial Science, L. Erlbaum, 277pp.Google Scholar
Funtowicz, S.O. and Ravetz, J.R. (1990). Uncertainty and Quality in Science for Policy, Kluwer Academic Publishers, 229pp.CrossRefGoogle Scholar
Good, I.J. (1962). “How Rational Should a Manager Be?Management Science, 8(4), pp. 383393.Google Scholar
Gregory, R. (2001). “Scenarios and Acceptance of Forecasts,” in Armstrong, J.S. (ed.), Principles of Forecasting: A Handbook for Researchers and Practitioners, Kluwer, 849pp.Google Scholar
Henrion, M. (1999) “Uncertainty,” in Wilson, R.A. and Keil, F.C. (eds.), MIT Encyclopedia of the Cognitive Sciences, MIT Press, pp. 853855.Google Scholar
Howard, R.A. and Matheson, J.E. (eds.) (1977). Readings in Decision Analysis, Decision Analysis Group, SRI International.Google Scholar
Ibrekk, H. and Morgan, M.G. (1987). “Graphical Communication of Uncertain Quantities to Nontechnical People,” Risk Analysis, 7, pp. 519529.Google Scholar
Inman, D.L., Jenkins, S.A., and Wasyl, J. (1998). “Database for Streamflow and Sediment Flux of California Rivers,” SIO Reference 98–9. Scripps Institution of Oceanography, University of California, San Diego.Google Scholar
IPCC (2001a). “Climate Change 2001: The Scientific Basis,” in Houghton, J.T. et al. (eds.), Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 881pp.Google Scholar
IPCC (2001b). “Climate Change 2001: Impacts, Adaptation, and Vulnerability,” in McCarthy, J.J. et al. (eds.), Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 1032pp.Google Scholar
IPCC (2001c). “Climate Change 2001: Mitigation,” in Metz, B. et al. (eds.), Contribution of Working Group III to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 700pp.Google Scholar
IPCC (2004). “Workshop Report,” in Manning, M. et al. (eds.), Workshop on Describing Scientific Uncertainties in Climate Change to Support Analysis of Risk and of Options, 146pp. Available at: www.ipcc.ch/pdf/supporting-material/ipcc-workshop-2004-may.pdf.Google Scholar
IPCC (2007). “The Physical Science Basis,” in Solomon, S. et al. (eds.), Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 800pp.Google Scholar
Kadane, J.B. (1990). “Comment: Codifying Chance,” Statistical Science, 5, pp. 1820.Google Scholar
Keeney, R.L. (1982). “Decision Analysis: An Overview,” Operations Research, 30, pp. 803837.Google Scholar
Keeney, R.L. (1992). Value-Focused Thinking: A Path to Creative Decision Making, Harvard University Press, 416pp.Google Scholar
Kent, S. (1964). “Words of Estimative Probability,” Studies in Intelligence, 8(4), pp. 4965.Google Scholar
Knight, F.H. (1921). Risk, Uncertainty and Profit, Houghton Mifflin Company, 381pp.Google Scholar
Kruskal, W. (1990). “Comment,” Statistical Science, 5, pp. 2021.Google Scholar
Kuhn, T.S. (1962). The Structure of Scientific Revolutions, University of Chicago Press, 172pp.Google Scholar
Lee, K. (1993). Compass and Gyroscope: Integrating Science and Politics for the Environment, Island Press, 243pp.Google Scholar
Lempert, R.J., Groves, D.G., Popper, S.W., and Bankes, S.C. (2006). “A General, Analytic Method for Generating Robust Strategies and Narrative Scenarios,” Management Science, 52(4), pp. 514528.Google Scholar
Lempert, R.J., Popper, S.W., and Bankes, S.C. (2003). Shaping the Next One Hundred Years: New Methods for Quantitative, Long-term Policy Analysis, MR-1626-RPC, RAND, 209pp.Google Scholar
Lempert, R.J., Popper, S.W., Groves, D. et al. (2013). “Making Good Decisions Without Predictions,” RAND Corporation Research Highlights, 6pp. Only available online at: www.rand.org/pubs/research_briefs/RB9701.html.Google Scholar
Lindblom, C.E. (1959). “The Science of ‘Muddling Through,’” Public Administration Review, 19(2), pp. 7988.Google Scholar
Mandel, D.R. and Barnes, A. (2014). “Accuracy of Forecasts in Strategic Intelligence,” Proceedings of the National Academy of Sciences, 111(30), pp. 1098410989.Google Scholar
Morgan, M.G. (1998). “Uncertainty Analysis in Risk Assessment,” Human and Ecological Risk Assessment, 4, pp. 2539.Google Scholar
Morgan, M.G. with Dowlatabadi, H., Henrion, M., Keith, D., Lempert, R., McBride, S., Small, M., and Wilbanks, T. (2009). Best Practice Approaches for Characterizing, Communicating, and Incorporating Scientific Uncertainty in Climate Decision Making, U.S. Climate Change Science Program Synthesis and Assessment Product (CCSP 5.2), 89pp.Google Scholar
Morgan, M.G., Fischhoff, B., Bostrom, A., and Atman, C.J. (2002). Risk Communication: A Mental Models Approach, Cambridge University Press, 351pp.Google Scholar
Morgan, M.G. and Henrion, M. (1990). Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, Cambridge University Press, 332pp.Google Scholar
Morgan, M.G., Kandlikar, M., Risbey, J., and Dowlatabadi, H. (1999). “Why Conventional Tools for Policy Analysis Are Often Inadequate for Problems of Global Change,” Climatic Change, 41, pp. 271281.CrossRefGoogle Scholar
Morgan, M.G. and Keith, D. (1995). “Subjective Judgments by Climate Experts,” Environmental Science & Technology, 29(10), pp. 468476.Google Scholar
Morgan, M.G. and Keith, D. (2008). “Improving the Way We Think about Projecting Future Energy Use and Emissions of Carbon Dioxide,” Climatic Change, 90(3), pp. 189215.CrossRefGoogle Scholar
Morris, S.C. (1990). Cancer Risk Assessment: A Quantitative Approach, M. Dekker, 408pp.Google Scholar
Moss, R. and Schneider, S.H. (2000). “Uncertainties in the IPCC TAR: Recommendations to Lead Authors for More Consistent Assessment and Reporting,” in Pachauri, R. et al. (eds.), Guidance Papers on the Cross Cutting Issues of the Third Assessment Report of the IPCC, World Meteorological Organisation, pp. 3351.Google Scholar
Moss, R.H., Edmonds, J.A., Hibbard, K.A. et al. (2010). “The Next Generation of Scenarios for Climate Change Research and Assessment,” Nature, 463, pp. 747756.Google Scholar
Mosteller, F. and Youtz, C. (1990). “Quantifying Probabilistic Expressions,” Statistical Science, 5, pp. 212.Google Scholar
Nakicenovic, N. and Swart, R. (eds.) (2000). Special Report on Emissions Scenarios, Cambridge University Press, 612pp.Google Scholar
National Assessment Synthesis Team (2000). “Climate Change Impacts on the United States: The Potential Consequences of Climate Variability and Change,” U.S. Global Change Research Program. Available at: www.globalchange.gov/browse/reports/climate-change-impacts-united-states-potential-consequences-climate-variability-and.Google Scholar
National Research Council (1986a). Understanding Risk: Informing Decisions in a Democratic Society, National Academy Press, 250pp.Google Scholar
National Research Council (1986b). Scientific Basis for Risk Assessment and Management of Uranium Mill Tailings, Committee on Uranium Mill Tailings Report, National Academy Press, 264pp.Google Scholar
Oreskes, N. and Conway, E.M. (2010). Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming, Bloomsbury Press, 355pp.Google Scholar
Paté-Cornell, M.E. (1996). “Uncertainties in Risk Analysis: Six Levels of Treatment,” Reliability Engineering and System Safety, 54, pp. 95111.Google Scholar
Patt, A.G. and Schrag, D.P. (2003.) “Using Specific Language to Describe Risk and Probability,” Climatic Change, 61, pp. 1730.Google Scholar
Presidential/Congressional Commission on Risk Assessment and Risk Management (1997). Vol. I: Framework for Environmental Health Risk Management; Vol. II: Risk Assessment and Risk Management in Regulatory Decision-Making. Available at: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=55006.Google Scholar
Raiffa, H. and Schlaifer, R. (1968). Applied Statistical Decision Theory, MIT Press, 356pp.Google Scholar
Rumsfeld, D. (2002). News briefing as quoted by Shermer, M., Scientific American, 293, September 2005, p. 38.Google Scholar
Schweizer, V.J. and Kriegler, E. (2012). “Improving Environmental Change Research with Systematic Techniques for Qualitative Scenarios,” Environmental Research Letters, 7(4), p. 044011.Google Scholar
Schweizer, V.J. and Morgan, M.G. (2016), “Bounding U.S. Electricity Demand in 2050,” Technology Forecasting & Social Change, 105, pp. 215223.CrossRefGoogle Scholar
Smil, V. (2003). Energy at the Crossroads, MIT Press, 448pp.Google Scholar
Smithson, M. (1988). Ignorance and Uncertainty: Emerging Paradigms, Springer-Verlag, 393pp.Google Scholar
Sunstein, C.R. (2005). Laws of Fear: Beyond the Precautionary Principle, Cambridge University Press, 234pp.Google Scholar
Tanur, J.M. (1990). “Comment: On the Possible Dangers of Isolation,” Statistical Science, 5, pp. 2122.Google Scholar
Thompson, M. (1980). “Aesthetics of Risk: Culture or Context,” in Schwing, R.C. and Albers, W.A. (eds.), Societal Risk Analysis, Plenum, pp. 273285.Google Scholar
Tukey, J.W. (1977). Exploratory Data Analysis, Addison-Wesley, 688pp.Google Scholar
von Winterfeldt, D. and Edwards, W. (1986). Decision Analysis and Behavioral Research, Cambridge University Press, 624pp.Google Scholar
Wallsten, T.S. and Budescu, D.V. (1990). “Comment,” Statistical Science, 5, pp. 2326.Google Scholar
Wallsten, T.S., Budescu, D.V., Rapoport, A., Zwick, R., and Forsyth, B. (1986). “Measuring the Vague Meanings of Probability Terms,” Journal of Experimental Psychology: General, 155(4), pp. 348365.Google Scholar
Weick, K. and Sutcliffe, K. (2001). Managing the Unexpected: Assuring High Performance in an Age of Uncertainty, Wiley, 200pp.Google Scholar
Wiener, J.B. and Rogers, M.D. (2002). “Comparing Precaution in the United States and Europe,” Journal of Risk Research, 5(4), pp. 317349.Google Scholar
Wilbanks, T. and Lee, R. (1985) “Policy Analysis in Theory and Practice,” in Lakshmanan, T.R. and Johansson, B. (eds.), Large-Scale Energy Projects: Assessment of Regional Consequences, North-Holland, pp. 273303.Google Scholar
Wildavsky, A. (1979). “No Risk Is the Highest Risk of All,” American Scientist, 67, pp. 3237.Google Scholar
Winkler, R.L. (1990). “Comment: Representing and Communicating Uncertainty,” Statistical Science, 5, pp. 2630.Google Scholar
Wolf, C., Jr. (1990). “Comment,” Statistical Science, 5, pp. 3132.Google Scholar

References

Abdulla, A., Azevedo, I., and Morgan, M.G. (2013). “Expert Assessments of the Cost of Light Water Small Modular Reactors,” Proceedings of the National Academy of Sciences, 110(24), pp. 96869691.Google Scholar
Anadon, L.D., Bosetti, V., Bunn, M., and Lee, A. (2012). “Expert Judgments about RD&D and the Future of Nuclear Energy,” Environmental Science & Technology, 41(21), pp. 1149711504.Google Scholar
Anadon, L.D., Nemet, G.F., and Verdolini, E. (2013). “The Future Costs of Nuclear Power using Multiple Expert Elicitations: Effects of RD&D and Elicitation Design,” Environmental Research Letters, 8(3), p. 034020.Google Scholar
Aspinall, W. (2010). “A Route to More Tractable Expert Advice,” Nature, 463, pp. 294295.Google Scholar
Bolger, F. and Rowe, G. (2014). “Delphi: Somewhere between Scylla and Charybdis?,” Proceedings of the National Academy of Science, 111(41), p. E4284.Google Scholar
Bolger, F. and Wright, G. (2011). “Improving the Delphi Process: Lessons from Social Psychological Research,” Technological Forecasting and Social Change, 78(9), pp. 15001513.Google Scholar
Budnitz, R.J. et al. (1995). “Recommendations for Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and the Use of Experts,” UCRL-ID 122160, Lawrence Livermore National Laboratory.Google Scholar
Budnitz, R.J., et al. (1997). “Recommendations for Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and Use of Experts,” NUREG/CR-6372, Vol. II, U.S. Nuclear Regulatory Commission.Google Scholar
Budnitz, R.J., Apostolakis, G., Boore, D.M., Cluff, L.S., Coppersmith, K.J., Cornell, C.A., and Morris, P.A. (1998). “Use of Technical Expert Panels: Applications to Probabilistic Seismic Hazard Analysis,” Risk Analysis, 18(4), pp. 463469.Google Scholar
Chan, G., Anadon, L.D., Chan, M., and Lee, A. (2011). “Expert Elicitation of Cost, Performance, and RD&D Budgets for Coal Power with CCS,” Energy Procedia, 4, pp. 26852692.Google Scholar
Charba, J.P. and Klein, W.H. (1980). “Skill in Precipitation Forecasting in the National Weather Service,” Bulletin of the American Meteorological Society, 61, pp. 15461555.Google Scholar
Christensen-Szalanski, J.J.J. and Bushyhead, J.B. (1981). “Physicians’ Use of Probabilistic Information in a Real Clinical Setting,” Journal of Experimental Psychology: Human Perception and Performance, 7(4), pp. 928935.Google Scholar
Clark, W.C., Tomich, T.P., van Noordwijk, M., Guston, D., Catacutan, D., Dickson, N.M., and McNie, E. (2011). “Boundary Work for Sustainable Development: Natural Resource Management at the Consultative Group on International Agricultural Research (CGIAR),” Proceedings of the National Academy of Sciences, 113(17), 8pp.Google Scholar
Clemen, R.T. (2008). “Comment on Cooke’s Classical Method,” Reliability Engineering and System Safety, 93, pp. 760765.Google Scholar
Clemen, R.T. and Winkler, R.L. (1999). “Combining Probability Distributions from Experts in Risk Analysis,” Risk Analysis, 19, pp. 187203.Google Scholar
Clemen, R.T. and Winkler, R.L. (2007). “Chapter 9: Aggregating Probability Distributions,” in Edwards, W., Miles, R.F. Jr., and von Winterfeldt, D. (eds.), Advances in Decision Analysis: From Foundations to Applications, Cambridge University Press, pp. 154176.Google Scholar
Colson, A.R. and Cooke, R.M. (2017). “Cross Validation for the Classical Model of Structured Expert Judgment,” Reliability Engineering and System Safety, 163, pp. 109120.Google Scholar
Cooke, R.M. (1991). Experts in Uncertainty: Opinion and Subjective Probability in Science, Oxford University Press, 336pp.Google Scholar
Cooke, R.M. and Goossens, L.L.H.J. (2008). “TU Delft Expert Judgment Data Base,” Reliability Engineering and System Safety, 93, pp. 657674.Google Scholar
Cooke, R.M., Wilson, A.M., Tuomisto, J.T., Morales, O., Tainio, M., and Evans, J.S. (2007). “A Probabilistic Characterization of the Relationship between Fine Particulate Matter and Mortality: Elicitation of European Experts,” Environmental Science & Technology, 41, pp. 65986605.Google Scholar
Curtright, A.E., Morgan, M.G., and Keith, D.W. (2008). “Expert Assessment of Future Photovoltaic Technology,” Environmental Science & Technology, 42(24), pp. 90319038.Google Scholar
Dalkey, N. and Helmer, O. (1972). “An Experimental Application of the Delphi Method to the Use of Experts,” RAND Corporation report RM- 727/1- (Abridged).Google Scholar
de Finetti, B. (1974). Theory of Probability: A Critical Introductory Treatment, Wiley, 2 vols.Google Scholar
DeGroot, M.H. (1970). Optimal Statistical Decisions, McGraw-Hill, 489pp.Google Scholar
Devilee, J.L.A. and Knol, A.B. (2011). “Software to Support Expert Elicitation: An Exploratory Study of Existing Software Packages,” RIVM Letter Report 630003001/2011 (Dutch National Institute of Public Health and Environment), 98pp. Available at: www.rivm.nl/en/Documents_and_publications/Scientific/Reports/2012/mei/Software_to_support_expert_elicitation_An_exploratory_study_of_existing_software_packages.Google Scholar
Dowlatabadi, H. and Morgan, M.G. (1993). “A Model Framework for Integrated Studies of the Climate Problem,” Energy Policy, 21(3), pp. 209221.Google Scholar
EPA (2011). “Expert Elicitation Task Force White Paper.” Available at: www.epa.gov/stpc/pdfs/ee-white-paper-final.pdf.Google Scholar
Evans, J.S., Graham, J.D., Gray, D.M., and Sielken, R.L., Jr. (1994a). “A Distributional Approach to Characterizing Low-Dose Cancer Risk,” Risk Analysis, 14(1), pp. 2534.Google Scholar
Evans, J.S., Gray, G.M., Sielken, R.L., Smith, A.E., Valdezflores, C., and Graham, J.D. (1994b). “Using of Probabilistic Expert Judgment in Uncertainty Analysis of Carcinogenic Potency,” Regulatory Toxicology and Pharmacology, 20 (1 pt.1), pp. 1536.Google Scholar
Funtowicz, S.O. and Ravetz, J.R. (1990). Uncertainty and Quality in Science for Policy, Kluwer, 229pp.Google Scholar
Garthwaite, P.H., Kadane, J.B., and O’Hagan, A. (2005). “Statistical Methods for Eliciting Probability Distributions,” Journal of the American Statistical Association, 100, pp. 680700.Google Scholar
Good, I.J. (1971). “46656 Varieties of Bayesians,” The American Statistician, 25(5), pp. 6263.Google Scholar
Henrion, M. and Fischhoff, B. (1986). “Assessing Uncertainty in Physical Constants,” American Journal of Physics, 54(9), pp. 791798.Google Scholar
Hoek, G., Boogaard, H., Knol, A. et al. (2010). “Concentration Response Functions for Ultrafine Particles and All-Cause Mortality and Hospital Admissions: Results of a European Expert Panel Elicitation,” Environmental Science & Technology, 44, pp. 476482.Google Scholar
Hora, S.C. (2007). “Chapter 9: Eliciting Probability from Experts,” in Ward, E.W., Miles, R.F. Jr., and von Winterfeldt, D. (eds.), Advances in Decision Analysis: From Foundations to Applications, Cambridge University Press, pp. 129153.Google Scholar
IPCC (2001). “Climate Change 2001: The Scientific Basis,” in Houghton, J.T. et al. (eds.), Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 881pp.Google Scholar
IPCC (2007). “Climate Change 2007: The Physical Science Basis,” in Solomon, S. et al. (eds.), Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, 800pp.Google Scholar
IPCC (2013). “Summary for Policymakers in Climate Change 2013: The Physical Science Basis,” in Stocker, T.F. et al. (eds.), Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press.Google Scholar
Jaynes, E.T. (2003). Probability Theory: The Logic of Science, Cambridge University Press, 727pp.Google Scholar
Kadane, J. and Fischhoff, B. (2013). “A Cautionary Note of Global Recalibration,” Judgment and Decision Making, 8(1), pp. 25–28.Google Scholar
Kahneman, D., Slovic, P., and Tversky, A. (eds.) (1982). Judgment under Uncertainty: Heuristics and Biases, Cambridge University Press, 555pp.Google Scholar
Karvetski, C.W., Olson, K.C., Mandel, D.R., and Twardy, C.R. (2013). “Probabilistic Coherence Weighting for Optimizing Expert Forecasts,” Decision Analysis, 10, pp. 305326.Google Scholar
Knol, A.B., de Hartog, J.J., Boogaard, H. et al. (2009). “Expert Elicitation on Ultrafine Particles: Likelihood of Health Effects and Causal Pathways,” Particle and Fibre Toxicology, 6, p. 19.Google Scholar
Knol, A.B., Slottje, P., van der Sluijs, J.P., and Lebret, E. (2010). “The Use of Expert Elicitation in Environmental Health Impact Assessment: A Seven Step Procedure,” Environmental Health, 9, p. 19.Google Scholar
Krayer von Krauss, M.P., Casman, E.A., and Small, M.J. (2004). “Elicitation of Expert Judgments of Uncertainty in the Risk Assessment of Herbicide-Tolerant Oilseed Crops,” Risk Analysis, 24(6), pp. 15151527.Google Scholar
Lichtenstein, S., Fischhoff, B., and Phillips, L. (1982). “Chapter 22: Calibration of Probabilities: The State of the Art to 1980,” in Kahneman, D., Slovic, P., and Tversky, A. (eds.), Judgment under Uncertainty: Heuristics and Biases, Cambridge University Press, pp. 306334.Google Scholar
Lin, S.W. and Cheng, C.H. (2009). “The Reliability of Aggregated Probability Judgments Obtained through Cooke’s Classical Method,” Journal of Modeling in Management, 4, pp. 149161.Google Scholar
Mandel, D. and Barnes, A. (2014). “Accuracy of Forecasts in Strategic Intelligence,” Proceedings of the National Academy of Sciences, 111(30), pp. 1098410989.Google Scholar
Mastrandrea, M.D. et al. (2010). “Guidance Note for Lead Authors of the IPCC Fifth Assessment Report on Consistent Treatment of Uncertainties, Intergovernmental Panel on Climate Change (IPCC).” Available at: www.ipcc.ch/pdf/supporting-material/uncertainty-guidance-note.pdf.Google Scholar
Morgan, M.G. (2014). “The Use (and Abuse) of Expert Elicitation in Support of Decision Making for Public Policy,” PNAS, 111(20), pp. 71767184.CrossRefGoogle ScholarPubMed
Morgan, M.G., Adams, P., and Keith, D.W. (2006). “Elicitation of Expert Judgments of Aerosol Forcing,” Climatic Change, 75, pp. 195214.Google Scholar
Morgan, M.G. and Dowlatabadi, H. (1996). “Learning from Integrated Assessment of Climate Change,” Climatic Change, 34, pp. 337368.Google Scholar
Morgan, M.G. with Dowlatabadi, H., Henrion, M., Keith, D., Lempert, R., McBride, S., Small, M., and Wilbanks, T. (2009). CCSP 5.2 Best Practice Approaches for Characterizing, Communicating, and Incorporating Scientific Uncertainty in Decisionmaking, Report by the Climate Change Science Program and the Subcommittee on Global Change Research, National Oceanic and Atmospheric Administration, 96pp.Google Scholar
Morgan, M.G. and Henrion, M. with a chapter by Small, M. (1990). Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, Cambridge University Press, 332pp.Google Scholar
Morgan, M.G. and Keith, D. (1995). “Subjective Judgments by Climate Experts,” Environmental Science & Technology, 29(10), pp. 468A–476A.Google Scholar
Morgan, M.G., Morris, S.C., Henrion, M., Amaral, D.A.L., and Rish, W.R. (1984). “Technical Uncertainty in Quantitative Policy Analysis: A Sulfur Air Pollution Example,” Risk Analysis, 4, pp. 201216.Google Scholar
Morgan, M.G., Morris, S.C., Rish, W.R., and Meier, A.K. (1978). “Sulfur Control in Coal-Fired Power Plants: A Probabilistic Approach to Policy Analysis,” Journal of the Air Pollution Control Association, 28, pp. 993997.Google Scholar
Morgan, M.G., Pitelka, L.F., and Shevliakova, E. (2001). “Elicitation of Expert Judgments of Climate Change Impacts on Forest Ecosystems,” Climatic Change, 49(3), pp. 279307.Google Scholar
Morris, D.E., Oakley, J.E., and Crowe, J.A. (2014). “A Web-Based Tool for Eliciting Probability Distributions from Experts,” Environmental Modelling and Software, 52, pp. 14.Google Scholar
Moss, R. and Schneider, S.H. (2000). “Uncertainties in the IPCC TAR: Recommendations to Lead Authors for More Consistent Assessment and Reporting,” in Pachauri, R. et al. (eds.), Guidance Papers on the Cross Cutting Issues of the Third Assessment Report of the IPCC, pp. 3351. Available at: www.ipcc.ch/pdf/supportingmaterial/guidance-papers-3.Google Scholar
Murphy, A.H. and Winkler, R.L. (1977). “Can Weather Forecasters Formulate Reliable Probability Forecasts of Precipitation and Temperature?,” National Weather Digest, 2, pp. 29(a).Google Scholar
National Assessment Synthesis Team (2001). Climate Change Impacts on the United States: The Potential Consequences of Climate Variability and Change, Cambridge University Press, 612pp.Google Scholar
NDU (1978). “February,” in Climate Change to the Year 2000: A Survey of Expert Opinion, Report published by the National Defense University in cooperation with the U.S. Department of Agriculture, the Defense Advanced Research Projects Agency, the National Oceanic and Atmospheric Administration, and Institute for the Future. [For a critique, see Stewart, T.R. and Glantz, M.H. (1985). “Expert Judgment and Climate Forecasting: A Methodological Critique of Climate Change to the Year 2000,” Climatic Change, 7, pp. 159183.]Google Scholar
O’Hagan, A., Buck, C.E., Daneshkhah, A., Eiser, J.R., Garthwaite, P.H., Jenkinson, D.J., Oakley, J.E., and Rakow, T. (2006). Uncertain Judgments: Eliciting Experts’ Probabilities, John Wiley & Sons, 321pp.Google Scholar
O’Hagan, A. and Oakley, J.E. (2010). “SHELF: The Sheffield Elicitation Framework, Version 2.0, School of Mathematics and Statistics,” University of Sheffield. Available at: www.tonyohagan.co.uk/shelf.Google Scholar
Oppenheimer, M., O’Neill, B.C., Webster, M., and Agerwala, S. (2007). “The Limit of Consensus,” Science, 317, pp. 15051506.Google Scholar
Presidential/Congressional Commission on Risk Assessment and Risk Management (1997). Vol. I: Framework for Environmental Health Risk Management; Vol. II: Risk Assessment and Risk Management in Regulatory Decision Making. Available at: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=55006.Google Scholar
Rao, A.B., Rubin, E.S., Keith, D.W., and Morgan, M.G. (2006). “Evaluation of Potential Cost Reductions from Improved Amine-Based CO2 Capture Systems,” Energy Policy, 34, pp. 37653772.Google Scholar
Refsgaard, J.C., Van der Sluijs, J.P., Brown, J., and Van der Keur, P. (2005). “A Framework for Dealing with Uncertainty Due to Model Structure Error,” Water Resources, 29, pp. 15861597.Google Scholar
Roman, H.A., Walker, K.D., Walsh, T.L., Conner, L., Richmond, H.M., Hubbell, B.J., and Kinney, P.L. (2008). “Expert Judgment Assessment of the Mortality Impact of Changes in Ambient Fine Particulate Matter in the U.S.,” Environmental Science & Technology, 42, pp. 22682274.Google Scholar
Rowe, G. and Wright, G. (1999). “The Delphi Technique as a Forecasting Tool: Issues and Analysis,” International Journal of Forecasting, 15(4), pp. 353375.Google Scholar
Sackman, H. (1975). Delphi Critique: Expert Opinion, Forecasting, and Group Process, Lexington Books, 142pp.Google Scholar
Schneider, S. et al. (2007). “Climate Change 2007: Impacts, Adaptation, and Vulnerabilities,” in Parry, M.L. et al. (eds.), Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, pp. 779810.Google Scholar
Spetzler, C.S. and Staël von Holstein, C.-A.S. (1975). “Probability Encoding in Decision Analysis,” Management Science, 22(3), pp. 340358.Google Scholar
Tversky, A. and Kahneman, D. (1974). “Judgments under Uncertainty: Heuristics and Biases,” Science, 185(4157), pp. 11241131.Google Scholar
Van der Sluijs, J.P., Craye, M., Funtowicz, S., Kloprogge, P., Ravetz, J., and Risbey, J. (2005a). “Combining Quantitative and Qualitative Measures of Uncertainty in Model-Based Environmental Assessment: The NUSAP System,” Risk Analysis, 25(2), pp. 481492.Google Scholar
Van der Sluijs, J.P., Risbey, J.S., and Ravetz, J. (2005b). “Uncertainty Assessment of VOC Emissions from Paint in the Netherlands using the NUSAP System,” Environmental Monitoring and Assessment, 105, pp. 229259.Google Scholar
Wallsten, T.S., Budescu, D.V., Rapoport, A., Zwick, R., and Forsyth, B. (1986). “Measuring the Vague Meanings of Probability Terms,” Journal of Experimental Psychology: General, 155(4), pp. 348365.Google Scholar
Wallsten, T.S. and Whitfield, R.G. (1989). “A Risk Assessment for Selected Lead-Induced Health Effects: An Example of a General Methodology,” Risk Analysis, 9(2), pp. 197207.Google Scholar
Wardekker, J.A., van der Sluijs, J.P., Janssen, P.H.M., Kloprogge, P., and Petersen, A.C. (2008). “Uncertainty Communication in Environmental Assessments: Views from the Dutch Science–Policy Interface,” Environmental Science and Policy, 11, pp. 627641.Google Scholar
Woudenberg, F. (1991). “An Evaluation of Delphi,” Technology Forecasting and Social Change, 40(2), pp. 131150.Google Scholar
Zickfeld, K., Levermann, A., Morgan, M.G., Kuhlbrodt, T., Rahmstorf, S., and Keith, D.W. (2007). “Expert Judgments on the Response on the Atlantic Meridional Overturning Circulation to Climate Change,” Climatic Change, 82, pp. 235265.Google Scholar
Zickfeld, K., Morgan, M.G., Frame, D., and Keith, D.W. (2010). “Expert Judgments about Transient Climate Response to Alternative Future Trajectories of Radiative Forcing,” Proceedings of the National Academy of Sciences, 107, pp. 1245112456.Google Scholar

References

Ames, B.N., Magaw, R., and Gold, L.S. (1987). “Ranking Possible Carcinogenic Hazards,” Science, 236, pp. 271280.Google Scholar
Burke, J.G. (1966). “Bursting Boilers and the Federal Power,” Technology and Culture, 7, pp. 123.Google Scholar
Case, A. and Deaton, A. (2015). “Rising Morbidity and Mortality in Midlife among White Non-Hispanic Americans in the 21st Century,” Proceedings of the National Academy of Science, 112(49), pp. 1507815083.Google Scholar
Clark, W.C. (1980). “Witches, Floods and Wonder Drugs,” in Schwing, R.C. and Albers, W.A. Jr. (eds.), Societal Risk Assessment: How Safe Is Safe Enough?, Plenum, pp. 287318.CrossRefGoogle Scholar
Crouch, E.A.C. and Wilson, R. (1982). Risk/Benefit Analysis, Ballinger, 218pp.Google Scholar
EPA SAB (2001). Improved Science-Based Environmental Stakeholder Processes: A Commentary by the EPA Science Advisory Board, EPA-SAB-EC-COM-01-006, 25pp. Available at: http://yosemite.epa.gov/sab/sabproduct.nsf/cee3f362f1a1344e8525718e004ea078/$file/eecm01006_report_appna-e.pdf.Google Scholar
Fischbeck, P.S. and Farrow, R.S. (eds.) (2001). Improving Regulation: Cases in Environment, Health and Safety, Resources for the Future, 461pp.Google Scholar
Fischhoff, B., Slovic, P., and Lichtenstein, S. (1978). “Fault Trees: Sensitivity of Estimated Failure Probabilities to Problem Representation,” Journal of Experimental Psychology: Human Perception and Performance, 4, pp. 342355.Google Scholar
Glickman, T.S. and Gough, M. (1990). Readings in Risk, Resources for the Future, distributed by Johns Hopkins University Press, 262pp.Google Scholar
Graham, J.D. and Vaupel, J. (1981). “Value of Life: What Difference Does It Make?,” Risk Analysis, 1, pp. 692704.Google Scholar
Graham, J.D. and Wiener, J.B. (1995). Risk versus Risk: Trade-offs in Protecting Health and the Environment, Harvard University Press, 337pp.Google Scholar
Heinzerling, L. (1998). “Regulatory Costs of Mythic Proportions,” The Yale Law Journal, 107(7), pp. 19812070.Google Scholar
Karcher, S.C., VanBriesen, J.M., and Nietch, C.T. (2012). Assessing the Challenges Associated with Developing an Integrated Modeling Approach for Predicting and Managing Water Quality and Quantity from the Watershed through the Drinking Water Treatment System, U.S. EPA Office of Research and Development, EPA/600/R-12/030, 55pp.Google Scholar
Keeney, R.L. (1995). “Understanding Life-Threatening Risks,” Risk Analysis, 15, pp. 627637.Google Scholar
Keeney, R.L., Kulkarni, R.B., and Nair, K. (1978). “Assessing the Risk of an LNG Terminal,” Technology Review, 81(1), pp. 6472.Google Scholar
Kuzmack, A.M. and McGaughy, R.E (1975). Quantitative Risk Assessment for Community Exposure to Vinyl Chloride, U.S. Environmental Protection Agency, 122pp.Google Scholar
Lave, L.B. (1981). The Strategy of Social Regulation: Decision Frameworks for Policy, Brookings, 166pp.Google Scholar
Mayer, J. (2016). Dark Money: The Hidden History of the Billionaires behind the Rise of the Radical Right, Doubleday, 449pp.Google Scholar
Möller-Gulland, J., McGlade, K., and Lago, M. (2011). “Effluent Tax in Germany,” EPI Water Report WP3 EX-POST, Evaluating Economic Policy Instrument for Sustainable Water Management in Europe, 39pp. Available at: www.feem-project.net/epiwater/docs/d32-d6-1/CS14_Germany.pdf.Google Scholar
Morgan, M.G. (1981a) “Probing the Question of Technology-Induced Risk,” IEEE Spectrum, 18(11), pp. 5864.Google Scholar
Morgan, M.G. (1981b) “Choosing and Managing Technology-Induced Risk,” IEEE Spectrum, 18(12), pp. 5360.Google Scholar
Morgan, M.G. and Lave, L.B. (1990). “Ethical Considerations in Risk Communication Practice and Research,” guest editorial in Risk Analysis, 10(3), pp. 355358.Google Scholar
Morgan, M.G. and McMichael, F.C. (1981). “A Characterization and Critical Discussion of Models and Their Use in Environmental Policy,” Policy Sciences, 14, pp. 345370.Google Scholar
Morrall, J.F., III (1986). “A Review of the Record,” Regulation, pp. 2534.Google Scholar
Morrall, J.F., III (2003). “Saving Lives: A Review of the Record,” AEI-Brookings Joint Center Working Paper 03-6, 28pp.Google Scholar
Morris, S.C. (1990). Cancer Risk Assessment: A Quantitative Approach, M. Dekker, 408pp.Google Scholar
Notarianni, K.A. (2000). “The Role of Uncertainty in Improving Fire Protection Regulation,” Ph.D. thesis, Department of Engineering and Public Policy, Carnegie Mellon University, 256pp.Google Scholar
Notarianni, K.A. and Fischbeck, P.S. (2001). “Performance with Uncertainty: A Process for Implementing Performance-Based Fire Regulations,” in Fischbeck, P.S. and Farrow, G.S. (eds.), Improving Regulation: Cases in Environment Health and Safety, Resources for the Future, pp. 233256.Google Scholar
NRC (1983). Risk Assessment in the Federal Government: Managing the Process, National Academies Press, 191 pp.Google Scholar
NRC (1993). Pesticides in the Diets of Infants and Children, National Academies Press, 386pp.Google Scholar
NRC (1994). Science and Judgment in Risk Assessment, National Academies Press, 651pp.Google Scholar
NRC (1996). Understanding Risk: Informing Decisions in a Democratic Society, National Academies Press, 249pp.Google Scholar
Oreskes, N. and Conway, E.M. (2010). Merchants of Doubt, Bloomsbury Press, 355pp.Google Scholar
Pope, C.A., III, Burnett, R.T., Turner, M.C., Cohen, A., Krewski, D., Jerrett, M., Gapstur, S.M., and Thun, M.J. (2011). “Lung Cancer and Cardiovascular Disease Mortality Associated with Ambient Air Pollution and Cigarette Smoke: Shape of the Exposure–Response Relationships,” Environmental Health Perspectives, 119(11), pp. 16161621.Google Scholar
Ramsberg, J.A.L. and Sjöberg, L. (1997). “The Cost-Effectiveness of Lifesaving Interventions in Sweden,” Risk Analysis, 17(4), pp. 467478.Google Scholar
Rasmussen, N.C. (1981). “The Application of Probabilistic Risk Assessment Techniques to Energy Technologies,” Annual Reviews of Energy, 6, pp. 123138.Google Scholar
Seinfeld, J.H. and Pandis, S. (2006). Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley, 1203pp.Google Scholar
Slovic, P., Fischhoff, B., and Lichtenstein, S. (1980). “Facts and Fears: Understanding Perceived Risk,” in Schwing, R.S. and Albers, W.A. Jr. (eds.), Societal Risk Assessment: How Safe Is Safe Enough?, Plenum, pp. 181214.Google Scholar
Tengs, T.O., Adams, M.E., Pliskin, J.S., Safran, D.G., Siegel, J.E., Weinstein, M.C., and Graham, J.D. (1995). “Five-Hundred Live Saving Interventions and Their Cost-Effectiveness,” Risk Analysis, 15, pp. 369390.Google Scholar
Tengs, T.O. and Graham, J.D. (1996). “Chapter 8: The Opportunity Costs of Social Investments in Life-Saving,” in Hahn, R.W. (ed.), Risks and Costs of Lives Saved, Oxford University Press, pp. 167182.Google Scholar
Thomann, R.V. and Mueller, J.A. (1987). Principles of Surface Water Quality Modeling and Control, Harper & Row, 644pp.Google Scholar
Thompson, M. (1980). “Aesthetics of Risk: Culture or Context,” in Schwing, R.C. and Albers, W.A. Jr. (eds.), Societal Risk Assessment: How Safe Is Safe Enough?, Plenum, pp. 273285.Google Scholar
Train, R. (1976). “Interim Procedures and Guidelines for Health Risk and Economic Impact Assessments of Suspected Carcinogens,” EPA Office of the Administrator, 15pp.Google Scholar
US EPA (1984). “Risk Assessment and Management: Framework for Decision Making,” US EPA 600-9-85, 37pp.Google Scholar
WASH-1400 (1975). Reactor Safety Study: An Assessment of Accident Risks in U.S. Commercial Nuclear Power Plants, NUREG-75/014 (WASH-1400), 207pp.Google Scholar
Wellen, C., Kamran-Disfani, A.-R., and Arhonditsis, G.B. (2015). “Evaluation of the Current State of Distributed Watershed Nutrient Water Quality Modeling,” Environmental Science & Technology, 49(6), pp. 32783290.Google Scholar
White, M.C., Infante, P.F., and Chu, K.C. (1982). “A Quantitative Estimate of Leukemia Mortality Associated with Occupational Exposure to Benzene,” Risk Analysis, 2(3), pp. 195204.Google Scholar
Wiener, J.B., Rogers, M.D., Hammitt, J.K., and Sand, P.H. (eds.) (2011). The Reality of Precaution: Comparing Risk Regulation in the United States and Europe, RFF Press/Earthscan/Routledge, 582pp.Google Scholar
Wildavsky, A. (1979). “No Risk Is the Highest Risk of All,” American Scientist, 67, Jan.–Feb., pp. 3237.Google Scholar
Wilmoth, J.R. (1998). “The Future of Human Longevity: A Demographer’s Perspective,” Science, 280, pp. 395397.Google Scholar
Wynder, E.L. and Hoffmann, D. (1979). “Tobacco and Health: A Societal Challenge,” The New England Journal of Medicine, 300, pp. 894903.Google Scholar
Zannetti, P. (ed.) (2003–2010). Air Quality Modeling: Theories, Methodologies, Computational Techniques, and Available Databases and Software, Vol. I, Fundamentals; Vol. II, Advanced Topics; Vol. III, Special Issues; Vol. IV, Advances and Updates, EnviroComp and Air & Waste Management Association.Google Scholar

References

Ågren, G. and Andersson, F. (2012). Terrestrial Ecosystem Ecology: Principles and Applications, Cambridge University Press, 330pp.Google Scholar
Alcamo, J., Shaw, R., and Hordijk, L. (eds.) (1990). The RAINS Model of Acidification: Science and Strategies in Europe, Kluwer, 402pp.Google Scholar
Au, T. and Au, T.P. (1992). Engineering Economics for Capital Investment Analysis, Prentice Hall, 540pp.Google Scholar
Ayres, R.U. (1984). “Limits and Possibilities of Large-Scale Long-Range Societal Models,” Technological Forecasting and Social Change, 25(4), pp. 297308.Google Scholar
Benjamin, J.R. and Cornell, C.A. (1970). Probability, Statistics, and Decision for Civil Engineers, McGraw-Hill, 684pp.Google Scholar
Boyd, R. (1972). “World Dynamics: A Note,” Science, 177, pp. 516519.Google Scholar
Casman, E.A., Ha-Duong, M., and Morgan, M.G. (2004). “Response to Sander Greenland’s Critique of Bounding Analysis,” Risk Analysis, 24(5), pp. 10931096.Google Scholar
Casman, E.A. and Morgan, M.G. (2005). “Use of Expert Judgment to Bound Lung Cancer Risks,” Environmental Science & Technology, 39, pp. 59115920.Google Scholar
Casman, E.A., Morgan, M.G., and Dowlatabadi, H. (1999). “Mixed Levels of Uncertainty in Complex Policy Models,” Risk Analysis, 19(1), pp. 3342.Google Scholar
Cohen, J.E. (1995). “Population Growth and Earth’s Human Carrying Capacity,” Science, 269, pp. 341346.Google Scholar
Craig, P.P., Gadgil, A., and Koomey, J.G. (2002). “What Can History Teach US? Examination of Long-Term Energy Forecasts for the United States,” Annual Review of Energy and the Environment, 27, pp. 83118.Google Scholar
Dowlatabadi, H. and Morgan, M.G. (1993). “A Model Framework for Integrated Studies of the Climate Problem,” Energy Policy, 21(3), pp. 209221.Google Scholar
EIA (2009). The National Energy Modeling System: An Overview 2009, DOE/EIA-0581, 77pp. Available at: www.eia.gov/forecasts/aeo/nems/overview/pdf/0581(2009).pdf.Google Scholar
Fischbeck, P., Zhai, H., and Anderson, J. et al. (2015). "A Techno-Economic Decision Support Tool for Guiding States’ Responses to the EPA Clean Power Plan.” Available at: www.cmu.edu/energy/cleanpowerplantool.Google Scholar
Flyvbjerg, B., Skamris Holm, M.K., and Buhl, S.L. (2003). “How Common and How Large Are Cost Overruns in Transport Infrastructure Projects?,” Transport Review, 23(1), pp. 7188.Google Scholar
Ford, A. (2009). Modeling the Environment, Island Press, 380pp.Google Scholar
Ford Foundation Energy Project (1974). A Time to Choose: America’s Energy Future, Ballenger, 511pp.Google Scholar
Forrester, J.W. (1969). Urban Dynamics, MIT Press, 285pp.Google Scholar
Forrester, J.W. (1971). World Dynamics, Wright-Allen Press, 142pp.Google Scholar
Gabriel, S.A., Kydes, A.S., and Whitman, P. (2001). “The National Energy Modeling System: A Large-Scale Energy-Economic Equilibrium Model,” Operations Research, 49(1), pp. 1425.Google Scholar
Greenberger, M. (1983). Caught Unawares: The Energy Decade in Retrospect, Ballinger, 415pp.Google Scholar
Greenberger, M., Crenson, M.A., and Crissy, B.L. (1976). Models in the Policy Process: Public Decision Making in the Computer Era, Russell Sage Foundation/Basic Books, 355pp.Google Scholar
GTS (1980). The Global 2000 Report to the President: Entering the Twenty-First Century, ed. by Barney, G.O., 3 vols., Council on Environmental Quality and the Department of State.Google Scholar
Ha-Duong, M.E., Casman, A., and Morgan, M.G. (2004). “Bounding Poorly Characterized Risks: A Lung Cancer Example,” Risk Analysis, 24(5), pp. 10711084.Google Scholar
Harte, J. (1988). Consider a Spherical Cow: A Course in Environmental Problem Solving, University Science Books, 283pp.Google Scholar
Hendrickson, C. and Au, T. (2008). Project Management and Construction: Fundamental Concepts for Owners, Engineers, Architects and Builders. Online book available at: http://pmbook.ce.cmu.edu.Google Scholar
Hendrickson, C.T., Lave, L.B., and Matthews, H.S. (2006). Environmental Life Cycle Assessment of Goods and Services: An Input-Output Approach, Resources for the Future, 262pp.Google Scholar
Henrion, M. (2004). “What’s Wrong with Spreadsheets: And How To Fix Them With Analytica,” 16pp. Available at: www.lumina.com/uploads/technology/Whats%20wrong%20with%20spreadsheets.pdf.Google Scholar
Holcombe, R.G. (1989). Economic Models and Methodology, Greenwood Press, 201pp.Google Scholar
Horowitz, K.J. and Planting, M.A. (2009). Concepts and Methods of the Input-Output Accounts, Bureau of Economic Analysis, U.S. Department of Commerce, 266pp. Available at: www.bea.gov/papers/pdf/IOmanual_092906.pdf.Google Scholar
House, P.W. and McLeod, J. (1977). Large Scale Models for Policy Evaluation, Wiley-Interscience, 326pp.Google Scholar
Huntington, H.G. (1994). “Oil Price Forecasting in the 1980s: What Went Wrong?,” The Energy Journal, 15, pp. 122.Google Scholar
IECM (2015). The Integrated Environmental Control Model. Available at: www.cmu.edu/epp/iecm.Google Scholar
ISO (1997). “ISO Standard 14040: Environmental Management – Life Cycle Assessment: Principles and Framework,” International Standard Organization, 12pp.Google Scholar
ISO (2006). “ISO 14040: Environmental Management – Life Cycle Assessment: Principles and Framework,” International Standards Organization. Available online at www.iso.org/iso/catalogue_detail?csnumber=37456.Google Scholar
Keyfitz, N. (1981). “The Limits of Population Forecasting,” Population and Development Review, 7(4), pp. 579593.Google Scholar
Koomey, J., Craig, P., Gadgil, A., and Lorenzetti, D. (2003). “Improving Long-Range Energy Modeling: A Plea for Historical Retrospectives,” The Energy Journal, 24, pp. 7592.Google Scholar
Lave, L.B. and Dowlatabadi, H. (1993). “Climate Change: The Effects of Personal Beliefs and Scientific Uncertainty,” Engineering Science &Technology, 27(10), pp. 19621972.Google Scholar
Lave, L.B., Dowlatabadi, H., McRae, G.J., Morgan, M.G., and Rubin, E.S. (1992). “Uncertainties of Climate Change,” Nature, 355, p. 197.Google Scholar
Linderoth, H. (2002). “Forecast Errors in IEA-Countries’ Energy Consumption,” Energy Policy, 30, pp. 5361.Google Scholar
Lutz, W. and Goldstein, J.R. (2004). “Introduction: How to Deal With Uncertainty in Population Forecasting?International Statistical Review, 72(1), pp. 14.Google Scholar
McKitrick, R.R. (1998). “The Econometric Critique of Computable General Equilibrium Modeling: The Role of Functional Forms,” Economic Modelling, 15(4), pp. 543573.Google Scholar
Matthews, H.S. and Hendrickson, C.T. (2015). Life Cycle Assessment: Quantitative Approaches for Decisions That Matter, 241pp. Only available at: https://cmu.app.box.com/s/5mnzyq1y3gcyjrveubf4/1/2746878222.Google Scholar
Meadows, D.H., Meadows, D.L., Randers, J., and Behrens, W.W. (1972). The Limits to Growth: A Report for the Club of Rome’s Project on the Predicament of Mankind, Universe Books, 205pp.Google Scholar
Milford, J.B., Russell, A.G., and McRae, G.J. (1989). “A New Approach to Photochemical Pollution Control: Implications of Spatial Patterns in Pollutant Responses to Reductions in Nitrogen Oxides and Reactive Organic Gas Emissions,” Environmental Science & Technology, 23(10), pp. 12901301.Google Scholar
Morgan, M.G. (2001). “The Neglected Art of Bounding Analysis,” Viewpoint, Environmental Science & Technology, 35, pp. 162A–164A.Google Scholar
Morgan, M.G. and Dowlatabadi, H. (1996). “Learning from Integrated Assessment of Climate Change,” Climatic Change, 34, pp. 337368.Google Scholar
Morgan, M.G. and Henrion, M. (1990). Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis, Cambridge University Press, 332pp.Google Scholar
Morgan, M.G., Kandlikar, M., Risbey, J., and Dowlatabadi, H. (1999). “Why Conventional Tools for Policy Analysis Are Often Inadequate for Problems of Global Change,” Climatic Change, 41, pp. 271281.Google Scholar
Morgan, M.G. and Keith, D. (1995). “Subjective Judgments by Climate Experts,” Environmental Science & Technology, 29(10), pp. 468A–476A.Google Scholar
Morgan, M.G. and McMichael, F.C. (1981). “A Characterization and Critical Discussion of Models and Their Use in Environmental Policy,” Policy Sciences, 14, pp. 345370.Google Scholar
Nordhaus, W.D. and Boyer, J. (2000). Warming the World: Economic Models of Global Warming, MIT Press, 232pp.Google Scholar
O’Neil, B.C. and Desai, M. (2005). “Accuracy of Past Projections of U.S. Energy Consumption,” Energy Policy, 33, pp. 979993.Google Scholar
Parson, E.A. and Fisher-Vanden, K. (1997). “Integrated Assessment Models of Global Climate Change,” Annual Reviews of Energy and the Environment, 22, pp. 589628.Google Scholar
Pindyck, R.S. (2013). “Climate Change Policy: What Do the Models Tell Us?,” Journal of Economic Literature, 51(3), pp. 860872.Google Scholar
Raftery, A.E., Li, N., Ševčíková, H., Gerland, P., and Heilig, G.K. (2012). “Bayesian Probabilistic Population Projections for All Countries,” Proceedings of the National Academy of Sciences, 109(35), pp. 1391513921.Google Scholar
Rodrik, D. (2015). Economics Rules: The Rights and Wrongs of the Dismal Science, W.W. Norton & Company, 253pp.Google Scholar
Rose, S., Turner, D., Blanford, G., Bistline, J., de la Chesnaye, F., and Wilson, T. (2014). Understanding the Social Cost of Carbon: A Technical Assessment – Executive Summary, EPRI, 18pp.Google Scholar
Rubin, E.S. (1991). “Benefit-Cost Implications of Acid Rain Controls: An Evaluation of the NAPAP Integrated Assessment,” Journal of the Air & Waste Management Association, 41(7), pp. 914921.Google Scholar
Rubin, E.S., Bloyd, C.N., Small, M.J., Marnicio, R.J., and Henrion, M. (1990). “Atmospheric Deposition Assessment Model: Applications to Regional Aquatic Acidification in Eastern North America,” in Kamari, J. (ed.), Impact Models to Assess Regional Acidification, Kluwer Academic Publishers, pp. 253284.Google Scholar
Rubin, E.S., Lave, L.B., and Morgan, M.G. (1991). “Keeping Climate Research Relevant,” Issues in Science and Technology, 8(2), pp. 4755.Google Scholar
Rubin, E.S., Small, M.J., Bloyd, C.N., and Henrion, M. (1992). “Integrated Assessment of Acid Deposition Effects on Lake Acidification,” Journal of Environmental Engineering, 118(1), pp. 120134.Google Scholar
Scarf, H.E. and Shoven, J.B. (eds.) (1984). Applied General Equilibrium Analysis, Cambridge University Press, 538pp.Google Scholar
Schnoor, J.L. (1996). Environmental Modeling: Fate and Transport of Pollutants in Water, Air, and Soil, John Wiley & Sons, 682pp.Google Scholar
Schweizer, V. and Morgan, M.G. (2016). “Bounding U.S. Electricity Demand in 2050,” Technological Forecasting & Social Change, pp. 215223.Google Scholar
Seinfeld, J.H. and Pandis, S.N. (2006). Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley, 1203pp.Google Scholar
Simon, H.A. (1981). Science of the Artificial, 2nd ed., MIT press, 247pp.Google Scholar
Smil, V. (2000). “Perils of Long-Range Energy Forecasting: Reflections on Looking Far Ahead,” Technology Forecasting and Social Change, 65, pp. 251264.Google Scholar
Smil, V. (2003). Energy at the Crossroads: Global Perspectives and Uncertainties, MIT Press, 427pp.Google Scholar
Smith, J. and Smith, P. (2007). Introduction to Environmental Modeling, Oxford University Press, 180pp.Google Scholar
Sterman, J.D. (1991). “A Skeptic’s Guide to Computer Models,” Managing a Nation: The Microcomputer Software Catalog, 2, pp. 209229.Google Scholar
Weaver, W. (1948). “Science and Complexity,” American Scientist, 36, pp. 536544.Google Scholar
West, G.R. (1995). “Comparison of Input–Output, Input–Output + Econometric and Computable General Equilibrium Impact Models at the Regional Level,” Economic Systems Research, 7(2), pp. 209227.Google Scholar
Weyant, J.P. (2012). “Lessons Learned from Past Energy-Environmental Inter-Model Comparison Projects: With Opportunities and Challenges Remaining,” Energy Modeling Forum and Department of Management Science and Engineering, Stanford University, 175pp.Google Scholar
Weyant, J. (2015). “Contributions of Integrated Assessment Models,” draft book chapter, Stanford University, 35pp.Google Scholar
Winebrake, J.J. and Sakva, D. (2006). “An Evaluation of Errors in U.S. Energy Forecasts: 1982–2003,” Energy Policy, 34, pp. 34753483.Google Scholar

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