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Uncertainty and economic analysis of climate change: a survey of approaches and findings

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  • Peterson, Sonja

Abstract

The analysis of climate change is confronted with large uncertainties that need to be taken into account to arrive at meaningful policy recommendations. The main contribution of economics to this interdisciplinary task is to provide formal frameworks and techniques for analyzing climate policy in the context of uncertainty. This paper will give an overview of existing approaches and findings to provide a broad picture of what economics can contribute to the debate.

Suggested Citation

  • Peterson, Sonja, 2006. "Uncertainty and economic analysis of climate change: a survey of approaches and findings," Open Access Publications from Kiel Institute for the World Economy 3778, Kiel Institute for the World Economy.
    • Handle: RePEc:zbw:ifwkie:3778
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    2. Eory, Vera & Topp, Cairistiona F. E. & Moran, Dominic & Butler, Adam, 2014. "Assessing uncertainty in the cost-effectiveness of agricultural greenhouse gas mitigation," 88th Annual Conference, April 9-11, 2014, AgroParisTech, Paris, France 170784, Agricultural Economics Society.
    3. Magdalena Zachlod-Jelec & Jakub Boratynski, 2016. "How large and uncertain are costs of 2030 GHG emissions reduction target for the European countries? Sensitivity analysis in a global CGE model," MF Working Papers 26, Ministry of Finance in Poland.
    4. Held, Hermann & Kriegler, Elmar & Lessmann, Kai & Edenhofer, Ottmar, 2009. "Efficient climate policies under technology and climate uncertainty," Energy Economics, Elsevier, vol. 31(Supplemen), pages 50-61.
    5. Scott, Michael J. & Daly, Don S. & Hathaway, John E. & Lansing, Carina S. & Liu, Ying & McJeon, Haewon C. & Moss, Richard H. & Patel, Pralit L. & Peterson, Marty J. & Rice, Jennie S. & Zhou, Yuyu, 2015. "Calculating impacts of energy standards on energy demand in U.S. buildings with uncertainty in an integrated assessment model," Energy, Elsevier, vol. 90(P2), pages 1682-1694.
    6. Martina Linnenluecke & Andrew Griffiths & Peter Mumby, 2015. "Executives’ engagement with climate science and perceived need for business adaptation to climate change," Climatic Change, Springer, vol. 131(2), pages 321-333, July.
    7. Gren, Ing-Marie & Carlsson, Mattias & Elofsson, Katarina & Munnich, Miriam, 2012. "Stochastic carbon sinks for combating carbon dioxide emissions in the EU," Energy Economics, Elsevier, vol. 34(5), pages 1523-1531.
    8. Halkos, George, 2014. "The Economics of Climate Change Policy: Critical review and future policy directions," MPRA Paper 56841, University Library of Munich, Germany.
    9. Medel, Carlos A., 2011. "The Effects of Global Warming on Fisheries," MPRA Paper 28373, University Library of Munich, Germany.
    10. Price, James & Keppo, Ilkka, 2017. "Modelling to generate alternatives: A technique to explore uncertainty in energy-environment-economy models," Applied Energy, Elsevier, vol. 195(C), pages 356-369.
    11. Tulkens, Philippe & Tulkens, Henry, 2006. "The White House and the Kyoto Protocol: Double Standards on Uncertainties and Their Consequences," Climate Change Modelling and Policy Working Papers 12063, Fondazione Eni Enrico Mattei (FEEM).
    12. Alberth, Stephan & Hope, Chris, 2007. "Climate modelling with endogenous technical change: Stochastic learning and optimal greenhouse gas abatement in the PAGE2002 model," Energy Policy, Elsevier, vol. 35(3), pages 1795-1807, March.
    13. Jo-Ting Huang-Lachmann & Edeltraud Guenther, 2020. "From Dichotomy to an Integrated Approach: Cities’ Benefits of Integrating Climate Change Adaptation and Mitigation," Sustainability, MDPI, vol. 12(18), pages 1-17, September.
    14. Lontzek, Thomas S. & Narita, Daiju, 2009. "The effect of uncertainty on decision making about climate change mitigation: a numerical approach of stochastic control," Kiel Working Papers 1539, Kiel Institute for the World Economy.
    15. Martina K. Linnenluecke & Andrew Griffiths & Monika Winn, 2012. "Extreme Weather Events and the Critical Importance of Anticipatory Adaptation and Organizational Resilience in Responding to Impacts," Business Strategy and the Environment, Wiley Blackwell, vol. 21(1), pages 17-32, January.
    16. Catenacci, Michela & Giupponi, Carlo, 2010. "Potentials and Limits of Bayesian Networks to Deal with Uncertainty in the Assessment of Climate Change Adaptation Policies," Sustainable Development Papers 59385, Fondazione Eni Enrico Mattei (FEEM).
    17. Vera Eory & Cairistiona F. E. Topp & Adam Butler & Dominic Moran, 2018. "Addressing Uncertainty in Efficient Mitigation of Agricultural Greenhouse Gas Emissions," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 627-645, September.
    18. DeCarolis, Joseph F., 2011. "Using modeling to generate alternatives (MGA) to expand our thinking on energy futures," Energy Economics, Elsevier, vol. 33(2), pages 145-152, March.
    19. Miftakhova, Alena, 2021. "Global sensitivity analysis for optimal climate policies: Finding what truly matters," Economic Modelling, Elsevier, vol. 105(C).
    20. Eory, Vera, "undated". "Evaluating the use of marginal abatement cost curves applied to greenhouse gas abatement in agriculture," Working Papers 199777, Scotland's Rural College (formerly Scottish Agricultural College), Land Economy & Environment Research Group.

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    Keywords

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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C60 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - General
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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