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Investment decision making under deep uncertainty -- application to climate change

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  • Hallegatte, Stephane
  • Shah, Ankur
  • Lempert, Robert
  • Brown, Casey
  • Gill, Stuart

Abstract

While agreeing on the choice of an optimal investment decision is already difficult for any diverse group of actors, priorities, and world views, the presence of deep uncertainties further challenges the decision-making framework by questioning the robustness of all purportedly optimal solutions. This paper summarizes the additional uncertainty that is created by climate change, and reviews the tools that are available to project climate change (including downscaling techniques) and to assess and quantify the corresponding uncertainty. Assuming that climate change and other deep uncertainties cannot be eliminated over the short term (and probably even over the longer term), it then summarizes existing decision-making methodologies that are able to deal with climate-related uncertainty, namely cost-benefit analysis under uncertainty, cost-benefit analysis with real options, robust decision making, and climate informed decision analysis. It also provides examples of applications of these methodologies, highlighting their pros and cons and their domain of applicability. The paper concludes that it is impossible to define the"best"solution or to prescribe any particular methodology in general. Instead, a menu of methodologies is required, together with some indications on which strategies are most appropriate in which contexts. This analysis is based on a set of interviews with decision-makers, in particular World Bank project leaders, and on a literature review on decision-making under uncertainty. It aims at helping decision-makers identify which method is more appropriate in a given context, as a function of the project's lifetime, cost, and vulnerability.

Suggested Citation

  • Hallegatte, Stephane & Shah, Ankur & Lempert, Robert & Brown, Casey & Gill, Stuart, 2012. "Investment decision making under deep uncertainty -- application to climate change," Policy Research Working Paper Series 6193, The World Bank.
  • Handle: RePEc:wbk:wbrwps:6193
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    References listed on IDEAS

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    Cited by:

    1. Koppelaar, Rembrandt H.E.M. & Keirstead, James & Shah, Nilay & Woods, Jeremy, 2016. "A review of policy analysis purpose and capabilities of electricity system models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 1531-1544.
    2. repec:eee:juipol:v:51:y:2018:i:c:p:51-60 is not listed on IDEAS
    3. Dethier, Jean-Jacques & Morrill, Curtis, 2012. "The great recession and the future of cities," Policy Research Working Paper Series 6256, The World Bank.
    4. Sussman Fran & Weaver Christopher P. & Grambsch Anne, 2014. "Challenges in applying the paradigm of welfare economics to climate change," Journal of Benefit-Cost Analysis, De Gruyter, vol. 5(3), pages 347-376, December.
    5. J. Jäger & M. Rounsevell & P. Harrison & I. Omann & R. Dunford & M. Kammerlander & G. Pataki, 2015. "Assessing policy robustness of climate change adaptation measures across sectors and scenarios," Climatic Change, Springer, vol. 128(3), pages 395-407, February.
    6. Butler, C. & Demski, C. & Parkhill, K. & Pidgeon, N. & Spence, A., 2015. "Public values for energy futures: Framing, indeterminacy and policy making," Energy Policy, Elsevier, vol. 87(C), pages 665-672.
    7. Bhave, Ajay Gajanan & Conway, Declan & Dessai, Suraje & Stainforth, David A., 2017. "Barriers and opportunities for robust decision making approaches to support climate change adaptation in the developing world," LSE Research Online Documents on Economics 68318, London School of Economics and Political Science, LSE Library.
    8. Jan Kwakkel & Marjolijn Haasnoot & Warren Walker, 2015. "Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world," Climatic Change, Springer, vol. 132(3), pages 373-386, October.
    9. Stéphane Hallegatte, 2012. "An exploration of the link between development, economic growth, and natural risk," Post-Print hal-00802047, HAL.
    10. repec:spr:climat:v:144:y:2017:i:4:d:10.1007_s10584-017-2062-5 is not listed on IDEAS
    11. Kwakkel, J.H. & Cunningham, S.C., 2016. "Improving scenario discovery by bagging random boxes," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 124-134.
    12. Cira,Dean A. & Kalra,Nidhi Rajiv & Lempert,Robert J. & Lotsch,Alexander & Mao, Zhimin & Peyraud, Suzanne & Bach,Sinh Tan, 2013. "Ensuring robust flood risk management in Ho Chi Minh city," Policy Research Working Paper Series 6465, The World Bank.
    13. Lempert Robert J., 2014. "Embedding (some) benefit-cost concepts into decision support processes with deep uncertainty," Journal of Benefit-Cost Analysis, De Gruyter, vol. 5(3), pages 487-514, December.
    14. Bonzanigo, Laura & Kalra, Nidhi, 2014. "Making informed investment decisions in an uncertain world : a short demonstration," Policy Research Working Paper Series 6765, The World Bank.
    15. Thomas D. Pol & Ekko C. Ierland & Silke Gabbert, 2017. "Economic analysis of adaptive strategies for flood risk management under climate change," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(2), pages 267-285, February.
    16. Dittrich, Ruth & Wreford, Anita & Moran, Dominic, 2016. "A survey of decision-making approaches for climate change adaptation: Are robust methods the way forward?," Ecological Economics, Elsevier, vol. 122(C), pages 79-89.
    17. World Bank, 2012. "Inclusive Green Growth : The Pathway to Sustainable Development," World Bank Publications, The World Bank, number 6058.

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    Keywords

    Climate Change Economics; Climate Change Mitigation and Green House Gases; Science of Climate Change; Global Environment Facility; Water Supply and Sanitation Governance and Institutions;

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