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Potentials and Limits of Bayesian Networks to Deal with Uncertainty in the Assessment of Climate Change Adaptation Policies

Author

Listed:
  • Michela Catenacci

    (Fondazione Eni Enrico Mattei)

  • Carlo Giupponi

    (Ca' Foscari University Centre for Environmental Economics and Management, and Fondazione Eni Enrico Mattei)

Abstract

Bayesian networks (BNs) have been increasingly applied to support management and decision-making processes under conditions of environmental variability and uncertainty, providing logical and holistic reasoning in complex systems since they succinctly and effectively translate causal assertions between variables into patterns of probabilistic dependence. Through a theoretical assessment of the features and the statistical rationale of BNs, and a review of specific applications to ecological modelling, natural resource management, and climate change policy issues, the present paper analyses the effectiveness of the BN model as a synthesis framework, which would allow the user to manage the uncertainty characterising the definition and implementation of climate change adaptation policies. The review will let emerge the potentials of the model to characterise, incorporate and communicate the uncertainty, with the aim to provide an efficient support to an informed and transparent decision making process. The possible drawbacks arising from the implementation of BNs are also analysed, providing potential solutions to overcome them.

Suggested Citation

  • Michela Catenacci & Carlo Giupponi, 2010. "Potentials and Limits of Bayesian Networks to Deal with Uncertainty in the Assessment of Climate Change Adaptation Policies," Working Papers 2010.7, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2010.7
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    References listed on IDEAS

    as
    1. Carraro, Carlo & Sgobbi, Alessandra, 2008. "Climate Change Impacts and Adaptation Strategies In Italy. An Economic Assessment," Climate Change Modelling and Policy Working Papers 6373, Fondazione Eni Enrico Mattei (FEEM).
    2. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    3. Anand Patwardhan & Mitchell J. Small, 1992. "Bayesian Methods for Model Uncertainty Analysis with Application to Future Sea Level Rise," Risk Analysis, John Wiley & Sons, vol. 12(4), pages 513-523, December.
    4. Aristides Patrinos & Anjuli Bamzai, 2005. "Policy needs robust climate science," Nature, Nature, vol. 438(7066), pages 285-285, November.
    5. William D. Nordhaus, 2006. "The "Stern Review" on the Economics of Climate Change," NBER Working Papers 12741, National Bureau of Economic Research, Inc.
    6. 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 (IfW Kiel).
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Heuson, Clemens & Gawel, Erik & Gebhardt, Oliver & Hansjürgens, Bernd & Lehmann, Paul & Meyer, Volker & Schwarze, Reimund, 2012. "Fundamental questions on the economics of climate adaptation: Outlines of a new research programme," UFZ Reports 05/2012, Helmholtz Centre for Environmental Research (UFZ).
    2. Heuson, Clemens & Gawel, Erik & Gebhardt, Oliver & Hansjürgens, Bernd & Lehmann, Paul & Meyer, Volker & Schwarze, Reimund, 2012. "Ökonomische Grundfragen der Klimaanpassung: Umrisse eines neuen Forschungsprogramms," UFZ Reports 02/2012, Helmholtz Centre for Environmental Research (UFZ).

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    More about this item

    Keywords

    Adaptation to Climate Change; Bayesian Network; Uncertainty;
    All these keywords.

    JEL classification:

    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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