IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-00112129.html
   My bibliography  Save this paper

Hierarchical fusion of expert opinion in the Transferable Belief Model, application on climate sensitivity

Author

Listed:
  • Minh Ha-Duong

    (CIRED - centre international de recherche sur l'environnement et le développement - Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique)

Abstract

This paper examines the fusion of conflicting and not independent expert opinion in the Transferable Belief Model. Regarding procedures that combine opinions symmetrically, when beliefs are bayesian the non-interactive disjunction works better than the non-interactive conjunction, cautious conjunction or Dempster's combination rule.Then a hierarchical fusion procedure based on the partition of experts into schools of thought is introduced, justified by the sociology of science concepts of epistemic communities and competing theories. Within groups, consonant beliefs are aggregated using the cautious conjunction operator, to pool together distinct streams of evidence without assuming that experts are independent. Across groups, the non-interactive disjunction is used, assuming that when several scientific theories compete, they can not be all true at the same time, but at least one will remain. This procedure balances points of view better than averaging: the number of experts holding a view is not essential.This is illustrated with a 16 experts real-world dataset on climate sensitivity from 1995. Climate sensitivity is a key parameter to assess the severity of the global warming issue. Comparing our findings with recent results suggests that, unfortunately, the plausibility that sensitivity is small (below 1.5C) has decreased since 1995, while the plausibility that it is above 4.5C remains high.

Suggested Citation

  • Minh Ha-Duong, 2008. "Hierarchical fusion of expert opinion in the Transferable Belief Model, application on climate sensitivity," Post-Print halshs-00112129, HAL.
    • Handle: RePEc:hal:journl:halshs-00112129
    DOI: 10.1016/j.ijar.2008.05.003
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00112129v3
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-00112129v3/document
    Download Restriction: no
    File URL: https://libkey.io/10.1016/j.ijar.2008.05.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gabriele C. Hegerl & Thomas J. Crowley & William T. Hyde & David J. Frame, 2006. "Climate sensitivity constrained by temperature reconstructions over the past seven centuries," Nature, Nature, vol. 440(7087), pages 1029-1032, April.
    2. Robert T. Clemen & Robert L. Winkler, 1999. "Combining Probability Distributions From Experts in Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 19(2), pages 187-203, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kenneth Gillingham & William D. Nordhaus & David Anthoff & Geoffrey Blanford & Valentina Bosetti & Peter Christensen & Haewon McJeon & John Reilly & Paul Sztorc, 2015. "Modeling Uncertainty in Climate Change: A Multi-Model Comparison," NBER Working Papers 21637, National Bureau of Economic Research, Inc.
    2. Melissa Dell & Benjamin F. Jones & Benjamin A. Olken, 2014. "What Do We Learn from the Weather? The New Climate-Economy Literature," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 740-798, September.
    3. Avner Engel & Shalom Shachar, 2006. "Measuring and optimizing systems' quality costs and project duration," Systems Engineering, John Wiley & Sons, vol. 9(3), pages 259-280, September.
    4. Atanasov, Pavel & Witkowski, Jens & Ungar, Lyle & Mellers, Barbara & Tetlock, Philip, 2020. "Small steps to accuracy: Incremental belief updaters are better forecasters," Organizational Behavior and Human Decision Processes, Elsevier, vol. 160(C), pages 19-35.
    5. Eliseev, Alexey V. & Mokhov, Igor I., 2008. "Eventual saturation of the climate–carbon cycle feedback studied with a conceptual model," Ecological Modelling, Elsevier, vol. 213(1), pages 127-132.
    6. Franz Dietrich & Christian List, 2017. "Probabilistic opinion pooling generalized. Part one: general agendas," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 48(4), pages 747-786, April.
    7. repec:cup:judgdm:v:13:y:2018:i:6:p:607-621 is not listed on IDEAS
    8. Patrick Afflerbach & Christopher Dun & Henner Gimpel & Dominik Parak & Johannes Seyfried, 2021. "A Simulation-Based Approach to Understanding the Wisdom of Crowds Phenomenon in Aggregating Expert Judgment," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 329-348, August.
    9. Chiara Franzoni & Paula Stephan & Reinhilde Veugelers, 2022. "Funding Risky Research," Entrepreneurship and Innovation Policy and the Economy, University of Chicago Press, vol. 1(1), pages 103-133.
    10. Robert F. Bordley, 2009. "Combining the Opinions of Experts Who Partition Events Differently," Decision Analysis, INFORMS, vol. 6(1), pages 38-46, March.
    11. Jason R. W. Merrick & J. Rene van Dorp & Jack Harrald & Thomas Mazzuchi & John E. Spahn & Martha Grabowski, 2000. "A systems approach to managing oil transportation risk in Prince William Sound," Systems Engineering, John Wiley & Sons, vol. 3(3), pages 128-142.
    12. Donnacha Bolger & Brett Houlding, 2016. "Reliability updating in linear opinion pooling for multiple decision makers," Journal of Risk and Reliability, , vol. 230(3), pages 309-322, June.
    13. Robert L. Winkler & Robert T. Clemen, 2004. "Multiple Experts vs. Multiple Methods: Combining Correlation Assessments," Decision Analysis, INFORMS, vol. 1(3), pages 167-176, September.
    14. Ine H. J. Van Der Fels‐Klerx & Louis H. J. Goossens & Helmut W. Saatkamp & Suzan H. S. Horst, 2002. "Elicitation of Quantitative Data from a Heterogeneous Expert Panel: Formal Process and Application in Animal Health," Risk Analysis, John Wiley & Sons, vol. 22(1), pages 67-81, February.
    15. Kenichiro McAlinn & Knut Are Aastveit & Jouchi Nakajima & Mike West, 2020. "Multivariate Bayesian Predictive Synthesis in Macroeconomic Forecasting," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(531), pages 1092-1110, July.
    16. J. Annan & J. Hargreaves, 2011. "On the generation and interpretation of probabilistic estimates of climate sensitivity," Climatic Change, Springer, vol. 104(3), pages 423-436, February.
    17. Jahanbani, Zeinab & Ataee-pour, Majid & Mortazavi, Ali, 2024. "Application of Z-numbers theory to study the influencing criteria in underground mining method selection," Resources Policy, Elsevier, vol. 88(C).
    18. Pennings, Clint L.P. & van Dalen, Jan & Rook, Laurens, 2019. "Coordinating judgmental forecasting: Coping with intentional biases," Omega, Elsevier, vol. 87(C), pages 46-56.
    19. Franz Dietrich & Christian List, 2017. "Probabilistic opinion pooling generalized. Part two: the premise-based approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 48(4), pages 787-814, April.
    20. Bosetti, Valentina & Golub, Alexander & Markandya, Anil & Massetti, Emanuele & Tavoni, Massimo, "undated". "Abatement Cost Uncertainty and Policy Instrument Selection under a Stringent Climate Policy. A Dynamic Analysis," Climate Change Modelling and Policy Working Papers 6383, Fondazione Eni Enrico Mattei (FEEM).
    21. Hongjun Fan & Hossein Enshaei & Shantha Gamini Jayasinghe, 2022. "Formation of Dataset for Fuzzy Quantitative Risk Assessment of LNG Bunkering SIMOPs," Data, MDPI, vol. 7(5), pages 1-13, May.

    More about this item

    Keywords

    climate sensitivity; experts aggregation; Dempster-Shafer; Transferable Belief Model; sensibilité climatique; agrégation des opinions d'expert;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:halshs-00112129. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.