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Ambiguous Aggregation of Expert Opinions: The Case of Optimal R&D Investment


  • Stergios Athanassoglou

    (Fondazione Eni Enrico Mattei and Euro-Mediterranean Center for Climate Change)

  • Valentina Bosetti

    (Fondazione Eni Enrico Mattei and Euro-Mediterranean Center for Climate Change)

  • Gauthier de Maere d'Aertrycke

    (Fondazione Eni Enrico Mattei and Euro-Mediterranean Center for Climate Change, Italy)


How should a decision-maker allocate R&D funds when a group of experts provides divergent estimates on a technology's potential effectiveness? To address this question, we propose a simple decision-theoretic framework that takes into account ambiguity over the aggregation of expert opinion and a decision-maker's attitude towards it. In line with the paper's focus on R&D investment, decision variables in our model may affect experts' subjective probability distributions of the future potential of a technology. Using results from convex optimization, we are able to establish a number of analytical results including a closed-form expression of our model's value function, as well as a thorough investigation of its differentiability properties. We apply our framework to original data from a recent expert elicitation survey on solar technology. The analysis suggests that more aggressive investment in solar technology R&D is likely to yield significant dividends even, or rather especially, after taking ambiguous aggregation into account.

Suggested Citation

  • Stergios Athanassoglou & Valentina Bosetti & Gauthier de Maere d'Aertrycke, 2012. "Ambiguous Aggregation of Expert Opinions: The Case of Optimal R&D Investment," Working Papers 2012.04, Fondazione Eni Enrico Mattei.
  • Handle: RePEc:fem:femwpa:2012.04

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    References listed on IDEAS

    1. Baker, Erin & Chon, Haewon & Keisler, Jeffrey, 2009. "Advanced solar R&D: Combining economic analysis with expert elicitations to inform climate policy," Energy Economics, Elsevier, vol. 31(Supplemen), pages 37-49.
    2. Valentina Bosetti, Carlo Carraro, Marzio Galeotti, Emanuele Massetti, Massimo Tavoni, 2006. "A World induced Technical Change Hybrid Model," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 13-38.
    3. Baker, Erin & Keisler, Jeffrey M., 2011. "Cellulosic biofuels: Expert views on prospects for advancement," Energy, Elsevier, vol. 36(1), pages 595-605.
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    More about this item


    Aggregation; Ambiguity; R&D; Expert Opinions; Convex/Conic Optimization;

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources

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