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A Meta-analysis of the Risk Aversion Coefficients of Natural Resource Managers Evaluated by Stated Preference Methods

Author

Listed:
  • Marielle Brunette

    (Laboratoire d'Economie Forestière, INRA - AgroParisTech)

  • Johanna Choumert

    (i) Economic Development Initiatives (E.D.I.), P.O. Box 393, Bukoba, Kagera region, Tanzania (ii) Centre d'Études et de Recherches sur le Développement International (CERDI), Université d'Auvergne.)

  • Stéphane Couture

    (INRA, UR 875 Applied Mathematics and Computer Science laboratory)

  • Claire Montagne-Huck

    (Laboratoire d'Economie Forestière, INRA - AgroParisTech)

Abstract

Although they have been widely studied, the attitudes of natural resource managers towards risk remain a common research topic through stated preference methods. The relationship between the risk aversion coefficients of natural resource managers, their characteristics, and the different studies has still not been elucidated. Using 63 studies, we shed light on why the partial, absolute and relative estimated risk aversion coefficients of natural resource managers differ. We investigated, through a meta-regression, the incidence of choices made by authors (elicitation method, measure of risk aversion coefficient, payoff choice) and characteristics of the natural resource managers (geographical location, type of activities) on the estimated risk aversion coefficients. Our results show that the model for the relative risk aversion coefficient has a stronger explanatory power than those for partial and absolute coefficients. The three coefficients are mainly explained by the type of publication, the elicitation procedure and the type of activities. However, the level of economic development of the country and the type of payoff (i.e., hypothetical or real) seem to have no impact whatsoever on the estimated coefficient. We also provide ranges for each type of risk aversion coefficient – absolute, partial and relative.

Suggested Citation

  • Marielle Brunette & Johanna Choumert & Stéphane Couture & Claire Montagne-Huck, 2015. "A Meta-analysis of the Risk Aversion Coefficients of Natural Resource Managers Evaluated by Stated Preference Methods," Working Papers - Cahiers du LEF 2015-13, Laboratoire d'Economie Forestiere, AgroParisTech-INRA, revised 2015.
  • Handle: RePEc:lef:wpaper:2015-13
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    File URL: http://www6.nancy.inra.fr/lef/Cahiers-du-LEF/2015/2015-13
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    Citations

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    Cited by:

    1. Benjamin Dequiedt & Emmanuel Servonnat, 2016. "Risk as a limit or an opportunity to mitigate GHG emissions? The case of fertilisation in agriculture," Working Papers 1606, Chaire Economie du climat.
    2. Caroline Roussy & Aude Ridier & Karim Chaib & Marie Boyet, 2018. "Marketing contracts and risk management for cereal producers," Agribusiness, John Wiley & Sons, Ltd., vol. 34(3), pages 616-630, June.
    3. Johanna Choumert & Pascale Phelinas, 2018. "Volcanic hazards, land and labor," Working Papers halshs-01845041, HAL.
    4. Lefebvre, Marianne & Midler, Estelle & Bontems, Philippe, 2020. "Adoption of environmentally-friendly agricultural practices with background risk: experimental evidence," TSE Working Papers 20-1079, Toulouse School of Economics (TSE).
    5. Sauter, Philipp A. & Hermann, Daniel & Mußhoff, Oliver, 2018. "Are foresters really risk-averse? A multi-method analysis and a cross-occupational comparison," Forest Policy and Economics, Elsevier, vol. 95(C), pages 37-45.

    More about this item

    Keywords

    Risk preferences; expected utility theory; stated-preference methods; metaanalysis; meta-regression; natural resources.;
    All these keywords.

    JEL classification:

    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

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