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How Well Can Experts Predict Farmers’ Choices in Risky Gambles?

Author

Listed:
  • Henning Schaak

    (Department of Economics and Social Sciences, University of Natural Resources and Life Sciences, Vienna)

  • Jens Rommel

    (Department of Economics, Swedish University of Agricultural Sciences)

  • Julian Sagebiel

    (Biodiversity Economics, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig)

  • Jesus Barreiro-Hurlé

    (European Commission, Joint Research Centre (JRC))

  • Douadia Bougherara

    (CEE-M, Univ. Montpellier, CNRS, INRAE, Institut Agro)

  • Luigi Cemablo

    (Department of Agricultural Sciences, University of Naples Federico II)

  • Marija Cerjak

    (Faculty of Agriculture, University of Zagreb)

  • Tajana Čop

    (Faculty of Agriculture, University of Zagreb)

  • Mikołaj Czajkowski

    (Faculty of Economic Sciences, University of Warsaw)

  • María Espinosa-Goded

    (Faculty of Economic and Business Science, University of Sevilla)

  • Julia Höhler

    (Business Economics Group, Wageningen University & Research)

  • Carl-Johan Lagerkvist

    (Department of Economics, Swedish University of Agricultural Sciences)

  • Macario Rodriguez-Entrena

    (WEARE - Water, Environmental, and Agricultural Resources Economics Research Group, Universidad de Córdoba)

  • Annika Tensi

    (Business Economics Group, Wageningen University & Research)

  • Sophie Thoyer

    (CEE-M, Univ. Montpellier, CNRS, INRAE, Institut Agro)

  • Marina Tomić Maksan

    (Faculty of Agriculture, University of Zagreb)

  • Riccardo Vecchio

    (Department of Agricultural Sciences, University of Naples Federico II)

  • Katarzyna Zagórska

    (Faculty of Economic Sciences, University of Warsaw)

Abstract

Risk is ubiquitous in agriculture and a core interest of agricultural economists. While farmers’ risk preferences are well studied, there is limited knowledge on the perspectives of other stakeholders on farmers’ risk preferences. We address this gap by eliciting predictions for a multiple-price-list task from 561 students, farm advisors, and experts from Italy, Poland, Croatia, Spain, France, Sweden, and the Netherlands. First, we investigate whether the risk preferences of farmers from different European production systems differ in terms of predictability for the experts. Second, we compare the predictions of different groups of experts, as well as their accuracy. Third, we evaluate whether the accuracy of predictions can be improved by changing incentive mechanisms. Overall, we find substantial variation in individual predictions. Yet, average predictions are close to the averages of the observed responses of farmers. We find that an international group of researchers in experimental economics provides more accurate predictions than farm advisors and other experts or students of agriculture. Differences in predictions by production systems are small. Incentivizing predictions by either a tournament scheme (the best prediction receives a reward) or high accuracy (randomly selected participants are paid depending on the quality of their prediction) do not strongly affect the accuracy, but may slightly reduce noise in the predictions.

Suggested Citation

  • Henning Schaak & Jens Rommel & Julian Sagebiel & Jesus Barreiro-Hurlé & Douadia Bougherara & Luigi Cemablo & Marija Cerjak & Tajana Čop & Mikołaj Czajkowski & María Espinosa-Goded & Julia Höhler & Car, 2023. "How Well Can Experts Predict Farmers’ Choices in Risky Gambles?," Working Papers 2023-03, Faculty of Economic Sciences, University of Warsaw.
  • Handle: RePEc:war:wpaper:2023-03
    as

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    File URL: https://www.wne.uw.edu.pl/download_file/2547/0
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    References listed on IDEAS

    as
    1. Marc F. Bellemare & Yu Na Lee & David R. Just, 2020. "Producer Attitudes Toward Output Price Risk: Experimental Evidence from the Lab and from the Field," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(3), pages 806-825, May.
    2. Géraldine Bocquého & Florence Jacquet & Arnaud Reynaud, 2014. "Expected utility or prospect theory maximisers? Assessing farmers' risk behaviour from field-experiment data," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(1), pages 135-172, February.
    3. Tomomi Tanaka & Colin F. Camerer & Quang Nguyen, 2010. "Risk and Time Preferences: Linking Experimental and Household Survey Data from Vietnam," American Economic Review, American Economic Association, vol. 100(1), pages 557-571, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Risk attitudes; Expert predictions; Expert forecasts; Multiple prices lists; Meta-science; Experimental economics;
    All these keywords.

    JEL classification:

    • Q19 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Other
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C99 - Mathematical and Quantitative Methods - - Design of Experiments - - - Other

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