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Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data


  • Bocqueho, Geraldine
  • Jacquet, Florence
  • Reynaud, Arnaud


We elicit risk preferences of French farmers in a field experimental setting under expected utility theory and cumulative prospect theory. We use two different estimation methods, namely the interval approach and the estimation of a random preference model. On average, farmers are risk averse and loss averse. They also exhibit an inverse S-shaped probability weighting function, meaning that they tend to overweight small probabilities and underweight high probabilities. We infer from our results that CPT explains farmers’ behaviour better than EUT in the context of our experiment. We also investigate how preferences correlate with individual socio-demographic characteristics. We find that education and agricultural innovation are negatively linked with risk aversion. Our results also show that age, education, household size and the level of secured income tend to lower farmers’ loss aversion. Finally, older farmers and farmers with large farms distort probabilities less than the others. These findings contribute to the literature which compares expected utility with competing decision theories. They also give important insights into farmers’ behaviour towards risk, which is critical for relevant public policy design.

Suggested Citation

  • Bocqueho, Geraldine & Jacquet, Florence & Reynaud, Arnaud, 2011. "Expected Utility or Prospect Theory Maximizers? Results from a Structural Model based on Field-experiment Data," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 114257, European Association of Agricultural Economists.
  • Handle: RePEc:ags:eaae11:114257

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    References listed on IDEAS

    1. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
    2. Francisco Galarza, 2009. "Choices under risk in rural peru," Artefactual Field Experiments 00047, The Field Experiments Website.
    3. Quiggin, John, 1982. "A theory of anticipated utility," Journal of Economic Behavior & Organization, Elsevier, vol. 3(4), pages 323-343, December.
    4. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-1289, November.
    5. 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.
    6. Kahneman, Daniel & Tversky, Amos, 1979. "Prospect Theory: An Analysis of Decision under Risk," Econometrica, Econometric Society, vol. 47(2), pages 263-291, March.
    7. Hey, John D & Orme, Chris, 1994. "Investigating Generalizations of Expected Utility Theory Using Experimental Data," Econometrica, Econometric Society, vol. 62(6), pages 1291-1326, November.
    8. Colin Camerer, 1998. "Bounded Rationality in Individual Decision Making," Experimental Economics, Springer;Economic Science Association, vol. 1(2), pages 163-183, September.
    9. Nguyen, Quang, 2009. "Do fishermen have different preferences?: Insights from an experimental study and household data," MPRA Paper 16012, University Library of Munich, Germany.
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    Cited by:

    1. Caroline Roussy & Aude Ridier & Karim Chaïb, 2014. "Adoption d’innovations par les agriculteurs : rôle des perceptions et des préférences," Post-Print hal-01123427, HAL.
    2. Douadia Bougherara & Xavier Gassmann & Laurent Piet, 2011. "A structural estimation of French farmers’ risk preferences: an artefactual field experiment," Working Papers SMART - LERECO 11-06, INRA UMR SMART-LERECO.
    3. Aude Ridier & Karim Chaib & Caroline Roussy, 2012. "The adoption of innovative cropping systems under price and production risks: a dynamic model of crop rotation choice," Working Papers hal-01208817, HAL.
    4. Caroline Roussy & Aude Ridier & Karim Chaïb & Arnaud Reynaud & Stéphane Couture, 2012. "A methodological way of evaluating innovative cropping systems integrating risk beliefs and risk preferences," Post-Print hal-01133976, HAL.

    More about this item


    risk preferences; field experiment; experimental economics; prospect theory; Risk and Uncertainty; C91; D81; J16; Q12;

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • J16 - Labor and Demographic Economics - - Demographic Economics - - - Economics of Gender; Non-labor Discrimination
    • 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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