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Competing theories of risk preferences and the demand for crop insurance: Experimental evidence from Peru

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  • Petraud, Jean
  • Boucher, Stephen
  • Carter, Michael

Abstract

Low demand for index insurance in several recent pilot programs has created a puzzle for development economists and policy makers concerned with enhancing farmers risk management capacity in low-income economies. This paper contributes to the resolution of this puzzle by providing empirical evidence on the relative effectiveness of two primary frameworks for modeling decision-making under uncertainty. Specifically, we test whether features of Cumulative Prospect Theory (CPT), or Expected Utility Theory (EUT), better predict farmers' demand for crop insurance. Whereas in EUT, risk preferences can be represented by a single risk aversion parameter, in CPT they are determined by at least four components: probability weighting, the curvature of a utility function, a reference income and loss aversion. The data come from a series of unframed and framed lotteries played with 480 small-holder cotton farmers in southern Peru. The unframed risk games allow us to measure individual-specific preference parameters, for both theories. We use these parameters to generate predictions of farmers' choices in two framed insurance games in which farmers choose to purchase one of two available insurance contracts or to purchase no insurance. In the first game, farmers' earnings are framed as gross revenues and are always positive, i.e., this game is played over gains. In the second game, earnings are framed as net revenues and may be either positive or negative so that this is a game played over mixed prospects. We test the relative performance of the two theories by comparing the predictions of farmers' choices versus their actual choices in the insurance games. An important finding with respect to marketing of insurance contracts is that framing incomes as net revenues instead of gross revenues increases the CPT predicted demand by 24%. In the actual insurance games however, only 8% more farmers chose insurance in the net revenues frame. We find that neither theory is a particularly strong predictor of insurance choices, although EUT fares better than CPT for better educated farmers.

Suggested Citation

  • Petraud, Jean & Boucher, Stephen & Carter, Michael, 2015. "Competing theories of risk preferences and the demand for crop insurance: Experimental evidence from Peru," 2015 Conference, August 9-14, 2015, Milan, Italy 211383, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae15:211383
    DOI: 10.22004/ag.econ.211383
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    Cited by:

    1. Michael R. CARTER & Alain de JANVRY & Elisabeth SADOULET & Alexandros SARRIS, 2014. "Index-based weather insurance for developing countries: A review of evidence and a set of propositions for up-scaling," Working Papers P111, FERDI.
    2. Elena Serfilippi & Michael Carter & Catherine Guirkinger, 2018. "Insurance Contracts when Individuals “Greatly Value” Certainty: Results from a Field Experiment in Burkina Faso," NBER Working Papers 25026, National Bureau of Economic Research, Inc.
    3. Che, Yuyuan & Feng, Hongli & Hennessy, David A., 2017. "The Geography and Psychology of Participation in U.S. Federal Crop Insurance Programs," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259190, Agricultural and Applied Economics Association.
    4. Mankaï, Selim & Marchand, Sébastien & Le, Ngoc Ha, 2024. "Valuing insurance against small probability risks: A meta-analysis," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 109(C).
    5. Freudenreich, Hanna & Musshoff, Oliver & Wiercinski, Ben, 2017. "The Relationship between Farmers' Shock Experiences and their Uncertainty Preferences - Experimental Evidence from Mexico," GlobalFood Discussion Papers 256212, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    6. Tobias Dalhaus & Barry J Barnett & Robert Finger, 2020. "Behavioral weather insurance: Applying cumulative prospect theory to agricultural insurance design under narrow framing," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-25, May.
    7. Yuyuan Che & Hongli Feng & David A. Hennessy, 2020. "Recency effects and participation at the extensive and intensive margins in the U.S. Federal Crop Insurance Program," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 52-85, January.
    8. Goodrich, Brittney K. & Yu, Jisang, 2018. "Risk Preferences and the Participation Pattern of Rainfall Index Insurance," 2018 Annual Meeting, August 5-7, Washington, D.C. 273879, Agricultural and Applied Economics Association.
    9. Huo, Ran & Colson, Gregory J., 2018. "Insurance Demand over Varying Coverage Levels: Experimental Evidence From China," 2018 Annual Meeting, August 5-7, Washington, D.C. 274476, Agricultural and Applied Economics Association.
    10. Xiaodong Du & Hongli Feng & David A. Hennessy, 2017. "Rationality of Choices in Subsidized Crop Insurance Markets," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 99(3), pages 732-756.
    11. Brittney Goodrich & Jisang Yu & Monte Vandeveer, 2020. "Participation patterns of the rainfall index insurance for pasture, rangeland and forage programme," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 45(1), pages 29-51, January.
    12. Eric Le Fur & J. François Outreville, 2021. "Real Options and Reduction of Basic Risk of Index‐Based Climate Agricultural Insurance," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1658-1671, December.

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