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Cognitive Dissonance as a Means of Reducing Hypothetical Bias



Hypothetical bias is a persistent problem in stated preference studies. We propose and test a method for reducing hypothetical bias based on the cognitive dissonance literature in social psychology. A central element of this literature is that people prefer not to take inconsistent stands and will change their attitudes and behavior to make them consistent. We find that participants in a stated preference willingness-to-pay study, when told that a nonhypothetical study of similar goods would follow, state significantly lower willingness to pay than participants not so informed. In other words, participants adjust their stated willingness to pay to avoid cognitive dissonance from taking inconsistent stands on their willingness to pay for the good being offered.

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  • Frode Alfnes & Chengyan Yue & Helen H. Jensen, 2009. "Cognitive Dissonance as a Means of Reducing Hypothetical Bias," Center for Agricultural and Rural Development (CARD) Publications 09-wp486, Center for Agricultural and Rural Development (CARD) at Iowa State University.
  • Handle: RePEc:ias:cpaper:09-wp486

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    References listed on IDEAS

    1. Yue, Chengyan & Alfnes, Frode & Jensen, Helen H., 2009. "Discounting Spotted Apples: Investigating Consumers’ Willingness to Accept Cosmetic Damage in an Organic Product," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(01), April.
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    7. Frode Alfnes, 2009. "Valuing product attributes in Vickrey auctions when market substitutes are available," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 36(2), pages 133-149, June.
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    Cited by:

    1. Magdalena Brzozowicz & Michał Krawczyk & Przemysław Kusztelak, 2017. "Do anchors hold for real? Anchoring effect and hypothetical bias in declared WTP," Working Papers 2017-24, Faculty of Economic Sciences, University of Warsaw.
    2. Celine Michaud & Daniel Llerena & Iragael Joly, 2013. "Willingness to pay for environmental attributes of non-food agricultural products: a real choice experiment," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 40(2), pages 313-329, March.
    3. Kirsten, Johann F. & Vermeulen, Hester & Van Zyl, Karlien & Du Randt, Gerrie & Du Plessis, H. & Weissnar, Tessa, 2012. "The economic potential for an origin based marketing and certification system for a meat product in South Africa: Perceptions, preferences, and experiments," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 125764, International Association of Agricultural Economists.
    4. Jussila Hammes , Johanna, 2017. "The impact of career concerns and cognitive dissonance on bureaucrats’ use of cost-benefit analysis," Working papers in Transport Economics 2017:5, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    5. Sckokai, Paolo & Veneziani, Mario & Moro, Daniele & Castellari, Elena, 2014. "Consumer willingness to pay for food safety: the case of mycotoxins in milk," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), issue 1, April.
    6. Greer Gosnell, 2017. "Be who you ought or be who you are? Environmental framing and cognitive dissonance in going paperless," GRI Working Papers 269, Grantham Research Institute on Climate Change and the Environment.
    7. Krawczyk, Michał, 2012. "Testing for hypothetical bias in willingness to support a reforestation program," Journal of Forest Economics, Elsevier, vol. 18(4), pages 282-289.
    8. Moser, Riccarda & Raffaelli, Roberta & Notaro, Sandra, 2010. "The Role Of Production Methods In Fruit Purchasing Behaviour: Hypothetical Vs Actual Consumers’ Preferences And Stated Minimum Requirements," 115th Joint EAAE/AAEA Seminar, September 15-17, 2010, Freising-Weihenstephan, Germany 116426, European Association of Agricultural Economists;Agricultural and Applied Economics Association.

    More about this item


    apples; cognitive consistency; hypothetical bias; instrument calibration; willingness to pay.;

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • Q13 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Markets and Marketing; Cooperatives; Agribusiness
    • Q51 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Valuation of Environmental Effects


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