IDEAS home Printed from https://ideas.repec.org/a/cup/jagaec/v41y2009i03p599-611_00.html
   My bibliography  Save this article

Willingness-to-Pay for Attribute Level and Variability: The Case of Mexican Millers' Demand for Hard Red Winter Wheat

Author

Listed:
  • Gallardo, R. Karina
  • Lusk, Jayson L.
  • Holcomb, Rodney B.
  • Rayas-Duarte, Patricia

Abstract

In-person interviews were carried out with Mexican millers who were administered a conjoint-type survey designed to incorporate uncertainty in attribute levels. Two methods were used to model millers' risk preferences: a modified mean-variance approach and an explicit expected utility approach. Controlling for variability, Mexican millers are willing to pay premiums for increases in quality factors such as test weight, protein content, falling number, and dough strength/extensibility. We find millers are not particularly sensitive to changes in the variability of quality characteristics. Out-of-sample forecasts suggest the mean-variance model provides an accurate depiction of actual Mexican imports.

Suggested Citation

  • Gallardo, R. Karina & Lusk, Jayson L. & Holcomb, Rodney B. & Rayas-Duarte, Patricia, 2009. "Willingness-to-Pay for Attribute Level and Variability: The Case of Mexican Millers' Demand for Hard Red Winter Wheat," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(3), pages 599-611, December.
    • Handle: RePEc:cup:jagaec:v:41:y:2009:i:03:p:599-611_00
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1074070800003096/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Guerrero-Baena, M. Dolores & Villanueva, Anastasio J. & Gómez-Limón, José A. & Glenk, Klaus, 2019. "Willingness to pay for improved irrigation water supply reliability: An approach based on probability density functions," Agricultural Water Management, Elsevier, vol. 217(C), pages 11-22.
    2. Roberts, Shane & Brooks, Kathleen & Nogueira, Lia & Walters, Cory G., 2022. "The role of quality characteristics in pricing hard red winter wheat," Food Policy, Elsevier, vol. 108(C).
    3. Agyekum Michael & Jolly Curtis M. & Thompson Henry, 2018. "Aflatoxins and Health Considerations in Consumer Food Choices in Ghana," Journal of Agricultural & Food Industrial Organization, De Gruyter, vol. 16(2), pages 1-12, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cup:jagaec:v:41:y:2009:i:03:p:599-611_00. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/aae .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.