IDEAS home Printed from https://ideas.repec.org/a/oup/ajagec/v95y2013i3p739-754.html
   My bibliography  Save this article

An Analysis of Selectivity in the Productivity Evaluation of Biotechnology: An Application to Corn

Author

Listed:
  • Guanming Shi
  • Jean-Paul Chavas
  • Joseph Lauer
  • Elizabeth Nolan

Abstract

We investigate selectivity bias in the evaluation of biotech hybrid productivity. The analysis is applied to experimental data on Wisconsin corn yields from 1990 to 2010. Relying on a Heckman-like factor that accounts for selectivity, we find evidence of selection bias, indicating that some of the observed yield advantage associated with GM hybrids can be attributed to their conventional genes. We document how the rising market concentration of biotech firms has contributed to increasing selectivity bias in corn yield. The impact, however, is offset by the negative effect of the rising adoption rate of GM corn on selectivity bias. Copyright 2013, Oxford University Press.

Suggested Citation

  • Guanming Shi & Jean-Paul Chavas & Joseph Lauer & Elizabeth Nolan, 2013. "An Analysis of Selectivity in the Productivity Evaluation of Biotechnology: An Application to Corn," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 95(3), pages 739-754.
    • Handle: RePEc:oup:ajagec:v:95:y:2013:i:3:p:739-754
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/ajae/aas169
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Fernandez-Cornejo, Jorge & Valle, Karen, 2014. "A Hedonic Model of Corn Seed Prices," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 169667, Agricultural and Applied Economics Association.
    2. Paul Vincelli, 2016. "Genetic Engineering and Sustainable Crop Disease Management: Opportunities for Case-by-Case Decision-Making," Sustainability, MDPI, vol. 8(5), pages 1-22, May.
    3. Xingliang Ma & Melinda Smale & David J. Spielman & Patricia Zambrano & Hina Nazli & Fatima Zaidi, 2017. "A Question of Integrity: Variants of Bt Cotton, Pesticides and Productivity in Pakistan," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(2), pages 366-385, June.
    4. Hutchins, Jared P. & Irwin, Scott H., 2022. "Productivity Growth from Genetic Improvement: Estimates from Soybean Experiment Station Data," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322202, Agricultural and Applied Economics Association.
    5. Fernandez-Cornejo, Jorge & Livingston, Michael J. & Mitchell, Lorraine & Wechsler, Seth, 2014. "Genetically Engineered Crops in the United States," Economic Research Report 164263, United States Department of Agriculture, Economic Research Service.
    6. Elizabeth Nolan & Paulo Santos, 2019. "Genetic modification and yield risk: A stochastic dominance analysis of corn in the USA," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-10, October.

    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:oup:ajagec:v:95:y:2013:i:3:p:739-754. 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: Oxford University Press (email available below). General contact details of provider: https://edirc.repec.org/data/aaeaaea.html .

    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.