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Factors Affecting The Likelihood Of Corn Rootworm Bt Seed Adoption

Author

Listed:
  • Payne, Tim
  • Fernandez-Cornejo, Jorge
  • Daberkow, Stan G.

Abstract

The likelihood of adopting corn rootworm (CRW) Bt seed technology was analyzed using an ordered logit model. Data used to estimate the model came from USDA's 2001 Agricultural Resource Management Survey. Statistically significant variables include operator age, farm type, farm size, rootworm loss and current treatment for rootworm, off farm labor, and Bt technology for corn borer. The likelihood of adoption was not related to crop rotation, tillage system, new variant CRW region, or education.

Suggested Citation

  • Payne, Tim & Fernandez-Cornejo, Jorge & Daberkow, Stan G., 2003. "Factors Affecting The Likelihood Of Corn Rootworm Bt Seed Adoption," 2003 Annual Meeting, July 13-16, 2003, Denver, Colorado 35983, Western Agricultural Economics Association.
    • Handle: RePEc:ags:waeade:35983
    DOI: 10.22004/ag.econ.35983
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    Cited by:

    1. Joshua D. Detre & Hiroki Uematsu & Ashok K. Mishra, 2011. "The influence of GM crop adoption on the profitability of farms operated by young and beginning farmers," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(1), pages 41-61, May.
    2. Krishna, Vijesh V. & Qaim, Matin, 2007. "Estimating the adoption of Bt eggplant in India: Who Benefits from public-private partnership?," Food Policy, Elsevier, vol. 32(5-6), pages 523-543.
    3. Guanming Shi & Jean-paul Chavas & Kyle Stiegert, 2010. "An Analysis of the Pricing of Traits in the U.S. Corn Seed Market," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(5), pages 1324-1338.
    4. Matty Demont & Marie Cerovska & Wim Daems & Koen Dillen & József Fogarasi & Erik Mathijs & František Muška & Josef Soukup & Eric Tollens, 2008. "Ex Ante Impact Assessment under Imperfect Information: Biotechnology in New Member States of the EU," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(3), pages 463-486, September.
    5. Luh, Yir-Hueih, 2017. "The Impact Of Education On Agricultural Productivity: Evidence From East Asian Economies," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 5(4), October.
    6. Bola Amoke Awotide & Adebayo Ogunniyi & Kehinde Oluseyi Olagunju & Lateef Olalekan Bello & Amadou Youssouf Coulibaly & Alexander Nimo Wiredu & Bourémo Kone & Aly Ahamadou & Victor Manyong & Tahirou Ab, 2022. "Evaluating the Heterogeneous Impacts of Adoption of Climate-Smart Agricultural Technologies on Rural Households’ Welfare in Mali," Agriculture, MDPI, vol. 12(11), pages 1-16, November.
    7. Suntornpithug, Pasu & Kalaitzandonakes, Nicholas G., 2009. "Understanding the Adoption of Cotton Biotechnologies in the US: Firm Level Evidence," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 10(1), pages 1-17.
    8. Zavale, Helder & Mabaya, Edward T. & Christy, Ralph D., 2005. "Adoption of Improved Maize Seed by Smallholder Farmers in Mozambique," Staff Papers 121065, Cornell University, Department of Applied Economics and Management.
    9. Oliver Musshoff & Norbert Hirschauer, 2011. "A behavioral economic analysis of bounded rationality in farm financing decisions," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 71(1), pages 62-83, May.

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    Keywords

    Crop Production/Industries;

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