Quantifying Adoption Intensity for Weed-Resistance Management Practices and Its Determinants among U.S. Soybean, Corn, and Cotton Farmers

Author

Fengxia Dong (fdong6@wisc.edu), Paul Mitchell (pdmitchell@wisc.edu), Terrance Hurley (tmh@umn.edu) and George B. Frisvold

Journal of Agricultural and Resource Economics, 2016, vol. 41, issue 1

Abstract: Using data envelopment analysis with principal components, we calculate an adoption-intensity index for herbicide-resistance best management practices (BMPs). Empirical results for over 1,100 farmers in twenty-two U.S. states suggest that many farmers could improve their herbicideresistance BMP adoption. Two-limit truncated regression results show that higher yields and a greater proportion of acres planted with Roundup Ready R seeds motivate weed BMP adoption. While soybean and corn farmers have lower adoption intensity than cotton farmers, farmer educational attainment and greater concern for herbicide effectiveness and for human and environmental safety are found to help increase the adoption of weed BMPs.

Keywords: adoption intensity; best management practices; common-weight data envelopment analysis; herbicide-resistance management; polychoric non-negative principal component analysis; weed-resistance management; Crop Production/Industries (search for similar items in EconPapers)
Date: 2016
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