Journal of Agricultural and Resource Economics
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Factors influencing adoption of variable-rate nutrient management (VRM) and georeferenced precision soil sampling (PSS) for fertilizer management among cotton producers and the factors affecting awareness of and participation in cost-share programs encouraging the adoption of nutrient-management practices were analyzed using multivariate probit regression with sample selection. Data were collected from a fourteen-state cotton producer survey. Factors including farm size, operator age, and farm location were correlated with the adoption of VRM and PSS, awareness of cost-sharing programs, and program participation. The results may help agencies target farms with the specific attributes most likely to participate in cost-share programs.
The authors regret that the above paper contained an error in the calculation of the survey expansion weights (Lambert et al., 2014, p. 110). Using the notation of the paper, the expansion factor for the lth stratum was introduced as wl =agbh=ngh, where g indexes states and h indexes farm size class. This is in fact the correct expression if Sinkhorn’s (1964) RAS method were used. However, Ireland and Kullback’s (1968) cross-entropy method was used to estimate the expansion factors, and division of variables a and b by the survey response frequency (ngh) is unnecessary. The typographical error has no bearing on the empirical analysis. References
A 2009 survey of cotton farmers in twelve states collected information about the use of georeferenced precision soil testing (PST). Adoption of PST technology and the interval until retesting were examined with a Poisson hurdle regression. Survey data were calibrated using a post-stratification weighting protocol. Farming experience, farm size, land ownership, variable rate fertilizer management plans, and the use of soil electrical conductivity devices were correlated the with period until PST adopters retested soil. Understanding how producers perceive the useful life of soil-test information may be important for monitoring the effectiveness of best nutrient management practice adoption.
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