Intensity of Precision Agriculture Technology Adoption by Cotton Producers

Author:

Paxton Kenneth W.,Mishra Ashok K.,Chintawar Sachin,Roberts Roland K.,Larson James A.,English Burton C.,Lambert Dayton M.,Marra Michele C.,Larkin Sherry L.,Reeves Jeanne M.,Martin Steven W.

Abstract

Many studies on the adoption of precision technologies have generally used logit models to explain the adoption behavior of individuals. This study investigates factors affecting the intensity of precision agriculture technologies adopted by cotton farmers. Particular attention is given to the role of spatial yield variability on the number of precision farming technologies adopted, using a count data estimation procedure and farm-level data. Results indicate that farmers with more within-field yield variability adopted a higher number of precision agriculture technologies. Younger and better educated producers and the number of precision agriculture technologies used were significantly correlated. Finally, farmers using computers for management decisions also adopted a higher number of precision agriculture technologies.

Publisher

Cambridge University Press (CUP)

Subject

Economics and Econometrics,Agronomy and Crop Science

Reference55 articles.

1. Cameron and Trivedi (2009) show that another way of interpreting the marginal effect of discrete variables is to exponentiate the coefficients (e β). One additional year in age is associated with the number of PA technologies decreasing by 1.02. The exponentiated coefficient of discrete variables applies to any Maximum Likelihood estimation (see Cameron and Trivedi 2009, pages 558–564).

2. RECENT DEVELOPMENTS IN COUNT DATA MODELLING: THEORY AND APPLICATION

3. Daberkow S.G. , and McBride W.D. 2000. “Adoption of Precision Agriculture Technologies by U.S. Farmers.” From the proceedings of the 5th International Conference on Precision Agriculture in Minneapolis, MN, July 16–19.

4. Statistical tests (t-test and Wald test) show that the coefficients on state dummies for Mississippi, Missouri, and Florida are statistically significant at the 5 percent level of significance. However, the Wald test also shows that the coefficients on state dummies for Mississippi and Missouri are not statistically different from one another.

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