Journal of Agricultural and Resource Economics
Issue Archives
Search and browse every article in the JARE archive, from 1992 to today. Filter by issue or author, read abstracts, and bookmark articles to come back to.
Search the archive
Keyword
Year & issue
Author
Articles
We examine the interdependence of high-yielding (HY) variety adoption and farm and farmer characteristics to achieve almost self-sufficiency in rice production in Bangladesh. We use data collected by the International Rice Research Institute (IRRI), Bangladesh, to estimate yield differentials, return differentials, and risk. We find that HY rice varieties contributed 61.34%, plot-specific attributes contributed 3.08%, and farmer-specific characteristics contributed 35.58% toward rice productivity. Additionally, adopting HY varieties resulted in a base return increase of about 154.03%. Plot-specific attributes had larger effects on the return model than on the differential yield model, while farmer-specific characteristics adversely impacted HY return gains.
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.
This research analyzes the adoption patterns among cotton farmers for remote sensing, yield monitors, soil testing, soil electrical conductivity, and other precision agriculture technologies using a Multiple Indicator Multiple Causation regression model. Adoption patterns are analyzed using principle component analysis to determine natural technology groupings. Identified bundles are regressed on farm structure and operator characteristics. The propensity to adopt technology bundles was greater for producers managing relatively larger operations who used a variety of information sources to learn about precision farming, irrigated cotton, practiced crop rotation, and participated in working land conservation programs.
Publish in JARE
JARE publishes applied research in agricultural, food, natural resource and environmental economics. Read the guidelines and policies, then submit through Editorial Express.
Ready to submit?
Manuscripts go through JARE’s Editorial Express site.
Library or member? Subscribe to JARE