Using the case of chronic wasting disease (CWD) in white-tailed deer, we estimated hunters’ willingness-to-pay (WTP) for testing their game and determined how their perception of disease risk, trust, and confidence in wildlife agency affected hunter participation in ongoing disease surveillance. The average WTP for testing was $23.75 per deer, and it was positively related to trust and confidence in the wildlife agency and the perception of risk about deer populations in the declining area and the pathogen spreading to other areas. These findings imply that implementing active outreach programs can improve hunter participation in user-paid systems for CWD surveillance.

This paper investigates the factors that drive farmers’ simultaneous adoption of six water conservation practices (WCPs) and the intensity of their adoption. We estimate farmers’ adoption of these WCPs with a multivariate probit model, and for the intensity of their adoption, an ordered probit model is estimated. Our results show that gender, age, education, and farm size (among other factors) influence the probability and extent of adoption of WCPs. Furthermore, combinations like drip and/or sprinkler irrigations and cover cropping, drip and/or sprinkler irrigations and intercropping (among others) are complements, suggesting the bundling of these WCPs.

Using a double-hurdle approach, we assess factors associated with the extent of participation in the rice market with data for small-scale farmers drawn from a nationally representative dataset. The results suggest that larger endowments and assets, animal farming and commercialization, and alternative off-farm income make farmers less likely to participate. Conversely, having access to credit, larger farm sizes, and being part of a farmers’ association all increase the likelihood of participation. Farms with better technological resources are also those with higher sales volumes. Further understanding market participation dynamics should prove useful for deriving evidence-based policy recommendations to strengthen this Bolivian sector.

This paper examines the potential effects of agricultural investment on economic outcomes in Guinea-Bissau (2014–2030). Through a dynamic computable general equilibrium (CGE) model, we found that improved agricultural performance will positively impact economic growth, sector output, and job opportunities for rural and urban workers. The decline in food prices will propagate indirect impacts on urban household welfare, while rural households will benefit from direct and indirect effects through the decline in the consumer price index. Poverty alleviation suggests agriculture’s crucial role in supporting ongoing industrialization and food security in Africa with attenuated income inequality.

Precision irrigation is a potential viable strategy for water use reductions on golf courses by making variable or site-specific irrigation applications. A group of US golf course superintendents were surveyed to examine whether and how superintendents’ risk preferences (attitudes) affect the adoption decisions of precision irrigation technologies on their golf courses. Under the prospect theory (PT) framework, a lottery experiment was used to elicit the measures of three risk attitudes, that is, risk curvature, probability distortion, and loss aversion. Using these three measures and other questions in the survey, we found that risk curvature has a significant positive effect on the precision irrigation technologies adoption on golf courses, while probability distortion affects the adoption negatively. Compared to the golf course in low precipitation areas, superintendents’ risk attitudes are more likely to affect the precision irrigation technologies adoption in the golf course in high precipitation areas. Additionally, risk curvature dominates the adoption decisions for newer technologies, while probability distortion dominates the older technologies adoption decisions. Our research enriches the literature on the decision-making behaviors of managers by considering how probability distortion, a factor typically ignored by other studies, affects technology adoption decisions and adds to the literature on examining the technology adoption behaviors under PT by focusing on golf course superintendents, a group that has not been studied.

This study formally links the literature on R&D-driven productivity growth to studies which examine GHG emission benefits from increased farm productivity growth. Using a global agricultural model and estimates from the literature, this study examines the impact of greater US public agricultural R&D spending over 2025−2035. The results show that roughly doubling public R&D investments in US agriculture could provide greater economic gains relative to its costs over the period 2017−2050. The GHG mitigation co-benefits from these investments also can be enhanced by combining R&D policies with strategies aimed at directly reducing farm inputs.

We examined the effect of using input and output quantities as compared with costs and revenues when estimating farm-level efficiency scores and ranking. We used farm-level data from the 2015 Ethiopia Rural Socioeconomic Survey (ERSS) where production inputs and outputs in quantities as well as monetary units could be distinguished. Average technical efficiency scores of 72.2% and 68.6%, respectively, were found for analysis based on quantities and on costs and revenues. Efficiency ranking differed significantly. Results suggest that type of data compilation introduces bias to the efficiency assessment and that conclusions may be unclear, which complicates policy advice.