20 pages, To achieve social sustainability, there is a need to incorporate social metrics of farmers’ well- being into agricultural monitoring systems. We contribute to the operationalisation of the measurement of farmers’ well- being by determining how farm- level factors influence farmers’ satisfaction with their work and quality of life. Using a data sample of 1099 farms that are part of the Farm Accountancy Data Network (FADN) in nine European countries, we tested a set of hypotheses related to work satisfaction and life quality perception based on a structural equation model. Satisfaction with on- farm work has a significant and substantial influence on satisfaction with quality of life. Farm- level aspects, such as working time, age of assets, financial situation of the farm and community engagement, significantly influenced farmers’ satisfaction with farming, but their joint effect explained less than one- fifth of the satisfaction. The results suggest that agricultural information systems intended to monitor and compare sustainability progress on farms would benefit from the integration of a metric measuring social concerns from the farmers’ point of view
29 pages, Agent-based models are important tools for simulating farmers’ behaviour in response to changing environmental, economic or institutional conditions and policies. This article introduces an agent-based modelling approach that combines behavioural factors with standard bio-economic modelling of agricultural production. More specifically, our framework integrates the cumulative prospect theory and social interactions with constrained optimisation decisions in agricultural production. We apply our modelling approach to an exemplary bio-economic model on the assessment of weed control decisions. Results show the effects of heterogeneous farm decision-making and social networks on mechanical weed control and herbicide use. This framework provides a generic and conceptually sound approach to improve the scope for representing farmers’ decision-making and allows the simulation of their decisions and recent advances in behavioural economics to be aligned with existing bio-economic models of agricultural systems.
24 pages, We present a systematic review of the extensive body of research on farmer risk preference measurement across Europe. We capture the methodological developments over time and discuss remaining challenges and potential areas for further research. Given the constantly evolving policy environment in Europe, and increasing climate-change related risks and uncertainties, there is large value to be gained from enhancing our understanding of this fundamental aspect of farmers’ decision-making processes and consequent actions.
18pgs, This analysis investigates the potential mechanisms and the practical significance of agricultural value chain development in a geographically challenging rural area of a developing country. Using data from a carefully designed primary survey administered in a hill and mountainous region in Western Nepal, we show that linking small-scale producers to regional and local traders can help increase income. Analysis of impact pathways shows that the positive impact on household income emerges through higher agricultural income, driven by higher sale volume at lower prices. Focusing on high value commodities in rural areas, where arable land is not always fully exploited or utilized, appears to lead to acreage expansion and some crop switching, contributing to higher supply albeit at lower prices. The positive impact on household income is practically significant; it helps improve household food security and asset accumulation. These findings are robust to alternative specifications. Targeted value chain interventions that strengthen and stabilize small-scale producers’ access to markets can contribute to rural poverty reduction via increase in agricultural income.
Analytic results indicate that producers having less elastic supply response capture more benefits per dollar expended than producers with more elastic supply response.
