88 research outputs found
Do private sustainability standards contribute to income growth and poverty alleviation? : a comparison of different coffee certification schemes in Ethiopia
Private sustainability standards are increasingly important in food trade with developing countries, but the implications for smallholder farmers are still poorly understood. We analyze the implications of different coffee certification schemes in Ethiopia using cross-sectional survey data, and regression and propensity-score-matching techniques. We find that: Rainforest Alliance (RA) and double Fairtrade-Organic (FT-Org) certifications are associated with higher incomes and reduced poverty, mainly because of higher prices; Fairtrade (FT) certification hardly affects welfare; and Organic (Org) certification reduces incomes, chiefly due to lower yields. Cooperative heterogeneity importantly shapes these results. Results imply that private standards may not always deliver what they promise to consumers
Input-output Concepts, Profits and Productivity Growth: An Application Using Flemish Farm Level Data
Farm Management, Productivity Analysis,
Farm household risk balancing : implications for policy from an EU perspective
Purpose - Building on the risk balancing theory and on recent discussions the appropriateness of using farm income maximization as behavioural assumption, this paper extends the risk balancing framework by accounting for business-household interactions. The purpose of this paper is to theoretically introduce the concept of farm household risk balancing, a theoretical framework in which the farm household sets a constraint on the total household-level risk and balances farm-level and off-farm-level risk.
Design/methodology/approach - The paper argues that the risk behaviour of farmers is better understood by considering risk at the household level. Using an analytical framework, equations are derived linking the farm activities, off-farm activities, consumption and business and private liquidity.
Findings - The framework shows that a farm household that wants to minimize the risk that total household cash flow falls below consumption needs, may exhibit a wide variety of behavioural responses to changes in the policy and economic environment.
Social implications - The framework suggests multiple ways for policy makers and individual farmers to support risk management.
Originality/value - Risk management is at the core of the agricultural policy and it is of paramount importance to be able to understand behavioural responses to market and policy instruments. This paper contributes to that by suggesting that the focus of current risk analysis and management studies may be too narrowly focused at the farm level
The Struggle of Farming Systems in Europe:Looking for Explanations through the Lens of Resilience
Many farming systems in Europe are struggling to respond to accumulating economic, environmental, institutional and social challenges. From a resilience perspective, they need three distinct capacities to continue delivering products, income and public goods: robustness, adaptability and transformability. Based on a structured assessment of the resilience capacities of 11 farming systems across Europe we conclude that three mismatches likely contribute to their struggles. First, while farming systems comprised many nonâfarm actors, resilience strategies largely focused on farms and their robustness, neglecting other options and opportunities. Second, while the delivery of public goods such as biodiversity and attractive landscapes was seen as a major concern, most resilience strategies focused on the delivery of private goods. Third, while in many farming systems actors expressed the need for transformation, farming systemsâ capacity to transform was perceived as low. Building on the differentiated concept of resilience, findings can guide policymakers, farming system actors, consumers and societal interest groups to identify pathways towards more resilient agricultural systems in Europe
Risk management and its role in enhancing perceived resilience capacities of farms and farming systems in Europe
In facing future challenges, risk management (RM) is essential for European farming systems (FS). This article synthesises lessons learned on RM based on a farm survey, interviews with farmers, and focus groups involving a range of FS actors. In contrast to previous literature, we broaden the definition of RM to include strategies that target long-term structural challenges, as well as expanding the level of analysis from the farm to the FS level. The results were consistent across the different methods. We found that farmers mainly worry about economic challenges: in particular long-term pressures. We also found that European farmers have implemented diverse RM strategies in the past 5 years, and that no single strategy has been applied by the vast majority of farmers. In line with perceptions of future challenges, there is a demand for the reorientation of RM strategies towards long-term pressures, rather than short-term shocks. FS actors were found to perceive RM as enhancing resilience capacities, especially adaptability. The results of interviews distinguished between major learning strategies and the attributes of farmers for enhancing robustness, adaptive, or transformative capacities. Focus group discussions revealed that the future development of RM strategies requires contributions by all FS actors
A framework to assess the resilience of farming systems
Agricultural systems in Europe face accumulating economic, ecological and societal challenges, raising concerns
about their resilience to shocks and stresses. These resilience issues need to be addressed with a focus on the
regional context in which farming systems operate because farms, farmersâ organizations, service suppliers and
supply chain actors are embedded in local environments and functions of agriculture. We define resilience of a farming
system as its ability to ensure the provision of the system functions in the face of increasingly complex and
accumulating economic, social, environmental and institutional shocks and stresses, through capacities of robustness,
adaptability and transformability. We (i) develop a framework to assess the resilience of farming systems, and (ii)
present a methodology to operationalize the framework with a view to Europeâs diverse farming systems. The
framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming systemâs
capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to
analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system
functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle
processes of agricultural practices, farm demographics, governance and risk management. The novelty of the
framework pertains to the focal scale of analysis, i.e. the farming system level, the consideration of accumulating
challenges and various agricultural processes, and the consideration that farming systems provide multiple functions
that can change over time. Furthermore, the distinction between three resilience capacities (robustness, adaptability,
transformability) ensures that the framework goes beyond narrow definitions that limit resilience to robustness. The
methodology deploys a mixed-methods approach: quantitative methods, such as statistics, econometrics and
modelling, are used to identify underlying patterns, causal explanations and likely contributing factors; while qualitative
methods, such as interviews, participatory approaches and stakeholder workshops, access experiential and contextual
knowledge and provide more nuanced insights. More specifically, analysis along the framework explores multiple
nested levels of farming systems (e.g. farm, farm household, supply chain, farming system) over a time horizon of 1-2
generations, thereby enabling reflection on potential temporal and scalar trade-offs across resilience attributes. The
richness of the framework is illustrated for the arable farming system in Veenkoloniën, the Netherlands. The analysis
reveals a relatively low capacity of this farming system to transform and farmers feeling distressed about
transformation, while other members of their households have experienced many examples of transformation
Healthier and Sustainable Food Systems: Integrating Underutilised Crops in a âTheory of Change Approachâ
Increasingly, consumers are paying attention to healthier food diets, âhealthyâ food attributes (such as âfreshnessâ, ânaturalnessâ and ânutritional valueâ), and the overall sustainability of production and processing methods. Other significant trends include a growing demand for regional and locally produced/supplied and less processed food. To meet these demands, food production and processing need to evolve to preserve the raw material and natural food properties while ensuring such sustenance is healthy, tasty, and sustainable. In parallel, it is necessary to understand the influence of consumersâ practices in maintaining the beneficial food attributes from purchasing to consumption. The whole supply chain must be resilient, fair, diverse, transparent, and economically balanced to make different food systems sustainable. This chapter focuses on the role of dynamic value chains using biodiverse, underutilised crops to improve food system resilience and deliver foods with good nutritional and health properties while ensuring low environmental impacts, and resilient ecosystem functions.This research was supported by the European Unionâs Horizon 2020 Research and Innovation Programme through the project âRealising Dynamic Value Chains for Underutilised Cropsâ (RADIANT), Grant Agreement number 101000622. The authors would also like to thank the scientific collaboration under the FCT project UIDB/50016/2020. in. The James Hutton Institute (CH and PPMI) are supported by the âRural and Environmental Science and Analytical Servicesâ (RESAS), a Division of the Scottish Government.Peer reviewe
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