Weighted Goal Programming and Penalty Functions: Whole-farm Planning Approach Under Risk

The paper presents multiple criteria approach to deal with risk in farmer’s decisions. Decision making process is organised in a framework of spreadsheet tool. It is supported by deterministic and stochastic mathematical programming techniques applying optimisation concept. Decision making process is conceptually divided into seven autonomous modules that are mutually linked up. Beside the common maximisation of expected income through linear programming it enables also reconstruction of current production practice. Income risk modelling is based on portfolio theory resting on expected value, variance (E,V) paradigm. Modules dealing with risk are therefore supported with quadratic and constrained quadratic programming. Non-parametric approach is utilised to estimate decision maker’s risk attitude. It is measured with coefficient of risk aversion, needed to maximise certainty equivalent for analysed farms. Multiple criteria paradigm is based on goal programming approach. In contribution focus is put on benefits and possible drawbacks of supporting weighted goal programming with penalty functions. Application of the tool is illustrated with three dairy farm cases. Obtained results confirm advantage of utilizing penalty function system. Beside greater positiveness it proves as useful approach for fine tuning of the model enabling imitation of farmer’s behaviour, which is due to his/her conservative nature not perfect or rational. Results confirm hypothesis that single criteria decision making, based on maximisation of expected income, might be biased and does not necessary lead to the best - achievable option for analysed farm.goal programming, risk modelling, risk aversion, production planning, Risk and Uncertainty,

Positive multi-criteria models in agriculture for energy and environmental policy analysis

Environmental consciousness and accompanying actions have been paralleled by the evolution of multi-criteria methods which have provided tools to assist policy makers in discovering compromises in order to muddle through. This paper recalls the development of multi-criteria methods in agriculture, focusing on their contribution to produce input or output functions useful for environmental and/or energy policy. Response curves generated by MC models can more accurately predict farmers’ response to market and policy parameters compared with classic profit maximizing behavior. Concrete examples from recent literature illustrate the above statements and ideas for further research are provided.multi-criteria models, interval programming, supply curves, bio-energy, policy analysis

Assessing farmer behaviour as affected by policy and technological innovations: bio-economic farm models

Farm Management,

Conservation Payments under Risk: A Stochastic Dominance Approach

Conservation payments can be used to preserve forest and agroforest systems. To explain landowners’ land-use decisions and determine appropriate conservation payments, it is necessary to focus on revenue risk. Marginal conditional stochastic dominance rules are used to derive conditions for determining the conservation payments required to guarantee that the environmentally-preferred land use dominates. An empirical application to shaded-coffee protection in the biologically important Chocó region of West-Ecuador shows that conservation payments required for preserving shaded-coffee areas are much higher than those calculated under risk-neutral assumptions. Further, the extant distribution of land has strong impacts on the required payments.agroforest systems, conservation payments, land allocation, portfolio diversification, risk, stochastic dominance

Farmers' behavior and the provision of public goods: towards an analytical framework

The new CAP reform aims to stimulate the role of agriculture as provider of public goods. An analytical framework is developed to model farmers’ decision making and to gain insight into farmers’ behavior in response to a number of policy instruments. The framework integrates characteristics of farm, farmer, market, as well as the policy instruments. Theoretical analysis suggests that attitudes, off-farm employment opportunities, non-pecuniary benefits and expectations of future developments can play important roles in farmer’s decision making regarding the provision of public goods. Empirical research is needed to test the hypothesis

Designing an institutional network for improving farm animal welfare in the EU

Improvements in the welfare of farmed animals in the EU have been achieved by legislation, increased welfare capacity in the food chain, greater public awareness, welfare measurement tools and dissemination of best practice. However, pressure for improvement grows. The EC recognises that delivering improved welfare would best be achieved by increasing welfare capacity, including establishing a Network of Welfare Reference Centres to provide support for welfare research, knowledge transfer and policy design. Designing a structure for this Network presents a challenge, as it would have multiple functions, interact with diverse stakeholders and operate in a complex environment. Here, we describe the use of a novel strategic planning approach to design an optimal structure for this Network. Our evaluation found that no existing structure was ideal, but that by taking functional units from several existing models, an optimal model could be identified

On farm conservation of rice biodiversity in Nepal: a simultaneous estimation approach

"This paper presents an empirical case study about farmer management of rice genetic resources in two communities of Nepal, drawing on interdisciplinary, participatory research that involved farmers, rice geneticists, and social scientists. The decision-making process of farm households is modeled and estimated in order to provide information for the design of community-based conservation programs. A bivariate model with sample selection treats the simultaneous process of whether farmers decide to plant landraces or modern varieties, and whether the landraces they choose to plant constitute genetic diversity of interest for future crop improvement. Findings show that the two landrace choices are affected by different social and economic factors. The estimation procedure demonstrates that in certain cases, however, the decision processes are interrelated. Policies to promote the conservation of local rice diversity will need to take both processes into account. Fitted equations are then used to compare the likelihood that households targeted for conservation according to one set of conservation criteria also meet other conservation criteria. Households most likely to plant landraces identified as important for crop improvement also grow richer, more spatially diverse rice varieties. In these communities, few policy trade-offs would result from employing one set of criteria instead of the other." Authors' AbstractLandraces, Crop diversity,

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