18,317 research outputs found

    Cost-Effectiveness Evaluation of Swiss Agri-Environmental Measures on Sector Level

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    Abstract This paper focuses on non-linear programming models and their suitability for ex-ante evaluations of agri-environmental policies on sector level. An approach is presented to compare organic farming payments as a multi-objective policy, with other, more targeted agri-environmental policies in Switzerland. The Swiss version of the comparative static sector-consistent farm group model FARMIS is able to group the sector’s farms into organic and non-organic farms and optimise them separately. CH-FARMIS is expanded with three modules particularly for this study: a) allowing for the simulation of uptake; b) integrating life cycle assessment data for energy use, eutrophication and biodiversity; and c) estimating the policy and farm-group-specific public expenditure, including transaction costs. This paper illustrates the functions of the model, shows preliminary energy use calculations for the German Agricultural Sector and discusses the advantages and limitations of the approach

    CH-FARMIS - An agricultural sector model for Swiss agriculture

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    This working paper gives an overview of the farm group model CH-FARMIS - a comparative static, process analytical, non-linear programming model that allows a separate assessment of the impacts of policies on organic and non-organic farming in Switzerland. In CH-FARMIS, the agricultural sector is represented by thirty farm groups, which can be char-acterised by their farming system, farm type and geographic location. Book keeping data from the Swiss FADN was used as a primary source for the model. By applying farm-specific weight-ing factors, farm data were aggregated to sector accounts. The technical coefficients of the farm model were either taken directly from farm accounts or calculated on the basis of normative data. Agricultural production is represented by 29 crop activities and 15 livestock activities. The factor allocation and production of each farm group is optimised by maximising farm income under policy and management restrictions. The restrictions cover the area of land and labour use, livestock feeding, fertiliser balance, rearing of young stock, allocation of direct payments and requirements with respect to the organic production system. A positive mathematical pro-gramming approach (PMP) was used to calibrate the production activities in the base year to observed activity levels

    A generic template for FSSIM

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    Agricultural and Food Policy, Environmental Economics and Policy, Land Economics/Use,

    The MODERE Model and The Economic Analysis of Farmers’ Decisions

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    The MODERE, the Ministry of the Environment Irrigation Decision Model, is a simulation tool which uses mathematical programming methods to reveal the implicit multiattribute objective function lying behind the observed cropping decision. The model takes different criteria such as profit maximization, risk aversion, avoidance of management complexities and so forth into account. In order to determine the feasible combination of attributes of this objective function the model considers the production possibility frontier explicitly as depending on market prices, policy incentives, availability of production factors, water irrigation facilities agronomic vocation and other constraints. Once calibrated the model becomes a powerful tool to assess the impact of different policy scenarios such as subsidies decoupling, water prices modifications, irrigation technique substitution and so on. The MODERE is a preference revelation model purposedly designed to be integrated in the Decision Support Platform which is used by the Spanish Ministry of the Environment to compare the policy scenarios which are relevant to assess the effectiveness and economic impact of the measures designed to reach the environmental objectives of the Water Framework Directive. The model is supported by a comprehensive data base built on purpose for its implementation covering almost all the Spanish Irrigation Districts with high spatial detail. This model is currently one of the important modules of the information and decision support systems developed by the Economic Analysis Unit of the Water Directorate at the Ministry of the Environment in Spain.Agricultural Economics, Water Economics, Simulated Models, Land Economics/Use, Political Economy, Research Methods/ Statistical Methods, Resource /Energy Economics and Policy,

    A Modelling Approach for Evaluating Agri-Environmental Policies at Sector Level

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    This paper presents a new approach to evaluate the cost effectiveness of agri-environmental policies at sector level. Policy uptake, cumulative environmental effects and public expenditure are identified as the main determinants of cost-effectiveness. On the basis of the sector-consistent, comparative-static, farm group model FARMIS, the determinants of policy cost-effectiveness at sector level are addressed. Firstly, intensity levels for the FARMIS activities are defined in order to model uptake of agri-environmental policies with FARMIS, secondly, life-cycle assessment data is attached to these intensity levels to determine environmental effects of the policies and thirdly, public expenditure is calculated under consideration of transaction costs. This paper concludes delineating the strengths and limitations of the approach

    Aggregation and Calibration of Agricultural Sector Models Through Crop Mix Restrictions and Marginal Profit Adjustments

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    All agricultural sector models must deal with aggregation and calibration somehow. The aggregation problem involves treating a group of producers as if they all responded in the same way as a single representative unit. The calibration problem concerns making a model reproduce as closely as possible an empirically observed set of decision maker actions. This paper shows how both calibration and aggregation are addressed through crop mix restrictions combined with marginal profit adjust-ments.mathematical programming, aggregation, calibration, crop mix, marginal cost, agricultural sector model, Agribusiness, C6, C61, Q1, Q11, Q17, Q18, R12, R13, R14,
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