On the development and use of farm models for policy impact assessment in the European Union – A review

Reidsma, P.; Janssen, Sander; Jansen, Jacques; Ittersum, M.K. van

doi:10.1016/j.agsy.2017.10.012

Cited by 102 publications

(73 citation statements)

References 132 publications

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“…Recent publications in the context of social-ecological systems modelling (Filatova et al, 2013;Schulze et al, 2017), integrated assessment (Laniak et al, 2013), agricultural systems modelling (Jones et al, 2017) and policy impact assessments (Reidsma et al, 2018) suggest that there is a need for improved representation of farmers' heterogeneous decision-making. The representation should not only consider cognitive individual processes, personal characteristic, or social interactions (as in most non-agricultural ABM), but also the socio-economic and natural environment as well as farm household characteristics.…”

Section: Agents' Decision-making In Farm Systemsmentioning

confidence: 99%

Representation of decision-making in European agricultural agent-based models

Huber

Bakker

Balmann

et al. 2018

Agricultural Systems

126

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 Agent-based modelling is a suitable tool for improving the understanding of farmers' behaviour.  Review 20 agricultural ABM addressing heterogeneous decision-making processes in the context of European agriculture.  Considerable scope to improve diversity in representation of decision-making by combining existing modelling approaches.  More coordinated and purposeful combinations of ABM and hybrid modelling approaches are needed.  Results provide an entry point for collaboration of agent-based modellers, agricultural systems modellers and social scientist.

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Section: Agents' Decision-making In Farm Systemsmentioning

confidence: 99%

Representation of decision-making in European agricultural agent-based models

Huber

Bakker

Balmann

et al. 2018

Agricultural Systems

126

View full text Add to dashboard Cite

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“…Agro-environmental conditions and farm characteristics determine the feasibility of production activities, while the socio-economic environment influences the selection of most suitable production activities. In this study, the bioeconomic farm model FSSIM (Farm System SIMulator; [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39]) was adapted and used to design new farm plans under the effects of CAP-greening policies, feed self-sufficiency, and gross margin maximisation scenarios on dairy farms in northwest Italy. We assessed the economic efficiency and environmental impacts of four different scenarios.…”

Section: Introductionmentioning

confidence: 99%

Integrated Assessment of the EU’s Greening Reform and Feed Self-Sufficiency Scenarios on Dairy Farms in Piemonte, Italy

et al. 2018

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Specialised dairy farms are challenged to be competitive and yet respect environmental constrains. A tighter integration of cropping and livestock systems, both in terms of feed and manure flows, can be beneficial for the farm economy and the environment. The greening of the direct payments, which was introduced in the European Union’s greening reform in 2013, is assumed to stimulate the transition towards more sustainable systems. The aim of this study was to quantitatively assess the impacts of greening policies on important economic and environmental indicators of sustainability, and explore potential further improvements in policies. The Farm System SIMulator (FSSIM) bioeconomic farm model was used to simulate the consequences of scenarios of policy change on three representative dairy farms in Piedmont, Italy, i.e., an ‘intensive’, an ‘extensive’, and an ‘organic’ dairy farm. Results showed that in general, there is a large potential to increase the current economic performance of all of the farms. The most profitable activity is milk production, resulting in the allocation of all of the available farm land to feed production. Imposing feed self-sufficiency targets results in a larger adaptation of current managerial practice than the adaptations that are required due to the greening policy scenario. It was shown that the cropping system is not always able to sustain the actual herd composition when 90% feed self-sufficiency is imposed. Regarding the greening policies, it is shown that extensive and organic farms already largely comply with the greening constrains, and the extra subsidy is therefore a bonus, while the intensive farm is likely to sacrifice the subsidy, as adapting the farm plan will substantially reduce profit. The introduction of nitrogen (N)-fixing crops in ecological focus areas was the easiest greening strategy to adopt, and led to an increase in the protein feed self-sufficiency. In conclusion, it is important to note that the greening policy in its current form does not lead to reduced environmental impacts. This implies that in order to improve environmental performance, regulations are needed rather than voluntary economic incentives.

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“…Accordingly, farmer's decision on the acquisition of a new machinery and replenishment of the fleet needs to be based on the complex interaction of economic, environmental, and social criteria and supported by the field stockholders (dealers, consultants, regional or national authorities, etc.) [1,2]. Despite its importance, there are several aspects that have a significant impact on the farmer's buying decision behaviour and decision-making process.…”

Section: Introductionmentioning

confidence: 99%

Definition of Reference Models for Power, Weight, Working Width, and Price for Seeding Machines

Yezekyan

Marinello

Armentano³

et al. 2018

Agriculture

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Machine functional parameters define fleet composition and management and, thus, play an important role in economic and environmental performance. Large availability of programming methods and decision support systems are available in the market, however, there is still a lack of applicative tools to forecast the perceived and necessary technical parameters and machinery price options to complete tasks. In the current research, most correlated functional parameters for four group of seeding machines were determined with the application of linear and multiple linear regression analyses. Power, weight, working width, number of rows, and list price were studied, and reference equations were developed for seed drills, precision, combined and no-tillage planters. Two statistical analyses models were, therefore, developed for each of the groups in order to allow evaluation and prediction of performance and cost, thus contributing to the selection process optimisation and perceived choice of the needed implement.

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On the development and use of farm models for policy impact assessment in the European Union – A review

Cited by 102 publications

References 132 publications

Representation of decision-making in European agricultural agent-based models

Representation of decision-making in European agricultural agent-based models

Integrated Assessment of the EU’s Greening Reform and Feed Self-Sufficiency Scenarios on Dairy Farms in Piemonte, Italy

Definition of Reference Models for Power, Weight, Working Width, and Price for Seeding Machines

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