Research, part of a Special Feature on Empirical based agent-based modeling Agent-based Analysis of Agricultural Policies: an Illustration of the Agricultural Policy Simulator AgriPoliS, its…

By Kathrin Happe, Konrad Kellermann, Alfons Balmann. 2006

297 citations recorded by the source corpus.

This paper combines agent-based modeling of structural change with agricultural policy analysis. Using the agent-based model AgriPoliS, we investigate the impact of a regime switch in agricultural policy on structural change under various framework conditions. Instead of first doing a sensitivity analysis to analyze the properties of our model and then examining the introduced policy in an isolated manner, we use a meta-modeling approach in combination with the statistical technique of Design of Experiments to systematically analyze the relationship between policy change and model assumptions regarding key determinants of structural change such as interest rates, managerial abilities, and technical change. As a result, we observe that the effects of policies are quite sensitive to the mentioned properties. We conclude that an isolated analysis of a policy regime switch would be of only minor value for policy advice given the ability of simulation models to examine various potential futures.

Subfields: Environmental Chemistry, General Agricultural and Biological Sciences

View Paper: https://www.semanticscholar.org/paper/f9863d6ba6560d452b231d8f0b07d789e197b05a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Chemistry

1. Thomas Berger
2. Pepijn Schreinemachers
3. C. Sahrbacher
4. Kathrin Happe
5. Konrad Kellermann

In General Agricultural and Biological Sciences

1. Thomas Berger
2. Pepijn Schreinemachers
3. C. Sahrbacher
4. Kathrin Happe
5. Konrad Kellermann
6. Christian Troost

Citations in the corpus

• Impacts of Decoupled Agricultural Support on Farm Structure, Biodiversity and Landscape Mosaic: Some EU Results (2009, background): “Briefly, AgriPoliS is a spatial, dynamic agent-based simulation model of regional structural change in agriculture (Balmann, 1997; Happe et al., 2006; Kellermann et al., 2008).”
• Describing human decisions in agent-based models - ODD + D, an extension of the ODD protocol (2013, background): “Agents may differ in parameters (e.g. managerial abilities, Happe et al., 2006; or preferences, Filatova et al., 2011).”
• NEW DIRECTIONS FOR URBAN ECONOMIC MODELS OF LAND USE CHANGE: INCORPORATING SPATIAL DYNAMICS AND HETEROGENEITY (2010, unknown): “7As pointed out by Parker and Filatova (2009), agricultural economists have had success in applying ABMs to agricultural land markets (e.g., Berger, 2001; Happe, Kellermann, and Balmann, 2006).”
• Integrated assessment of future CAP policies: land use changes, spatial patterns and targeting (2009, methodology): “In this light, MEA-Scope considers the dynamic interactions of farms on the local land and product markets as well as in simultaneous decision making on factor allocation (Happe et al., 2006a,b; Osuch et al., 2007).”
• An agent-based simulation model of human-environment interactions in agricultural systems (2011, methodology): “AgriPoliS has been used to ex ante simulate structural change in European agriculture, in response to proposed changes to the Common Agricultural Policy (Happe et al. 2009, 2008, 2006).”
• Does structure matter? The impact of switching the agricultural policy regime on farm structures (2008, methodology): “Based on expert information from regional agricultural authorities, we therefore assume that farm agents in 8 For details on the adjustment methodology, refer to Sahrbacher et al. (2005) and Happe et al. (2006).”