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Agent based modeling for agricultural policy evaluation: A review

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  • Dimitris Kremmydas

    (Department of Agricultural Economics and Rural Development, Agricultural University of Athens, Iera Odos 75, Athens 11855, Greece)

Abstract

In Agent-based computational economics economy is considered a complex system where the interactions between the economic agents are of ultimate importance. Simulating the economic system by modeling the behavior of the individual encompasses many advantages and certain epistemological issues are raised. In the analysis of Agricultural Policy, the agent based modeling (ABM) approach has been employed for studying Land Use Changes (LUCC), the dynamics of structural changes, the transmission of innovations, the simulation of water use management and for environmental modeling. This approach can help overcoming various simplifying assumptions of the traditional models (like the “homogenous agent” assumption) or the difficulty in modeling interactions. In this paper we initially do a short presentation of the principles of modeling economic systems with the ABM approach quoting its features, the advantages and disadvantages. Afterwards we make a discussion on the application of the ABM for modeling and evaluating agricultural policies and present four current application (Agripolis, Reg-MAS, MP-MAS, SWISSland). We finish this paper with some conclusions and suggestions.

Suggested Citation

  • Dimitris Kremmydas, 2012. "Agent based modeling for agricultural policy evaluation: A review," Working Papers 2012-3, Agricultural University of Athens, Department Of Agricultural Economics.
    • Handle: RePEc:aua:wpaper:2012-3
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    2. Shang, Linmei & Heckelei, Thomas & Börner, Jan & Rasch, Sebastian, 2020. "Adoption and Diffusion of Digital Farming Technologies – Integrating Farm-Level Evidence and System-Level Interaction," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305586, German Association of Agricultural Economists (GEWISOLA).
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    5. Ida Nadia S. Djenontin & Leo C. Zulu & Arika Ligmann-Zielinska, 2020. "Improving Representation of Decision Rules in LUCC-ABM: An Example with an Elicitation of Farmers’ Decision Making for Landscape Restoration in Central Malawi," Sustainability, MDPI, vol. 12(13), pages 1-35, July.
    6. Baillie, Sarah & Kaye-Blake, William & Smale, Paul & Dennis, Samuel, 2016. "Simulation modelling to investigate nutrient loss mitigation practices," Agricultural Water Management, Elsevier, vol. 177(C), pages 221-228.
    7. van der Linden, Aart & de Olde, Evelien M. & Mostert, Pim F. & de Boer, Imke J.M., 2020. "A review of European models to assess the sustainability performance of livestock production systems," Agricultural Systems, Elsevier, vol. 182(C).
    8. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    9. Williams, T.G. & Guikema, S.D. & Brown, D.G. & Agrawal, A., 2020. "Resilience and equity: Quantifying the distributional effects of resilience-enhancing strategies in a smallholder agricultural system," Agricultural Systems, Elsevier, vol. 182(C).
    10. Alina Evelyn Badillo-Márquez & Alberto Alfonso Aguilar-Lasserre & Marco Augusto Miranda-Ackerman & Oscar Osvaldo Sandoval-González & Daniel Villanueva-Vásquez & Rubén Posada-Gómez, 2021. "An Agent-Based Model-Driven Decision Support System for Assessment of Agricultural Vulnerability of Sugarcane Facing Climatic Change," Mathematics, MDPI, vol. 9(23), pages 1-32, November.
    11. Kaye-Blake, William & Schilling, Chris & Monaghan, Ross & Vibart, Ronaldo & Dennis, Samuel & Post, Elizabeth, 2019. "Quantification of environmental-economic trade-offs in nutrient management policies," Agricultural Systems, Elsevier, vol. 173(C), pages 458-468.

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    More about this item

    Keywords

    Agent based modeling; Agricultural policy evaluation; Agripolis; Reg-MAS; MP-MAS; SWISSland;
    All these keywords.

    JEL classification:

    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling

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