Agent based modeling for agricultural policy evaluation: A review
AbstractIn 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.
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Bibliographic InfoPaper provided by Agricultural University of Athens, Department Of Agricultural Economics in its series Working Papers with number 2012-3.
Length: 18 pages
Date of creation: 2012
Date of revision:
Agent based modeling; Agricultural policy evaluation; Agripolis; Reg-MAS; MP-MAS; SWISSland;
Find related papers by 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
- C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
This paper has been announced in the following NEP Reports:
- NEP-AGR-2013-01-12 (Agricultural Economics)
- NEP-ALL-2013-01-12 (All new papers)
- NEP-CMP-2013-01-12 (Computational Economics)
- NEP-HME-2013-01-12 (Heterodox Microeconomics)
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- Stefania Bandini & Sara Manzoni & Giuseppe Vizzari, 2009. "Agent Based Modeling and Simulation: An Informatics Perspective," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 12(4), pages 4.
- Happe, K. & Hutchings, N.J. & Dalgaard, T. & Kellerman, K., 2011. "Modelling the interactions between regional farming structure, nitrogen losses and environmental regulation," Agricultural Systems, Elsevier, vol. 104(3), pages 281-291, March.
- Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad & Sahrbacher, Christoph, 2008. "Does structure matter? The impact of switching the agricultural policy regime on farm structures," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 431-444, August.
- Balmann, Alfons, 1997. "Farm-Based Modelling of Regional Structural Change: A Cellular Automata Approach," European Review of Agricultural Economics, Foundation for the European Review of Agricultural Economics, vol. 24(1), pages 85-108.
- Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
- Appel, Franziska & Musshoff, Oliver, 2011. "How appropriate are myopic optimization models to predict decision behaviour: A comparison between agent-based models and business management games," 2011 International Congress, August 30-September 2, 2011, Zurich, Switzerland 115994, European Association of Agricultural Economists.
- Tyler Freeman & James Nolan & Richard Schoney, 2009. "An Agent-Based Simulation Model of Structural Change in Canadian Prairie Agriculture, 1960-2000," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(4), pages 537-554, December.
- repec:att:wimass:9721 is not listed on IDEAS
- Lobianco, Antonello & Esposti, Roberto, 2010. "The Regional Multi-Agent Simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies," MPRA Paper 25817, University Library of Munich, Germany.
- James Millington & Ra�l Romero-Calcerrada & John Wainwright & George Perry, 2008. "An Agent-Based Model of Mediterranean Agricultural Land-Use/Cover Change for Examining Wildfire Risk," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(4), pages 4.
- Nigel Gilbert & Pietro Terna, 2000. "How to build and use agent-based models in social science," Mind and Society: Cognitive Studies in Economics and Social Sciences, Fondazione Rosselli, vol. 1(1), pages 57-72, March.
- Kathrin Happe & Alfons Balmann & Konrad Kellermann, 2003. "Structural, efficiency and income effects of direct payments: an analysis of different payment schemes for the German region 'Hohenlohe'," Others 0308001, EconWPA.
- Kaye-Blake, William & Li, Frank Y. & Martin, A. McLeish & McDermott, Alan & Neil, Hayley & Rains, Scott, 2009. "A review of Multi-Agent Simulation Models in Agriculture," 2009 Conference, August 27-28, 2009, Nelson, New Zealand 97165, New Zealand Agricultural and Resource Economics Society.
- Weisbuch, Gerard, 2000. "Environment and institutions: a complex dynamical systems approach," Ecological Economics, Elsevier, vol. 35(3), pages 381-391, December.
- Steven N. Durlauf, 1997.
"What Should Policymakers Know About Economic Complexity?,"
97-10-080, Santa Fe Institute.
- Kaufmann, Peter & Stagl, Sigrid & Franks, Daniel W., 2009. "Simulating the diffusion of organic farming practices in two New EU Member States," Ecological Economics, Elsevier, vol. 68(10), pages 2580-2593, August.
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