Lobianco, Antonello and Esposti, Roberto (2010): The Regional Multi-Agent Simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies. Published in: Computers and Electronics in Agriculture , Vol. 72, No. 1 (June 2010): pp. 14-26.
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RegMAS (Regional Multi Agent Simulator) is an open-source spatially explicit multi-agent model framework specifically designed for long-term simulations of the effects of policies on agricultural systems. Using iterated conventional optimisation problems as agents’ behavioural rules, it allows for a bidirectional integration between geophysical and social models where spatially-distributed characteristics are taken into account in the programming problem of the optimising agents. With RegMAS it is possible to simulate the local specific response to a given policy (or scenario), where policies, together with macro and regional characteristics, are read into the program in specially formatted spreadsheets and standard GIS files. The paper presents the model logic and structure and describes its functioning by applying it to a case-study, where RegMAS results are compared with conventional agent-based modelling to demonstrate the advantages of spatial explicitness. The simulation refers to the impact of the recent “Health Check” of the CAP on farm structures, income and land use in a hilly area of a central Italian region (Marche).
|Item Type:||MPRA Paper|
|Original Title:||The Regional Multi-Agent Simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies|
|Keywords:||Agent-Based Modelling; Mathematical Programming; Explicit Spatial Analysis; Common Agricultural Policy|
|Subjects:||C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis
Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q1 - Agriculture > Q18 - Agricultural Policy ; Food Policy
|Depositing User:||Antonello Lobianco|
|Date Deposited:||13. Oct 2010 11:21|
|Last Modified:||31. Dec 2015 15:03|
Antòn, J. & Sckokai, P. (2006), ‘The challenge of decoupling agricultural support’, EuroChoices 5(3), 13–19.
Arﬁni, F. (2000), ‘I modelli di programmazione matematica per l’analisi della politica agricola comune’. INEA seminar Valutare gli eﬀetti della Politica Agricola Comune, Rome, 24 October 2000.
Baﬀes, J. & de Gorter, H. (2005), Experience with decoupling agricultural support, in M. A. Aksoy & J. C. Beghin, eds, ‘Global Agricultural Trade and Developing Countries’, World Bank Publications, pp. 75–89.
Balmann, A. (1997), ‘Farm-based modelling of regional structural change: A cellular automata approach’, European Review of Agricultural Economics 24(1-2), 85–108. doi:10.1093/erae/24.1-2.85.
Boero, R. (2006), ‘The spatial dimension and social simulations: A review of three books’, JASSS, Journal of Artiﬁcial Societies and Social Simulation.
Bousquet, F., Bakam, I., Proton, H. & Page, C. L. (1998), Cormas: Common-pool resources and multi-agent systems, in A. P. del Pobil, J. M. & M. Ali, eds, ‘Tasks and Methods in Applied Artiﬁcial Intelligence’, Vol. 1416 of Lecture Notes in Computer Science, Springer, pp. 826–837.
Brady, M., Kellermann, K., Sahrbacher, C. & Jelinek, L. (2009), ‘Impacts of decoupled agricultural support on landscape values: an eu-wide assessment’, Journal of Agricultural Economics 60(3), 563–585.
Castella, J., Boissau, S., Trung, T. & Quang, D. (2005), ‘Agrarian transition and lowland-upland interactions in mountain areas in northern vietnam: application of multi-agent simulation model’, Agricultural systems.
Ellis, J. R., Hughes, D. W. & Butcher, W. R. (1991), ‘Economic modeling of farm production and conservation decisions in response to alternative resource and environmental policies’, Northeastern Journal of Agricultural and Resource Economics 20(1), 98–108.
EUCOM (2008), Proposal for a council regulation establishing common rules for direct support schemes for farmers under the common agricultural policy and establishing certain support schemes for farmers, COM 306, Commission of the European Communities. 20 May 2008.
Happe, K., Balmann, A., Kellermann, K. & Sahrbacher, C. (2008), ‘Does structure matter? the impact of switching the agricultural policy regime on farm structures’, Journal of Economic Behavior & Organization 67(2)
Happe, K., Kellermann, K. & Balmann, A. (2006), ‘Agent-based analysis of agricultural policies: an illustration of the agricultural policy simulator agripolis, its adaptation, and behavior.’, Ecology and Society 11(1), 49
Hazell, P. B. & Norton, R. D. (1986), Mathematical Programming for Economic Analysis in Agriculture, Macmillan, New York.
Heckelei, T. & Britz, W. (2005), Models based on positive mathematical programming: state of the art and further extensions, in F. Arﬁni, ed., ‘Modelling agricultural policies: state of the art and new challenges. Proceddings of the 89th European seminar of the European Association of Agricultural Economics’, Monte Università Parma, pp. 48–73.
Kellermann, K., Happe, K., Sahrbacher, C. & Brady, M. (2007), ‘Agripolis 2.0 – documentation of the extended model’, IDEMA working paper 20.
Kellermann, K., Sahrbacher, C. & Balmann, A. (2008), Land markets in agent based models of structural change, in ‘Modelling Agricultural and Rural Development Policies. 107th EAAE Seminar, Sevilla’.
Lobianco, A. (2006), Il sistema agricolo ed alimentare nelle Marche. Rapporto 2005, Edizioni Scientiﬁche Italiane, chapter 2.1, pp. 71–81.
Lobianco, A. (2007), ‘The eﬀects of decoupling on two italian regions. An agent-based model.’, Associazione Bartola PhD Studies, 2.
Makhorin, A. (2007), ‘Gnu linear programming kit. reference manual’. Available from: http://www.gnu.org/software/glpk/
Paris, Q. (1991), An economic interpretation of Linear Programming, Iowa State University Press. Also available in Italian with title Programmazione lineare. Un’interpretazione economica.
Parker, D. C. (2003), ‘Multi-agent systems for the simulation of land-use and land-cover change: A review’, Annals of the Association of American Geographers 93(2), 314–337.
Piorr, A., Ungaro, F., Ciancaglini, A., Happe, K., Sahrbacher, A., Sattler, C., Uthes, S. & Zander, P. (2009), ‘Integrated assessment of future cap policies: land use changes, spatial patterns and targeting’, Environmental Science and Policy. doi:10.1016/j.envsci.2009.01.001.
Romero, C. & Rehman, T. (2003), Multiple criteria analysis for agricultural decisions, Developments in agricultural economics, 2nd edn, Elsevier.
Sahrbacher, C., Schnicke, H., Happe, K. & Graubner, M. (2005), ‘Adaptation of agent-based model agripolis to 11 study regions in the enlarged european union’, IDEMA working paper 10.