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The Regional Multi-Agent Simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies

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  • Lobianco, Antonello
  • Esposti, Roberto

Abstract

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).

Suggested Citation

  • 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.
    • Handle: RePEc:pra:mprapa:25817
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    File URL: https://mpra.ub.uni-muenchen.de/25817/1/MPRA_paper_25817.pdf
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    References listed on IDEAS

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    Cited by:

    1. Fastelli, Laura & Landi, Chiara & Rovai, Massimo & Andreoli, Maria, 2017. "A spatial analysis of terrain features and farming styles in a disadvantaged area of Tuscany (Mugello): implications for the evaluation and the design of CAP payments," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 6(1), May.
    2. Anke Möhring & Gabriele Mack & Albert Zimmermann & Maria Pia Gennaio & Stefan Mann & Ali Ferjani, 2011. "Modellierung von Hofübernahmeund Hofaufgabeentscheidungen in agentenbasierten Modellen," Journal of Socio-Economics in Agriculture (Until 2015: Yearbook of Socioeconomics in Agriculture), Swiss Society for Agricultural Economics and Rural Sociology, vol. 4(1), pages 163-188.
    3. Malawska, Anna & Topping, Christopher John, 2016. "Evaluating the role of behavioral factors and practical constraints in the performance of an agent-based model of farmer decision making," Agricultural Systems, Elsevier, vol. 143(C), pages 136-146.
    4. Kremmydas, Dimitris & Athanasiadis, Ioannis N. & Rozakis, Stelios, 2018. "A review of Agent Based Modeling for agricultural policy evaluation," Agricultural Systems, Elsevier, vol. 164(C), pages 95-106.
    5. Fastelli, Laura & Rovai, Massimo & Andreoli, Maria, 2018. "A Spatial Integrated Database for the Enhancement of the Agricultural Custodianship Role (SIDECAR)—Some preliminary tests using Tuscany as a case-study Region," Land Use Policy, Elsevier, vol. 78(C), pages 791-802.
    6. A. Bonfiglio & B. Camaioni & S. Coderoni & R. Esposti & F. Pagliacci & F. Sotte, 2016. "Where does EU money eventually go? The distribution of CAP expenditure across the European space," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 43(4), pages 693-727, November.
    7. Ran Sun & James Nolan & Suren Kulshreshtha, 2022. "Agent-based modeling of policy induced agri-environmental technology adoption," SN Business & Economics, Springer, vol. 2(8), pages 1-26, August.
    8. Lisa Baldi & Arfini, Filippo & Calzolai, Sara & Donati, Michele, 2023. "CAP reform and GHG emissions: policy assessment using a PMP agent-based model," 97th Annual Conference, March 27-29, 2023, Warwick University, Coventry, UK 334520, Agricultural Economics Society - AES.
    9. Mack, Gabriele & Möhring, Anke & Ferjani, Ali & Zimmermann, Albert & Mann, Stefan, 2013. "Transfer of single farm payment entitlements to farm successors: impact on structural change and rental prices in Switzerland," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 2(2), pages 1-18, August.
    10. D’Urso, Pierpaolo & Manca, Germana & Waters, Nigel & Girone, Stefania, 2019. "Visualizing regional clusters of Sardinia's EU supported agriculture: A Spatial Fuzzy Partitioning Around Medoids," Land Use Policy, Elsevier, vol. 83(C), pages 571-580.
    11. Albert Zimmermann & Anke Möhring & Gabriele Mack & Ali Ferjani & Stefan Mann, 2015. "Pathways to Truth: Comparing Different Upscaling Options for an Agent-Based Sector Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(4), pages 1-11.
    12. Roberto Esposti, 2022. "The Coevolution of Policy Support and Farmers' Behaviour. An investigation on Italian agriculture over the 2008-2019 period," Working Papers 464, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    13. Reidsma, Pytrik & Janssen, Sander & Jansen, Jacques & van Ittersum, Martin K., 2018. "On the development and use of farm models for policy impact assessment in the European Union – A review," Agricultural Systems, Elsevier, vol. 159(C), pages 111-125.
    14. Dimitris Kremmydas, 2012. "Agent based modeling for agricultural policy evaluation: A review," Working Papers 2012-3, Agricultural University of Athens, Department Of Agricultural Economics.
    15. Mack, Gabriele & Ferjani, Ali & Mohring, Anke & Zimmerman, Albert & Mann, Stefan, 2015. "How did farmers act? An ex-post validation of normative and positive mathematical programming for an agent-based sector model," 2015 Conference, August 9-14, 2015, Milan, Italy 212201, International Association of Agricultural Economists.
    16. Viaggi, Davide & Bartolini, Fabio & Raggi, Meri & Sardonini, Laura, 2010. "The role of the Common Agricultural Policy in the spatial location of agricultural activities," 116th Seminar, October 27-30, 2010, Parma, Italy 95242, European Association of Agricultural Economists.

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    More about this item

    Keywords

    Agent-Based Modelling; Mathematical Programming; Explicit Spatial Analysis; Common Agricultural Policy;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • 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

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