IDEAS home Printed from https://ideas.repec.org/a/zbw/espost/320715.html
   My bibliography  Save this article

Strategic bidding behaviour in agricultural land rental markets: Reinforcement learning in an agent-based model

Author

Listed:
  • Njiru, Ruth Dionisia Gicuku
  • Dong, Changxing
  • Appel, Franziska
  • Balmann, Alfons

Abstract

Agricultural land markets are crucial for efficient land allocation, yet they face complexities arising from land characteristics and the heterogeneous nature of market participants. This study explores how to address heterogeneity in the modelling process for land markets models by integrating Deep Reinforcement Learning (DRL) into the agent-based model AgriPoliS, to model strategic bidding behaviour. The simulations demonstrates that a DRL agent adapts its bidding strategies based on long-term growth objectives, experience, competitive interactions and adaptive decision-making leading to increased land rental and farm growth compared to a standard agent using a fixed bidding strategy. The results reveal how strategic behaviour not only improve individual farm performance but also affect neighbouring farms, emphasizing the dynamic interactions within land markets. By capturing the agent’s strategic behaviour, this work contributes towards more realistic modelling of agricultural land market dynamics and offers insights into the implications of potential land market regulations. Future research will explore multi-agent frameworks to further refine these interactions and address the limitations of static bidding strategies.

Suggested Citation

  • Njiru, Ruth Dionisia Gicuku & Dong, Changxing & Appel, Franziska & Balmann, Alfons, 2025. "Strategic bidding behaviour in agricultural land rental markets: Reinforcement learning in an agent-based model," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 28(2), pages 392-422.
  • Handle: RePEc:zbw:espost:320715
    DOI: 10.22434/ifamr.1126
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/320715/1/Njiru_2025_Strategic_bidding_behaviour.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22434/ifamr.1126?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Margarian, Anne, 2014. "The reflexive relationship between local land markets and farmers’ strategies in Germany," Studies in Agricultural Economics, Research Institute for Agricultural Economics, vol. 116(01), pages 1-12, April.
    2. Heinrich, Florian & Appel, Franziska & Balmann, Alfons, 2019. "Can land market regulations fulfill their promises?," FORLand Working Papers 12 (2019), Humboldt University Berlin, DFG Research Unit 2569 FORLand "Agricultural Land Markets – Efficiency and Regulation".
    3. de Janvry, Alain & Gordillo, Gustavo & Sadoulet, Elisabeth & Platteau, Jean-Philippe (ed.), 2001. "Access to Land, Rural Poverty, and Public Action," OUP Catalogue, Oxford University Press, number 9780199242177.
    4. An, Li, 2012. "Modeling human decisions in coupled human and natural systems: Review of agent-based models," Ecological Modelling, Elsevier, vol. 229(C), pages 25-36.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dong, Changxing & Njiru, Ruth Dionisia Gicuku & Appel, Franziska, 2025. "Deep Reinforcement Learning in agent-based model AgriPoliS to simulate strategic land market interactions," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 83, pages 1-18.
    2. Ficko, Andrej & Boncina, Andrej, 2013. "Probabilistic typology of management decision making in private forest properties," Forest Policy and Economics, Elsevier, vol. 27(C), pages 34-43.
    3. Qingxu Huang & Dawn C Parker & Tatiana Filatova & Shipeng Sun, 2014. "A Review of Urban Residential Choice Models Using Agent-Based Modeling," Environment and Planning B, , vol. 41(4), pages 661-689, August.
    4. Kamel Louhichi & Aymeric Ricome & Sergio Gomez y Paloma, 2022. "Impacts of agricultural taxation in Sub‐Saharan Africa: Insights from agricultural produce cess in Tanzania," Agricultural Economics, International Association of Agricultural Economists, vol. 53(5), pages 671-686, September.
    5. Bindewald, Eckart, 2017. "A survey suggests individual priorities are virtually unique: Implications for group dynamics, goal achievement and ecology," Ecological Modelling, Elsevier, vol. 362(C), pages 69-79.
    6. James D. A. Millington & Hang Xiong & Steve Peterson & Jeremy Woods, 2017. "Integrating Modelling Approaches for Understanding Telecoupling: Global Food Trade and Local Land Use," Land, MDPI, vol. 6(3), pages 1-18, August.
    7. Xia, Min & Zhang, Yanyuan & Zhang, Zihong & Liu, Jingjie & Ou, Weixin & Zou, Wei, 2020. "Modeling agricultural land use change in a rapid urbanizing town: Linking the decisions of government, peasant households and enterprises," Land Use Policy, Elsevier, vol. 90(C).
    8. Coronese, Matteo & Occelli, Martina & Lamperti, Francesco & Roventini, Andrea, 2023. "AgriLOVE: Agriculture, land-use and technical change in an evolutionary, agent-based model," Ecological Economics, Elsevier, vol. 208(C).
    9. Matthew J. Baker & Jonathan Conning, 2023. "A Model of Enclosures: Coordination, Conflict, and Efficiency in the Transformation of Land Property Rights," Papers 2311.01592, arXiv.org, revised Jan 2025.
    10. Grimm, Volker & Berger, Uta, 2016. "Structural realism, emergence, and predictions in next-generation ecological modelling: Synthesis from a special issue," Ecological Modelling, Elsevier, vol. 326(C), pages 177-187.
    11. Anshuka Anshuka & Floris F. Ogtrop & David Sanderson & Simone Z. Leao, 2022. "A systematic review of agent-based model for flood risk management and assessment using the ODD protocol," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 112(3), pages 2739-2771, July.
    12. Handi Chandra‐Putra & Clinton J. Andrews, 2020. "An integrated model of real estate market responses to coastal flooding," Journal of Industrial Ecology, Yale University, vol. 24(2), pages 424-435, April.
    13. Goetghebuer, Tatiana & Platteau, Jean-Philippe, 2010. "Inheritance patterns in migration-prone communities of the Peruvian Highlands," Journal of Development Economics, Elsevier, vol. 93(1), pages 71-87, September.
    14. Nicholas R. Magliocca, 2020. "Agent-Based Modeling for Integrating Human Behavior into the Food–Energy–Water Nexus," Land, MDPI, vol. 9(12), pages 1-25, December.
    15. Panagiotis Reklitis & Damianos P. Sakas & Panagiotis Trivellas & Giannis T. Tsoulfas, 2021. "Performance Implications of Aligning Supply Chain Practices with Competitive Advantage: Empirical Evidence from the Agri-Food Sector," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    16. Keijiro Otsuka & Yanyan Liu & Futoshi Yamauchi, 2016. "The future of small farms in Asia," Development Policy Review, Overseas Development Institute, vol. 34(3), pages 441-461, May.
    17. Jonas Friege & Georg Holtz & Emile Chappin, 2016. "Exploring Homeowners’ Insulation Activity," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 19(1), pages 1-4.
    18. Baland, Jean-Marie & Gaspart, Frederic & Platteau, Jean-Philippe & Place, Frank, 2007. "The Distributive Impact of Land Markets in Uganda," Economic Development and Cultural Change, University of Chicago Press, vol. 55(2), pages 283-311, January.
    19. Ondoua Ondoua, Valerie Hervé & Ntieche, Adamou & Nzepang, Fabrice & Mbondo, Georges Dieudonné, 2025. "Réexamen du lien entre formation et rendement agricole : cas des cacaoculteurs du grand sud au Cameroun [Re-examining the link between training and agricultural yield: the case of cocoa farmers in ," MPRA Paper 125689, University Library of Munich, Germany.
    20. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • Q18 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Agricultural Policy; Food Policy; Animal Welfare Policy

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:espost:320715. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zbwkide.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.