IDEAS home Printed from https://ideas.repec.org/h/spr/lnechp/978-3-642-31301-1_16.html
   My bibliography  Save this book chapter

Rural landscapes in turbulent times: a spatially explicit agent-based model for assessing the impact of agricultural policies

In: Managing Market Complexity

Author

Listed:
  • Marleen Schouten

    (Wageningen University)

  • Nico Polman

    (LEI Wageningen UR)

  • Eugène Westerhof

    (LEI Wageningen UR)

  • Tom Kuhlman

    (LEI Wageningen UR)

Abstract

This paper presents a spatially explicit rural agent-based model which has been developed to assess how agricultural policy interventions, market dynamics and environmental change affect heterogeneous farm agents, their land use and the landscape of which they are part. This model moves beyond current literature by modelling market transactions among agents that are heterogeneous with respect to their economic and environmental characteristics within their spatially explicit landscape. The spatially explicit landscape is described by plot size, natural environmental and agricultural quality, shape, type of land use, intensity of use and distance to the homestead. The model is presented using the Overview, Design concepts, and Details (ODD) protocol. Modelling features are demonstrated by evaluating two different land market implementations which are based on auction mechanisms. We also explore how economic indicators change as the relative market power of buyers and sellers change, by moving from a buyers to a sellers’ market and vice versa.

Suggested Citation

  • Marleen Schouten & Nico Polman & Eugène Westerhof & Tom Kuhlman, 2012. "Rural landscapes in turbulent times: a spatially explicit agent-based model for assessing the impact of agricultural policies," Lecture Notes in Economics and Mathematical Systems, in: Andrea Teglio & Simone Alfarano & Eva Camacho-Cuena & Miguel Ginés-Vilar (ed.), Managing Market Complexity, edition 127, chapter 0, pages 195-207, Springer.
  • Handle: RePEc:spr:lnechp:978-3-642-31301-1_16
    DOI: 10.1007/978-3-642-31301-1_16
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.

    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:spr:lnechp:978-3-642-31301-1_16. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.