IDEAS home Printed from https://ideas.repec.org/p/ags/aare11/100735.html
   My bibliography  Save this paper

Ecological Afforestation in China: A Market-based Approach

Author

Listed:
  • Xu, Jintao
  • Zhang, Haipeng
  • Bennett, Jeffrey W.
  • Wang, Xuehong
  • Eigenraam, Mark

Abstract

This article focuses on the program of Ecological Afforestation on barren lands, degraded arable lands, harvested sites and sloped farmland in Sichuan, China. Farmers were given the opportunity to propose afforestation activities for which they would be paid an specified amount. These bids and predictions of the expected environmental benefits to be generated were used to assess the net benefit of each proposal. Most features of the bidding scheme were successfully implemented and improvements in the economic efficiency of the afforestation scheme were observed. The market-based approach is demonstrated to be a practical way forward for Ecological Afforestation in China. The bidding scheme showed savings of approximately 110,000 Yuan when compared to past grant based programs. However, the bidding scheme is shown to increase the transaction costs of achieving the policy goal, by about 30 per cent compared to the previous ‘command and control’ regime. When transaction costs are accounted for there are still cost savings when compared to the command and control approach. Finding effective methods to reduce transaction costs will be key to any future implementation of the Ecological Afforestation bidding scheme.

Suggested Citation

  • Xu, Jintao & Zhang, Haipeng & Bennett, Jeffrey W. & Wang, Xuehong & Eigenraam, Mark, 2011. "Ecological Afforestation in China: A Market-based Approach," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100735, Australian Agricultural and Resource Economics Society.
  • Handle: RePEc:ags:aare11:100735
    as

    Download full text from publisher

    File URL: http://purl.umn.edu/100735
    Download Restriction: no

    Citations

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


    Cited by:

    1. Xuehong Wang & Jeff Bennett & Jintao Xu & Haipeng Zhang, 2011. "An auction scheme for land use change in Sichuan Province, China," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 55(10), pages 1269-1288, November.

    More about this item

    Keywords

    Environmental Economics and Policy;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ags:aare11:100735. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search). General contact details of provider: http://edirc.repec.org/data/aaresea.html .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.