Advanced Search
MyIDEAS: Login

Reducing Bias from Choice Experiments Estimates in the Demand for Recreation

Contents:

Author Info

  • Longo, Alberto
  • Rowan, Emma
  • Hutchinson, W. George
Registered author(s):

    Abstract

    In valuing the demand for recreation, the literature has grown from using revealed preference methods to applying stated preference methods, namely contingent valuation and choice modelling. Recent attempts have merged revealed and stated preference data to exploit the strengths of both sources of data. We use contingent behaviour and choice experiments data to show that, with choice experiments exercises, when respondents are asked to choose which improvement programme they prefer for a site with recreational opportunities, failing to consider the information explaining the number of visits that respondents intend to take to a recreational site under each hypothetical programme leads to biased coefficients estimates in the models for the choice experiments data.

    Download Info

    If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
    File URL: http://purl.umn.edu/91827
    Download Restriction: no

    Bibliographic Info

    Paper provided by Agricultural Economics Society in its series 84th Annual Conference, March 29-31, 2010, Edinburgh, Scotland with number 91827.

    as in new window
    Length:
    Date of creation: 29 Mar 2010
    Date of revision:
    Handle: RePEc:ags:aesc10:91827

    Contact details of provider:
    Email:
    Web page: http://www.aes.ac.uk/
    More information through EDIRC

    Related research

    Keywords: travel cost; contingent behaviour; choice experiments; revealed preferences; stated preferences; Environmental Economics and Policy; Q51; Q26;

    Find related papers by JEL classification:

    This paper has been announced in the following NEP Reports:

    References

    References listed on IDEAS
    Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
    as in new window
    1. John C. Whitehead & Subhrendu K. Pattanayak & George L. Van Houtven & Brett R. Gelso, 2005. "Combining Revealed and Stated Preference Data to Estimate the Nonmarket Value of Ecological Services: An Assessment of the State of the Science," Working Papers 05-19, Department of Economics, Appalachian State University, revised 2007.
    Full references (including those not matched with items on IDEAS)

    Citations

    Lists

    This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

    Statistics

    Access and download statistics

    Corrections

    When requesting a correction, please mention this item's handle: RePEc:ags:aesc10:91827. 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).

    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 references are entirely missing, you can add them using this form.

    If the full references list an item that is present in RePEc, but the system did not link 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 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.