|Appears in Collections:||Economics Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Modelling attribute non-attendance in choice experiments for rural landscape valuation|
Gilbride, Timothy J
Hensher, David A
discrete choice modelling
latent class models
stochastic attribute selection models
|Citation:||Scarpa R, Gilbride TJ, Campbell D & Hensher DA (2009) Modelling attribute non-attendance in choice experiments for rural landscape valuation, European Review of Agricultural Economics, 36 (2), pp. 151-174.|
|Abstract:||Non-market effects of agriculture are often estimated using discrete choice models from stated preference surveys. In this context we propose two ways of modelling attribute non-attendance. The first involves constraining coefficients to zero in a latent class framework, whereas the second is based on stochastic attribute selection and grounded in Bayesian estimation. Their implications are explored in the context of a stated preference survey designed to value landscapes in Ireland. Taking account of attribute non-attendance with these data improves fit and tends to involve two attributes one of which is likely to be cost, thereby leading to substantive changes in derived welfare estimates.|
|Rights:||The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
|EurRev_2009.pdf||179.12 kB||Adobe PDF||Under Embargo until 31/12/2999 Request a copy|
Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependent on the depositor still being contactable at their original email address.
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.