Attribute processing in environmental choice analysis: implications for willingness to pay
Danny Campbell (),
Victoria Lorimer,
Claudia Aravena and
W. George Hutchinson
No 91718, 84th Annual Conference, March 29-31, 2010, Edinburgh, Scotland from Agricultural Economics Society
Abstract:
Data from a discrete choice experiment is used to investigate the implications of failing to account for attribute processing strategies (APSs). The research was designed to elicit the economic benefits associated with landscape restoration activities that were intended to remediate environmental damage caused by illegal dumping activities. In this paper we accommodate APSs using an equality constrained latent class model. By retrieving the conditional class membership probabilities we recover estimates of the weights that each respondent assigned to each attribute, which we subsequently use ensure unnecessary weight is not allocated to attributes not attended to by respondents. Results from the analysis provide strong evidence that significant gains in models fit as well as more defensible and reliable willingness to pay estimates can be achieved using when the APSs are accounted for.
Keywords: Environmental; Economics; and; Policy (search for similar items in EconPapers)
Pages: 17
Date: 2010-03-29
New Economics Papers: this item is included in nep-dcm, nep-env and nep-tur
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
https://ageconsearch.umn.edu/record/91718/files/18 ... avena_hutchinson.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ags:aesc10:91718
DOI: 10.22004/ag.econ.91718
Access Statistics for this paper
More papers in 84th Annual Conference, March 29-31, 2010, Edinburgh, Scotland from Agricultural Economics Society Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().