Joint estimation of contingent valuation survey responses
Timothy Park and
John Loomis
Environmental & Resource Economics, 1996, vol. 7, issue 2, 149-162
Abstract:
Hanemann's utility difference model for the dichotomous choice contingent valuation method is modified to account for interrelationships between responses to a set of contingent valuation questions. A nonlinear seemingly unrelated regression model is presented to jointly estimate the probit models and to derive WTP from the CV responses. The model is used to test and impose restrictions derived from economic theory on the utility difference model. Mean WTP estimates for three different types of changes in the quality of California deer hunting were uniformly lower for the joint response probit model compared to a set of independent probit models. Copyright Kluwer Academic Publishers 1996
Keywords: Contingent valuation; utility difference model; joint dichotomous responses (search for similar items in EconPapers)
Date: 1996
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)
Downloads: (external link)
http://hdl.handle.net/10.1007/BF00699289 (text/html)
Access to full text is restricted to subscribers.
Related works:
Working Paper: Joint Estimation of Contingent Valuation Survey Responses (1991) 
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:kap:enreec:v:7:y:1996:i:2:p:149-162
Ordering information: This journal article can be ordered from
http://www.springer. ... al/journal/10640/PS2
DOI: 10.1007/BF00699289
Access Statistics for this article
Environmental & Resource Economics is currently edited by Ian J. Bateman
More articles in Environmental & Resource Economics from Springer, European Association of Environmental and Resource Economists Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().