A replication of willingness-to-pay estimates in "An adding up test on contingent valuations of river and lake quality" (Land Economics, 2015)
John Whitehead
No 2017-55, Economics Discussion Papers from Kiel Institute for the World Economy (IfW Kiel)
Abstract:
Desvousges, Mathews and Train (2015) find that their contingent valuation method (CVM) survey data does not pass the adding up test using a nonparametric estimate of mean willingness-to-pay. Their data suffers from non-monotocity, flat bid curve and fat tails problems, each of which can cause willingness-to-pay estimates to be sensitive to the approach chosen to measure the central tendency. Using additional parametric approaches that are standard in the literature, I find that willingness to pay for the whole is not statistically different from the sum of the parts in two of three additional estimates. In additional robustness checks, all six of the additional tests find that the WTP estimates do not reject the adding up hypothesis. The negative result in Desvousges, Mathews and Train (2015) is not robust to these alternative approaches to willingness-to-pay estimation.
Keywords: contingent valuation; adding up test; willingness-to-pay (search for similar items in EconPapers)
JEL-codes: Q51 (search for similar items in EconPapers)
Date: 2017
New Economics Papers: this item is included in nep-dcm and nep-env
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.economics-ejournal.org/economics/discussionpapers/2017-55
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:zbw:ifwedp:201755
Access Statistics for this paper
More papers in Economics Discussion Papers from Kiel Institute for the World Economy (IfW Kiel) Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().