Estimating the Benefits to Florida Households from Avoiding Another Gulf Oil Spill Using the Contingent Valuation Method: Internal Validity Tests with Probability-based and Opt-in Samples

John Whitehead, Andrew Ropicki, John Loomis, Sherry Larkin, Tim Haab and Sergio Alvarez

No 21-13, Working Papers from Department of Economics, Appalachian State University

Abstract: This paper evaluates the importance of contingent valuation method data quality by examining differences in results between probability-based and opt-in internet samples. Our data is from a survey estimating passive use losses associated with the BP/Deepwater Horizon oil spill to Florida residents. Several internal tests of validity are conducted. We find that the willingness to pay estimates from the opt-in sample may be biased upwards and only the probability-based sample data pass the scope test. In general, we conclude that the probability-based sample data is of higher quality. Key Words: contingent valuation, scope test, probability-based sample data; opt-in sample data

JEL-codes: Q51 (search for similar items in EconPapers)
Date: 2021
New Economics Papers: this item is included in nep-ara, nep-dcm, nep-ene and nep-env
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://econ.appstate.edu/RePEc/pdf/wp2113.pdf (application/pdf)

Related works:
Journal Article: Estimating the benefits to Florida households from avoiding another Gulf oil spill using the contingent valuation method: Internal validity tests with probability‐based and opt‐in samples (2023)
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:apl:wpaper:21-13

Access Statistics for this paper

More papers in Working Papers from Department of Economics, Appalachian State University Contact information at EDIRC.
Bibliographic data for series maintained by O. Ashton Morgan ().