On the inference about willingness to pay distribution using contingent valuation data

Mikolaj Czajkowski, Ewa Zawojska, Norman Meade, Ronaldo Seroa da Motta, Mike Welsh and Ramon Ortiz ()
Additional contact information
Norman Meade: Independent consultant
Ronaldo Seroa da Motta: State University of Rio de Janeiro
Mike Welsh: Independent consultant

No 2022-08, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: Although contingent valuation (CV) is one of the main sources of estimates of non-market values of environmental goods, little guidance exists regarding parametric approaches for modelling CV data, which would reliably estimate willingness-to-pay (WTP) values based on binary choice, payment card or open-ended preference elicitation data, among others. CV studies often rely on relatively simple approaches to modeling stated preference responses, without examining alternative modelling specifications. Lower-bound, non-parametric estimates seem to be preferred in legal cases, while studies that apply parametric approaches often select a specification among a limited set of commonly used distributions. To enhance the reliability of CV-based WTP estimates, we propose to adopt a more flexible approach to parametric modelling of a WTP distribution, by considering a wide range of parametric model specifications. We demonstrate the advantages of the proposed approach using databases from two large CV studies: the eutrophication reduction valuation for the Baltic Sea Action Plan and the Deepwater Horizon natural resource damage assessment. We find non-negligible differences in WTP value estimates across models with different assumed parametric distributions, and we observe the variation in the values to decrease when only better-fitting models are considered. This emphasizes the need for cautiously identifying the model best fitting to the data, instead of choosing a specification ad hoc without taking into account alternative parametric distributions. Focusing on the best-fitting parametric specifications, we provide alternative WTP value estimates for the two empirical cases studied.

Keywords: contingent valuation; parametric modelling; stated preferences; willingness to pay; welfare estimates (search for similar items in EconPapers)
JEL-codes: D61 H41 H43 Q51 (search for similar items in EconPapers)
Pages: 59 pages
Date: 2022
New Economics Papers: this item is included in nep-agr, nep-dcm, nep-env and nep-upt
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https://www.wne.uw.edu.pl/download_file/1415/0 First version, 2022 (application/pdf)

Related works:
Journal Article: On the inference about a willingness-to-pay distribution using contingent valuation data (2024)
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Persistent link: https://EconPapers.repec.org/RePEc:war:wpaper:2022-08

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