Improving meta-analyses on hypothetical bias by using separate models for private and public goods

Baoubadi Atozou, Stéphane Bergeron, Maurice Doyon and Lota Tamini

Journal of Environmental Economics and Policy, 2022, vol. 11, issue 3, 260-271

Abstract: Previous meta-analyses examined hypothetical bias studies with the aim of identifying characteristics of stated preference (SP) design that potentially reduce hypothetical bias. However, previous meta-analyses combined observations for both public and private goods in their models. In this paper, we argue that eliciting values for public and private goods should be considered in separate models. Individuals’ behaviours, the choice of mechanism and the efficiency of mitigation techniques are specific to each type of good. Separating the models should allow more precise model specification and better identification of design effects. With two meta-regressions hierarchical mixed-effect models we provide the first meta-analysis for public and private goods separately. This approach provides specific information regarding SP design and better insight into the efficiency of mitigation techniques to reduce hypothetical bias.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/21606544.2021.1971114 (text/html)
Access to full text is restricted to subscribers.

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:taf:teepxx:v:11:y:2022:i:3:p:260-271

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/teep20

DOI: 10.1080/21606544.2021.1971114

Access Statistics for this article

Journal of Environmental Economics and Policy is currently edited by Ken Willis

More articles in Journal of Environmental Economics and Policy from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().