Information and Learning in Stated-Preference Studies
Mikolaj Czajkowski (),
Nick Hanley (),
William Neilson () and
Katherine Simpson ()
Additional contact information
Katherine Simpson: Economics Division, University of Stirling, Scotland
Authors registered in the RePEc Author Service: Katherine Needham
No 2016-20, Working Papers from Faculty of Economic Sciences, University of Warsaw
We use experimental variation to influence how people learn a given amount of objective, scientific information about an unfamiliar public good. We then estimate the impact of treatment on valuations for that good in a stated preference survey. Our main treatment, a pre-survey multiple choice quiz about objective public good attributes, increased learning rates by over 60%. We find that despite increasing learning and retention rates, treatment had no statistically significant impact on mean nor variance of the distribution of valuations. We show with a very simple theoretical model this result is consistent with a model of confirmatory bias used by agents in stated preference surveys and inconsistent with other models of preference formation.
Keywords: Information; Updating; Preferences; Public Goods (search for similar items in EconPapers)
JEL-codes: D01 D83 Q41 (search for similar items in EconPapers)
Pages: 54 pages
New Economics Papers: this item is included in nep-dcm and nep-exp
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7) Track citations by RSS feed
Downloads: (external link)
http://www.wne.uw.edu.pl/index.php/download_file/2941/ First version, 2016 (application/pdf)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:war:wpaper:2016-20
Access Statistics for this paper
More papers in Working Papers from Faculty of Economic Sciences, University of Warsaw Contact information at EDIRC.
Bibliographic data for series maintained by Marcin Bąba ().