Eliciting risk attitudes -- how to avoid mean and variance bias in Holt-and-Laury lotteries
Norbert Hirschauer,
Oliver Musshoff,
Syster C. Maart-Noelck and
Sven Gruener
Applied Economics Letters, 2014, vol. 21, issue 1, 35-38
Abstract:
This article shows that including inconsistent subjects in a Holt-and-Laury analysis will bias the mean, as well as the variance of the risk attitudes of the subject group of interest to an extent that cannot be determined a priori and that must not be neglected. One might be tempted to simply drop inconsistent subjects from the analysis to avoid such biases in a population-level analysis. Unfortunately, however, this is not a solution: first, the sample size may fall to an unacceptably low level. Second -- and even more important -- simply dropping inconsistent subjects from the analysis may introduce another unknown bias since systematic differences may exist in the risk preferences of those who answer consistently and those who do not. One must thus conclude that, if the group of interest contains a large proportion of inconsistent subjects, the whole set-up of the Holt-and-Laury lottery (HLL) experiment must be critically reconsidered and the experiment eventually repeated.
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
http://hdl.handle.net/10.1080/13504851.2013.835474 (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:apeclt:v:21:y:2014:i:1:p:35-38
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEL20
DOI: 10.1080/13504851.2013.835474
Access Statistics for this article
Applied Economics Letters is currently edited by Anita Phillips
More articles in Applied Economics Letters from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().