The statistical power of individual-level risk preference estimation

Brian Albert Monroe ()
Additional contact information
Brian Albert Monroe: University College Dublin

Journal of the Economic Science Association, 2020, vol. 6, issue 2, No 5, 168-188

Abstract: Abstract Accurately estimating risk preferences is of critical importance when evaluating data from many economic experiments or strategic interactions. I use a simulation model to conduct power analyses over two lottery batteries designed to classify individual subjects as being best explained by one of a number of alternative specifications of risk preference models. I propose a case in which there are only two possible alternatives for classification and find that the statistical methods used to classify subjects result in type I and type II errors at rates far beyond traditionally acceptable levels. These results suggest that subjects in experiments must make significantly more choices, or that traditional lottery pair batteries need to be substantially redesigned to make accurate inferences about the risk preference models that characterize a subject’s choices.

Keywords: Power analysis; Risk preferences; Experimental economics; Expected utility theory; Rank dependent utility (search for similar items in EconPapers)
JEL-codes: C12 C13 C18 C52 C90 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s40881-020-00098-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:spr:jesaex:v:6:y:2020:i:2:d:10.1007_s40881-020-00098-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/40881

DOI: 10.1007/s40881-020-00098-x

Access Statistics for this article

Journal of the Economic Science Association is currently edited by Nikos Nikiforakis and Robert Slonim

More articles in Journal of the Economic Science Association from Springer, Economic Science Association Contact information at EDIRC.
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().