Judging Statistical Models of Individual Decision Making under Risk Using In- and Out-of-Sample Criteria
Andreas Drichoutis and
Jayson Lusk
PLOS ONE, 2014, vol. 9, issue 7, 1-13
Abstract:
Despite the fact that conceptual models of individual decision making under risk are deterministic, attempts to econometrically estimate risk preferences require some assumption about the stochastic nature of choice. Unfortunately, the consequences of making different assumptions are, at present, unclear. In this paper, we compare three popular error specifications (Fechner, contextual utility, and Luce error) for three different preference functionals (expected utility, rank-dependent utility, and a mixture of those two) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing functionals and error specifications. Expected utility theory is least affected by the selection of the error specification. A mixture model combining the two conceptual models assuming contextual utility provides the best fit of the data both in- and out-of-sample.
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)
Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0102269 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 02269&type=printable (application/pdf)
Related works:
Working Paper: Judging statistical models of individual decision making under risk using in- and out-of-sample criteria (2012) 
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:plo:pone00:0102269
DOI: 10.1371/journal.pone.0102269
Access Statistics for this article
More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().