Judging statistical models of individual decision making under risk using in- and out-of-sample criteria

Andreas Drichoutis and Jayson Lusk

MPRA Paper from University Library of Munich, Germany

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 two popular error specifications (Luce vs. Fechner), with and without accounting for contextual utility, for two different conceptual models (expected utility and rank-dependent expected utility) using in- and out-of-sample selection criteria. We find drastically different inferences about structural risk preferences across the competing specifications. Overall, a mixture model combining the two conceptual models assuming Fechner error and contextual utility provides the best fit of the data both in- and out-of-sample.

Keywords: error specification; expected utility theory; experiment; probability weighting; rank dependent utility; risk (search for similar items in EconPapers)
JEL-codes: C25 C91 D81 (search for similar items in EconPapers)
Date: 2012-05-19
New Economics Papers: this item is included in nep-ore and nep-upt
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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https://mpra.ub.uni-muenchen.de/38951/1/MPRA_paper_38951.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/38973/1/MPRA_paper_38973.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/42019/1/MPRA_paper_42019.pdf revised version (application/pdf)

Related works:
Journal Article: Judging Statistical Models of Individual Decision Making under Risk Using In- and Out-of-Sample Criteria (2014)
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