Testing models of complexity aversion

Georgalos, Konstantinos and Nabil, Nathan (2025) Testing models of complexity aversion. Journal of Behavioral and Experimental Economics, 116: 102354. ISSN 2214-8043

Text (complexity_JBEE_rev2)
complexity_JBEE_rev2.pdf - Accepted Version
Available under License Creative Commons Attribution.
Download (414kB)

Abstract

In this study we aim to test behavioural models of complexity aversion. In this framework, complexity is defined as a function of the number of outcomes in a lottery. Using Bayesian inference techniques, we re-analyse data from a lottery-choice experiment. We quantitatively specify and estimate adaptive toolbox models of cognition, which we rigorously test against popular expectation-based models; modified to account for complexity aversion. We find that for the majority of the subjects, a toolbox model performs best both in-sample, and with regards to its predictive capacity out-of-sample, suggesting that individuals resort to heuristics in the presense of extreme complexity.

Item Type:

Journal Article

Journal or Publication Title:

Journal of Behavioral and Experimental Economics

Uncontrolled Keywords:

/dk/atira/pure/subjectarea/asjc/3200/3202

Subjects:

?? bayesian modellingcomplexity aversionheuristicsrisky choicetoolbox modelsapplied psychologyeconomics and econometricsgeneral social sciencessocial sciences(all) ??

Departments:

Lancaster University Management School > Economics

ID Code:

229328

Deposited By:

ep_importer_pure

Deposited On:

12 May 2025 09:45

Refereed?:

Yes

Published?:

Published

Last Modified:

17 May 2025 02:12

URI:

https://eprints.lancs.ac.uk/id/eprint/229328