{"title":"Testing models of complexity aversion","authors":"Konstantinos Georgalos, Nathan Nabil","doi":"10.1016/j.socec.2025.102354","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51637,"journal":{"name":"Journal of Behavioral and Experimental Economics","volume":"116 ","pages":"Article 102354"},"PeriodicalIF":1.6000,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Behavioral and Experimental Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214804325000217","RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍:
The Journal of Behavioral and Experimental Economics (formerly the Journal of Socio-Economics) welcomes submissions that deal with various economic topics but also involve issues that are related to other social sciences, especially psychology, or use experimental methods of inquiry. Thus, contributions in behavioral economics, experimental economics, economic psychology, and judgment and decision making are especially welcome. The journal is open to different research methodologies, as long as they are relevant to the topic and employed rigorously. Possible methodologies include, for example, experiments, surveys, empirical work, theoretical models, meta-analyses, case studies, and simulation-based analyses. Literature reviews that integrate findings from many studies are also welcome, but they should synthesize the literature in a useful manner and provide substantial contribution beyond what the reader could get by simply reading the abstracts of the cited papers. In empirical work, it is important that the results are not only statistically significant but also economically significant. A high contribution-to-length ratio is expected from published articles and therefore papers should not be unnecessarily long, and short articles are welcome. Articles should be written in a manner that is intelligible to our generalist readership. Book reviews are generally solicited but occasionally unsolicited reviews will also be published. Contact the Book Review Editor for related inquiries.