测试复杂性厌恶模型

IF 1.6 3区经济学 Q2 ECONOMICS

Journal of Behavioral and Experimental Economics Pub Date : 2025-03-11 DOI:10.1016/j.socec.2025.102354

Konstantinos Georgalos, Nathan Nabil

{"title":"测试复杂性厌恶模型","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":"{\"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}","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

摘要

在这项研究中，我们的目的是测试复杂性厌恶的行为模型。在这个框架中，复杂性被定义为彩票结果数量的函数。使用贝叶斯推理技术，我们重新分析了来自彩票选择实验的数据。我们定量地指定和估计认知的自适应工具箱模型，我们严格测试流行的基于期望的模型；修改以考虑复杂性厌恶。我们发现，对于大多数受试者来说，工具箱模型在样本内和样本外的预测能力方面都表现最好，这表明个体在极端复杂性的情况下求助于启发式。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Testing models of complexity aversion

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Journal of Behavioral and Experimental Economics ECONOMICS-

CiteScore

2.60

自引率

12.50%

发文量

113

审稿时长

83 days

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.