Harmful choices

Angelo Petralia
{"title":"Harmful choices","authors":"Angelo Petralia","doi":"arxiv-2408.01317","DOIUrl":null,"url":null,"abstract":"We investigate the choice behavior of a decision maker (DM) who harms\nherself, by maximizing some distortion of her true preference, in which the\nfirst $i$ alternatives are moved to the bottom, in a reversed order. The\ndeterministic declination of our pattern has no empirical power, but it allows\nto define a degree of self-punishment, which measures the extent of the denial\nof pleasure adopted by the DM in her decision. We analyze irrational choices\nthat display the lowest degree of self-punishment, and a characterization of\nthem is provided. Moreover, we characterize the choice behavior that exhibits\nthe highest degree of self-punishment, and we show that it comprises almost all\nchoices. We also characterize stochastic self-punishment, which collects all\nthe Random Utility Models (RUMs) whose support is restricted to the harmful\ndistortions of some preference. Full identification of the DM's preference and\nrandomization over its harmful distortions is allowed if each alternative is\nselected from the ground set with probability greater than zero. Finally, the\ndegree of self-punishment of harmful stochastic choices is characterized.","PeriodicalId":501188,"journal":{"name":"arXiv - ECON - Theoretical Economics","volume":"188 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - ECON - Theoretical Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.01317","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

We investigate the choice behavior of a decision maker (DM) who harms herself, by maximizing some distortion of her true preference, in which the first $i$ alternatives are moved to the bottom, in a reversed order. The deterministic declination of our pattern has no empirical power, but it allows to define a degree of self-punishment, which measures the extent of the denial of pleasure adopted by the DM in her decision. We analyze irrational choices that display the lowest degree of self-punishment, and a characterization of them is provided. Moreover, we characterize the choice behavior that exhibits the highest degree of self-punishment, and we show that it comprises almost all choices. We also characterize stochastic self-punishment, which collects all the Random Utility Models (RUMs) whose support is restricted to the harmful distortions of some preference. Full identification of the DM's preference and randomization over its harmful distortions is allowed if each alternative is selected from the ground set with probability greater than zero. Finally, the degree of self-punishment of harmful stochastic choices is characterized.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
有害的选择
我们研究了一个决策者(DM)的选择行为,这个决策者通过最大化其真实偏好的某种扭曲来伤害自己,在这种扭曲中,前 $i$ 个备选方案以相反的顺序被移到了底部。我们这种模式的决定性拒绝没有经验可循,但它允许我们定义自我惩罚的程度,以衡量 DM 在决策中对快乐的否定程度。我们分析了自我惩罚程度最低的非理性选择,并对它们进行了描述。此外,我们还描述了自我惩罚程度最高的选择行为,并证明它几乎包含了所有的选择。我们还描述了随机自我惩罚的特征,它收集了所有随机效用模型(RUM),这些模型的支持被限制在某些偏好的有害偏好上。如果每个备选方案从地面集中选出的概率大于零,那么就可以完全识别 DM 的偏好,并对其有害扭曲进行随机化。最后,对有害随机选择的自我惩罚程度进行了描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Expert Classification Aggregation Approximately Optimal Auctions With a Strong Bidder Beyond Rationality: Unveiling the Role of Animal Spirits and Inflation Extrapolation in Central Bank Communication of the US The Extreme Points of Fusions A Statistical Equilibrium Approach to Adam Smith's Labor Theory of Value
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1