{"title":"Making valuations with the priority heuristic","authors":"Konstantinos V. Katsikopoulos","doi":"10.1016/j.jmp.2024.102883","DOIUrl":null,"url":null,"abstract":"<div><p>The priority heuristic is a lexicographic semi-order for choosing between gambles. It has merits such as predicting, out-of-sample, people's majority choice more accurately than benchmarks such as prospect theory, having been axiomatized, and logically implying major violations of expected utility theory. The heuristic has shortcomings too, such as failing to account for individual differences and intricate choice patterns, and predicting less accurately than various model ensembles and neural networks in some environments. This note focuses on an important purported shortcoming of the heuristic, that it cannot produce valuations of gambles. I point out that the certainty equivalent of a gamble for the priority heuristic is known and suggest that this fact can be used to enhance the scope of the heuristic. Indeed, by making simple auxiliary assumptions and calculations, I demonstrate that the priority heuristic can explain the Saint Petersburg paradox and the equity premium puzzle, and to do so arguably more parsimoniously and plausibly than standard approaches.</p></div>","PeriodicalId":50140,"journal":{"name":"Journal of Mathematical Psychology","volume":"123 ","pages":"Article 102883"},"PeriodicalIF":2.2000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S002224962400052X/pdfft?md5=33d571a5e4e5b946fd089948c0769780&pid=1-s2.0-S002224962400052X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical Psychology","FirstCategoryId":"102","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S002224962400052X","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
The priority heuristic is a lexicographic semi-order for choosing between gambles. It has merits such as predicting, out-of-sample, people's majority choice more accurately than benchmarks such as prospect theory, having been axiomatized, and logically implying major violations of expected utility theory. The heuristic has shortcomings too, such as failing to account for individual differences and intricate choice patterns, and predicting less accurately than various model ensembles and neural networks in some environments. This note focuses on an important purported shortcoming of the heuristic, that it cannot produce valuations of gambles. I point out that the certainty equivalent of a gamble for the priority heuristic is known and suggest that this fact can be used to enhance the scope of the heuristic. Indeed, by making simple auxiliary assumptions and calculations, I demonstrate that the priority heuristic can explain the Saint Petersburg paradox and the equity premium puzzle, and to do so arguably more parsimoniously and plausibly than standard approaches.
期刊介绍:
The Journal of Mathematical Psychology includes articles, monographs and reviews, notes and commentaries, and book reviews in all areas of mathematical psychology. Empirical and theoretical contributions are equally welcome.
Areas of special interest include, but are not limited to, fundamental measurement and psychological process models, such as those based upon neural network or information processing concepts. A partial listing of substantive areas covered include sensation and perception, psychophysics, learning and memory, problem solving, judgment and decision-making, and motivation.
The Journal of Mathematical Psychology is affiliated with the Society for Mathematical Psychology.
Research Areas include:
• Models for sensation and perception, learning, memory and thinking
• Fundamental measurement and scaling
• Decision making
• Neural modeling and networks
• Psychophysics and signal detection
• Neuropsychological theories
• Psycholinguistics
• Motivational dynamics
• Animal behavior
• Psychometric theory