.png){kind=icon}
返回
.png){kind=icon}
.png){kind=icon}
摘要
En 中文
Context-dependent individual choice challenges the principle of utility maximization. I explain context dependence as the optimal response of an imperfectly informed agent to the ease of comparison of the options. I introduce a discrete choice model, the Bayesian probit, which allows the analyst to identify stable preferences from context-dependent choice data. My model accommodates observed behavioral phenomena-including the attraction and compromise effects-that lie beyond the scope of any random utility model. I use data from frog mating choices to illustrate how the model can outperform the random utility framework in goodness of fit and out-of-sample prediction.
Keyword:
STOCHASTIC CHOICE
RATIONAL INATTENTION
DECISION-MAKING
ATTRACTION
VIOLATIONS
SIMILARITY
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
6.3
论文数:
2.6K
被引数:
3.2W
机构
引用论文
DECISION FIELD-THEORY - A DYNAMIC COGNITIVE APPROACH TO DECISION-MAKING IN AN UNCERTAIN ENVIRONMENT.png)
PSYCHOLOGICAL REVIEW.png)
PSYCHOLOGICAL REVIEWIF5.8
PREAI
.png){kind=icon}
分享.png){kind=icon}
收藏
分享收藏
查看更多内容