Alternatives to Bayesian Updating

被引：0
|
作者：
Ortoleva, Pietro [1 ,2 ]
机构：
[1] Princeton Univ, Dept Econ, Princeton, NJ 08544 USA
[2] Princeton Univ, Sch Publ & Int Affairs, Princeton, NJ 08544 USA
来源：
ANNUAL REVIEW OF ECONOMICS | 2024年 / 16卷
关键词：
Bayes' rule; non-Bayesian behavior; base-rate neglect; conservatism; cognitive noise; hypothesis testing; MODEL; INFORMATION; EXPECTATIONS; PROBABILITY; PSYCHOLOGY; STATISTICS; INFERENCE; JUDGMENT; PRICES; MEMORY;
D O I：
10.1146/annurev-economics-100223-050352
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
We discuss models of updating that depart from Bayes' rule even when it is well-defined. After reviewing Bayes' rule and its foundations, we beginour analysis with models of non-Bayesian behavior arising from a bias, apull toward suboptimal behavior due to a heuristic or a mistake. Next, weexplore deviations caused by individuals questioning the prior probabilitiesthey initially used. We then consider non-Bayesian behavior resulting fromthe optimal response to constraints on perception, cognition, or memory, aswell as models based on motivated beliefs or distance minimization. Finally,we briefly discuss models of updating after zero probability events.
引用
收藏
页码：545 / 570
页数：26
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