.png){kind=icon}
返回
Bayesian Networks and Boundedly Rational Expectations*
.png){kind=icon}
OA
AI
DOI：10.1093/qje/qjw011.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
I present a framework for analyzing decision making under imperfect understanding of correlation structures and causal relations. A decision maker (DM) faces an objective long-run probability distribution p over several variables (including the action taken by previous DMs). The DM is characterized by a subjective causal model, represented by a directed acyclic graph over the set of variable labels. The DM attempts to fit this model to p, resulting in a subjective belief that distorts p by factorizing it according to the graph via the standard Bayesian network formula. As a result of this belief distortion, the DM's evaluation of actions can vary with their long-run frequencies. Accordingly, I define a personal equilibrium notion of individual behavior. The framework enables simple graphical representations of causal-attribution errors (such as coarseness or reverse causation), and provides tools for checking rationality properties of the DM's behavior. I demonstrate the framework's scope of applications with examples covering diverse areas, from demand for education to public policy. JEL Code: D03.
Keyword:
MODEL
EQUILIBRIUM
INFORMATION
GAMES
期刊
IF:
12.7
论文数:
1.2K
被引数:
4.1W
机构
引用论文
An Approach to Asset Pricing Under Incomplete and Diverse Perceptions一种不完整和多样化感知下的资产定价方法.png)
ECONOMETRICA
ECONOMETRICAIF7.1
PREAI
分享收藏Efficacy of felbamate monotherapy in patients undergoing presurgical evaluation of partial seizures
OAAI
OAAI分享收藏
查看更多内容