The Fake News Effect: Experimentally Identifying Motivated Reasoning Using Trust in News
设计实验，区分动机推理与贝叶斯更新，发现人们会因政治偏好扭曲对信息来源可信度的判断，从而解释信念偏差、极化与过度自信。
Motivated reasoning posits that people distort how they process information in the direction of beliefs they find attractive. This paper creates a novel experimental design to identify motivated reasoning from Bayesian updating when people have preconceived beliefs. It analyzes how subjects assess the veracity of information sources that tell them the median of their belief distribution is too high or too low. Bayesians infer nothing about the source veracity, but motivated beliefs are evoked. Evidence supports politically motivated reasoning about immigration, income mobility, crime, racial discrimination, gender, climate change, and gun laws. Motivated reasoning helps explain belief biases, polarization, and overconfidence.