Journal of Public Economics · 2021 · Charlie Rafkin、Advik Shreekumar、Pierre-Luc Vautrey
中文摘要
政府常常就仍具不确定性的问题提出早期建议。政府的早期立场是否会影响人们对最新建议的信任程度?我们利用2020年4月初一项针对1900名美国受访者的激励性在线实验来考察这一问题。我们向所有参与者展示了CDC关于冠状病毒死亡人数的最新预测,并随机让参与者接触突出特朗普总统此前如何淡化冠状病毒威胁的信息。当总统的前后不一致变得显著时,参与者更不可能根据该预测修正其关于死亡人数的先验信念;他们对政府的信任也更低。这些结果与一个关于从政府信息传递中提取信号的简单模型相一致,并对在其他情境下设计不断变更的指导意见具有启示意义。
Abstract
Governments often make early recommendations about issues that remain uncertain. Do governments’ early positions affect how much people believe the latest recommendations? We investigate this question using an incentivized online experiment with 1900 US respondents in early April 2020. We present all participants with the latest CDC projection about coronavirus death counts. We randomize exposure to information that highlights how President Trump previously downplayed the coronavirus threat. When the President’s inconsistency is salient, participants are less likely to revise their prior beliefs about death counts from the projection. They also report lower trust in the government. These results align with a simple model of signal extraction from government communication, and have implications for the design of changing guidelines in other settings.