Abstract
I consider a situation in which citizens consult a report by the media to learn the state of the world. Besides the true state of the world, the report can contain two types of inaccuracies: persistent bias following from the media's ideology and random noise. Employing a theoretical model, I show that citizens perform additional investigations if there is much variance in noise. In contrast, citizens are not affected by persistent bias as they can anticipate it. These predictions are confirmed through an empirical analysis of the start of the COVID-19 outbreak, in which I utilize sentiment data to differentiate persistent bias from noise in media reports. The results suggest that media quality is more of a concern than media neutrality.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
