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How do levels of vagueness in news influence population movement: evidence from Japan’s COVID-19 cluster news

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  • Zihan Xu

Abstract

We examine how different levels of vagueness in COVID-19-related online news affected population movement, where the level of vagueness is defined by the presence or absence of specific information regarding the locations of COVID-19 clusters. Leveraging population data at the 500-metre-mesh level and data on the COVID-19 cluster news in Japan, we conduct a difference-in-differences approach. We find that news with specific location information resulted in a significant percentage reduction in population, particularly within 1 km range of the cluster, with news of clusters occurring in schools leading to the largest population reduction. In contrast, news without specific location information exhibited no statistically significant impact on population movement. These findings suggest that news with lower level of vagueness may contribute to preventing the spread of infectious diseases by reducing population movement, but this reduction may also have a significant impact on normal economic activities. Consequently, the communication strategies in online media are particularly crucial for balancing the need for disease prevention with the preservation of economy activity, especially in the context of pandemics like COVID-19.

Suggested Citation

  • Zihan Xu, 2026. "How do levels of vagueness in news influence population movement: evidence from Japan’s COVID-19 cluster news," Applied Economics, Taylor & Francis Journals, vol. 58(35), pages 7381-7401, July.
    • Handle: RePEc:taf:applec:v:58:y:2026:i:35:p:7381-7401
    DOI: 10.1080/00036846.2025.2532882
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