COVID-19 Data: The Logarithmic Scale Misinforms the Public and Affects Policy Preferences

19 Pages Posted: 29 Apr 2020 Last revised: 11 May 2020

See all articles by Alessandro Romano

Alessandro Romano

Yale Law School

Chiara Sotis

London School of Economics & Political Science (LSE)

Goran Dominioni

Yale Law School

Sebastian Guidi

Yale Law School

Date Written: April 29, 2020

Abstract


Mass media routinely present data on COVID-19 diffusion using either a log scale or a linear scale. We show that the scale adopted on these graphs has important consequences on how people understand and react to the information conveyed. In particular, we find that when we show the number of COVID-19 related deaths on a logarithmic scale, people have a less accurate understanding of how the pandemic has developed, make less accurate predictions on its evolution, and have different policy preferences than when they are exposed to a linear scale. Consequently, merely changing the scale the data is presented on can alter public policy preferences and the level of worry, despite the fact that people are exposed to a lot of COVID-19 related information. Reducing misinformation can help improving the response to COVID-19, thus, mass media and policymakers should always describe the evolution of the pandemic using a graph on a linear scale, or at least they should show both scales. More generally, our results confirm that policymakers should not only care about what information to communicate, but also about how to do it, as even small differences in data framing can have a significant impact.

Keywords: COVID-19, Public Understanding, Framing, Media

JEL Classification: D90, D91, I10, I12, I18

Suggested Citation

Romano, Alessandro and Sotis, Chiara and Dominioni, Goran and Guidi, Sebastian, COVID-19 Data: The Logarithmic Scale Misinforms the Public and Affects Policy Preferences (April 29, 2020). Available at SSRN: https://ssrn.com/abstract=3588511

Alessandro Romano (Contact Author)

Yale Law School ( email )

New Haven, CT
United States

Chiara Sotis

London School of Economics & Political Science (LSE) ( email )

Houghton Street
London, WC2A 2AE
United Kingdom

Goran Dominioni

Yale Law School ( email )

127 Wall Street
New Haven, CT 06511
United States

Sebastian Guidi

Yale Law School ( email )

127 Wall Street
New Haven, CT 06510
United States

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