When Guidance Changes: Government Inconsistency and Public Beliefs

56 Pages Posted: 29 May 2020 Last revised: 9 Jul 2020

See all articles by Charlie Rafkin

Charlie Rafkin

Massachusetts Institute of Technology (MIT)

Advik Shreekumar

Massachusetts Institute of Technology (MIT)

Pierre-Luc Vautrey

Massachusetts Institute of Technology (MIT)

Date Written: July 7, 2020

Abstract

Governments often provide inconsistent guidance to the public. Does inconsistency affect how much people believe the latest recommendations? Using an incentivized online experiment with 1,900 US respondents in early April 2020, we present all participants with the latest official projection about coronavirus death counts. We randomize exposure to information that highlights the government’s inconsistency about the coronavirus threat. When inconsistency is salient, participants have reduced propensity to revise prior beliefs about death counts and lower self-reported 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.

Keywords: signaling, Bayesian updating, coronavirus

JEL Classification: D78, D83, D91, H12, I18

Suggested Citation

Rafkin, Charlie and Shreekumar, Advik and Vautrey, Pierre-Luc, When Guidance Changes: Government Inconsistency and Public Beliefs (July 7, 2020). Available at SSRN: https://ssrn.com/abstract=3613446 or http://dx.doi.org/10.2139/ssrn.3613446

Charlie Rafkin (Contact Author)

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Advik Shreekumar

Massachusetts Institute of Technology (MIT) ( email )

50 Memorial Drive
Cambridge, MA MA 02142
United States

Pierre-Luc Vautrey

Massachusetts Institute of Technology (MIT) ( email )

Cambridge, MA
United States

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