Partisan Bias in Non-political Information Processing

52 Pages Posted: 6 Dec 2021 Last revised: 2 May 2022

See all articles by Yunhao Zhang

Yunhao Zhang

Massachusetts Institute of Technology (MIT) - Sloan School of Management

David G. Rand

Massachusetts Institute of Technology (MIT)

Date Written: November 30, 2021

Abstract

Political divisions have become a central feature of modern life. Here, we ask whether these divisions affect decisions outside the context of politics. In an incentivized task assessing the accuracy of non-political news headlines, we find partisan bias in advice-taking: Democratic participants are less swayed by (accurate) information that comes from Republicans compared to the same information from Democrats (Republican participants display no such bias). We then adjudicate between two possible mechanisms for this biased advice-taking: a preference-based account, where participants are motivated to take less advice from counter-partisans because doing so is unpleasant; versus a belief-based account, where participants sincerely believe co-partisans are more competent at the task (even though this belief is incorrect). To do so, we examine the impact of a 1000-fold increase in the stakes, which should increase accuracy motivations (and thereby reduce the relative impact of partisan motivations). We find that increasing the stakes does not reduce biased advice-taking, hence no evidence to support the bias is driven by preference. Consistent with the belief-based account, we find that Democratic participants (incorrectly) believe their co-partisans are better at the task, and this incorrect belief is much less severe among Republican participants. Further supporting the notion that the stated beliefs are sincere, raising the stakes of the belief elicitation of relative partisan competence does not affect the stated beliefs. Finally, participants – instead of ignoring the feedback – update in favor of their counter-partisans given feedback that suggests counter-partisans are competent. The implication of our study is that political divisions perhaps are not driven by a preference-based distaste of counter-partisans but by people having incorrect beliefs about counter-partisans’ competence (e.g., due to a lack of access to news that sustains a positive image of counter-partisans).

Keywords: Partisan Bias, Political Motivated Reasoning, Information Friction, Experimental Economics

Suggested Citation

Zhang, Yunhao and Rand, David G., Partisan Bias in Non-political Information Processing (November 30, 2021). Available at SSRN: https://ssrn.com/abstract=3974777 or http://dx.doi.org/10.2139/ssrn.3974777

Yunhao Zhang (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

HOME PAGE: http://https://mitsloan.mit.edu/phd/students/yunhao-zhang

David G. Rand

Massachusetts Institute of Technology (MIT) ( email )

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

HOME PAGE: http://www.daverand.org

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