S9 Ep20: What triggered January 6?

Two explanations circulated immediately after the March to Save America on January 6, 2021 turned into a riot: a mob manipulated by a demagogue, or ordinary citizens defending democracy against a stolen election. Konstantin Sonin, David Van Dijcke, and Austin Wright have used anonymised location data from forty million mobile devices to investigate why the protests escalated so dramatically.

No surprise: partisanship was the strongest predictor of attendance, proximity to Proud Boys chapters and use of the far-right social network Parler also increased participation. But political isolation amplified the movement: the communities most over-represented among those who traveled to Washington were small Republican enclaves surrounded by Democrat-leaning areas, politically and socially cut off from their neighbours. And participation also spiked in counties that experienced a "midnight swing," where the reported vote count favoured Trump on election night before shifting to Biden as mail-in ballots were counted. These were precisely the counties where the "Stop the Steal" narrative landed hardest. 

The research behind this episode:

Sonin, Konstantin, David Van Dijcke, and Austin L. Wright. 2023. "Isolation and Insurrection: How Partisanship and Political Geography Fueled January 6, 2021." CEPR DP18209. 

To cite this episode:

Phillips, Tim, and Konstantin Sonin. 2026. “What triggered January 6?” VoxTalks Economics (podcast). 

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About the guest

Konstantin Sonin is the John Dewey Distinguished Service Professor at the Harris School of Public Policy at the University of Chicago. Born in the Soviet Union, he has spent his career studying how political institutions work under stress, with particular attention to how information and misinformation shape political behaviour, elections, and collective action. He is one of the leading economists working on the political economy of authoritarian and democratic governance, and his research on protest, polarisation, and political geography has made him a central figure in the study of democratic backsliding.

Research cited in this episode

Regression discontinuity design is a statistical method used to identify causal effects by exploiting a threshold or cutoff. Sonin, Van Dijcke, and Wright use two regression discontinuity designs: one exploiting the narrow margins by which Trump lost certain states, and one exploiting the gap between the election-night vote tally and the final certified result in individual counties. In both cases, the design allows them to isolate the effect of a specific trigger on protest participation, separating it from the general background of partisan feeling.

The "midnight swing" refers to the shift in reported vote tallies that occurred in many counties on election night 2020 as large batches of mail-in ballots were counted. Because mail-in voters skewed heavily Democratic, counties where in-person votes were reported first showed strong Trump leads that reversed overnight as the mail-in totals arrived. For professional observers and election administrators, this pattern was entirely expected; it followed directly from the different rules different states used to count mail-in ballots during the pandemic. For many voters, particularly those already primed to distrust the electoral process, it read as suspicious. The paper finds that communities exposed to larger swings sent disproportionately more participants to Washington on January 6.

Network Exposure design is a methodological innovation introduced in this paper. It measures how much exposure a given community had to election-denial signals flowing through its social networks, and distinguishes this from exposure arising simply through geographic proximity to other communities. Isolated communities proved hypersensitive to information traveling through their social networks, but not to information spreading through neighbouring areas. This suggests the amplification mechanism was social, not spatial.

Political isolation in this paper refers to being a minority political community within a larger, differently-leaning area. A small Republican-voting enclave inside a Democrat-leaning county or district is politically isolated in this sense. The paper finds that isolation of this kind was a strong amplifier of partisanship in predicting participation. Two other measures of isolation, one based on mobile device travel patterns ("locational isolation") and one based on Facebook connections ("social media isolation"), produce consistent results, suggesting the effect is not an artefact of how isolation is measured.

The Proud Boys are a far-right extremist organisation active in the United States. The paper finds that communities with a local Proud Boys chapter were over-represented among those who traveled to Washington on January 6, making proximity to the organisation a robust correlate of participation, independent of general partisan leanings.

Parler was a social media platform popular among far-right users in the United States during the period leading up to January 6, 2021. Communities where Parler usage was relatively higher were also over-represented among participants in the March to Save America, suggesting that the platform played a role in amplifying mobilisation signals within the networks most susceptible to them.

Collective action theory is the study of how individuals decide to participate in group action, particularly when the costs fall on participants individually but the benefits are shared. Sonin, Van Dijcke, and Wright contribute behavioural evidence on the specific role of political isolation and network-amplified grievance in driving participation.

More VoxTalks Economics

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How protests are born, and how they die Every year we see thousands of protest movements on our city streets. Benoît Schmutz-Bloch explains why do some protests persist, and some disappear, and some remain peaceful, but others become violent.