Violent and nonviolent protests during Civil Rights Era

More evidence of nonviolent protest superiority. Creative research on resistance method and effect on US Congressional policy support:

Are peaceful or violent protests more effective at achieving policy change? I study the effect of protests during the Civil Rights Era on legislator votes in the US House. Using a fixed-effects specification, my identifying variation is changes within the congressional district over time. I find that peaceful protests made legislators vote more liberally, consistent with the goals of the Civil Rights Movement. By contrast, violent protests backfired and made legislators vote more conservatively. The effect of peaceful protests was limited to civil rights-related votes. The effect of violent protests extended to welfare-related votes. I explore alternative explanations for these results and show that the results are robust to them. Congressional districts where incumbents were replaced responded more strongly. Furthermore, congressional districts with a larger population share of whites responded more strongly. This is consistent with a signaling model of protests where protests transmitted new information to white voters but not to black voters.

That is the abstract of the job market paper of Gábor Nyéki from Duke.

Repost from the always great Marginal Revolution

The trust problem of cryptocurrency

intriguing story and helpful explainer:

…after much deliberation and hand-wringing, in the aftermath of a multimillion-dollar swindle from his automated, algorithm-driven, supposedly foolproof corporation, Vitalik Buterin, then 22 years old, announced the ‘hard fork’ of the cryptocurrency Ethereum. By making that announcement, Buterin shattered certain tightly held assumptions about the future of trust and the nature of many vital institutions that make modern life possible. He also really pissed off a lot of people.

Influencers are overrated

A team at Stanford finds reasons to question the effectiveness of targeting influencers to spread info.

While tackling this question, a team of Stanford researchers found a remarkable result: Simply seeding a few more people at random avoids the challenge of mapping a network’s contours and can spread information in a way that is essentially indistinguishable from cases involving careful analysis; seeding seven people randomly may result in roughly the same reach as seeding five people optimally. (The results are available in their online working paper, “Just a Few Seeds More: Value of Network Information for Diffusion.”) finds reason to question influencer effectiveness at spreading information…