Discrimination on #EconTwitter

This paper documents discrimination in the formation of professional networks among academic economists. We created 80 bot accounts that claim to be PhD students differing in three characteristics: gender (male or female), race (Black or White), and university affiliation (top- or lower-ranked). The bots randomly followed 6,920 users in the #EconTwitter community. Follow-back rates were 12 percent higher for White students compared to Black students, 21 percent higher for students from top-ranked universities compared to those from lower-ranked institutions, and 25 percent higher for female compared to male students. Notably, the racial gap persists even among students from top-ranked institutions.

That is from a new AERInsights paper by Nicolás Ajzenman, Bruno Ferman, and Pedro C. Sant’Anna.  Here is a useful picture from the paper.  Being at a top school, or at least pretending to be, is what really matters?