Research

Is deplatforming effective in reducing toxicity on social media? To answer this question we study a policy change on Reddit in June 2020 which led to a simultaneous ban of thousands of forums containing hateful content, but not the users of these forums. We use data on the near universe of comments left on Reddit to examine the impact of the ban on user behaviour in a differences-in-differences design. We find that the most active users of banned subreddits comment more after the policy change and substitute to new forums in the weeks after the ban. The increase in activity persists in the long run, but is not associated with higher toxicity: instead, the comments left by affected users outside banned subreddits contain 20% fewer instances of hate speech. We do not find evidence that the policy leads to lower quality of engagement, negative spillover effects or recreation of banned subreddits elsewhere on the platform. Overall, the results suggest that moderation targeting toxic digital spaces can be effective in combating hate speech without lowering user engagement, and thus can be aligned with platforms' incentives.

Ubiquitous culturally shaped spatial institutions may pose a barrier to climate action at a large cost to the global commons. Studying data on the full English housing stock, we document that conservation areas - designations created to preserve the aesthetic character of a neighbourhood not uncommon across the globe - may be responsible for 3 to 4 million tonnes of avoidable CO2 emissions annually. Using a suite of microeconometric methods, we show that properties in conservation areas are less energy efficient, exhibit lower level of retrofit investment, and consume notably more energy. The effects can be directly attributed to increased retrofit costs. The added planning restrictions, by increasing the administrative burden and associated costs and slowing down local planning processes, have further negative spillover effects on spatial development outside conservation areas.

Hello.

Economics pays increasing attention to narratives as a source of data on beliefs and social processes, but our ability to analyse them is limited due to methodological constraints and high dimensionality of the data. In this work, I propose a methodology for the analysis of cultural text which uses character as a unit of observation. In an application to a newly constructed corpus of Indian folktales, I illustrate how looking at descriptions and behaviours of characters can facilitate the comparison of folklore to contemporaneous ethnographic data, as well as potentially improve our understanding of gender norms and stereotypes.