There is increasing evidence of the importance of tailoring development interventions to the local context. We implement an RCT in the Democratic Republic of the Congo, where there is variation in the presence of age sets, a mode of social organization that creates cohesive groups of young men who provide a check on the power of the older political elite. We provide villages chiefs with cash to purchase health products and form oversight committees. Some villages are randomly assigned to form a diverse committee and other villages are randomly assigned to form a young male committee.

Do liberal societies cultivate and sustain the social norms and other preferences required to perpetuate their basic institutions in the long run? To explore the dynamic stability of liberalism as a culture-institutions coevolutionary process, we measure the value of personal autonomy and aversion to being controlled by others, among East Germans raised under Communist rule and East Germans raised in liberal Germany.

This paper investigates the effect of rising anti-immigrant sentiment in European democratic host countries on support for democracy in African migrants’ origin communities. We propose a novel methodology to estimate migration stocks from sub-national areas of origin to any possible country in the world based on Google trends data. We use these data alongside measures of anti-immigrant sentiment at destination to study origin communities exposure to anti-immigrant sentiment.

This study investigates the short-, medium-, and long-term impacts of state censorship on knowledge production, focusing on the largest book banning in Chinese history, triggered by the creation of the Siku Quanshu (Complete Library in Four Sections) during 1772–1783. By analyzing publication data of over 161,000 books spanning from the 1660s to the 1940s, we find that categories subjected to more severe bans experienced a significant decline in publications in the decades following the bans (1780s to 1840s).

The talk is about the research within SWECOV, a large research pogram on the COVID-19 pandemic. The program is built on a rich set of medical, social and economic microdata from Sweden and was started when I served on the Swedish Corona Commission. In the seminar, I will give three examples of concrete projects. The first escribes the inequaltites, along different social gradients, in the medical, social and economic outfalls of the pandemic.

In the late 1930s, a team of writers traveled the United States to record the life stories of thousands of older Americans for posterity. We combine close human readings with text analysis by large-language models (LLMs) to turn these unstructured texts into a rich data set that captures the narrators' experiences, economic fortunes, and perspectives on what brought happiness, satisfaction, and meaning into their lives. We first demonstrate that, under the right circumstances, LLMs can detect and analyse factual information in this corpus in a comparable way to human readers.