This paper examines the dynamic implications of social networks for the labour market outcomes of refugees resettled in the U.S. A theoretical model of job information transmission shows that the relationship between social network size and labour market outcomes is heterogeneous and depends on the vintage of network members: an increase in network size can negatively impact some cohorts in a network while benefiting others. To test this prediction, I use new data on political refugees resettled in the U.S. and exploit the fact that these refugees are distributed across cities by a resettlement agency, precluding individuals from sorting. The results indicate that an increase in the number of social network members resettled in the same year or one year prior to a new arrival leads to a deterioration of outcomes, while a greater number of tenured network members improves the probability of employment and raises the hourly wage.

We use a field experiment to show that referral-based hiring has the potential to disadvantage qualified women, highlighting another potential channel behind gender disparities in the labor market. Through a recruitment drive for a firm in Malawi, we look at men’s and women’s referral choices under different incentives and constraints. We find that men systematically refer few women, despite being able to refer qualified women when explicitly asked for female candidates. Performance pay also did not alter men’s tendencies to refer men. In addition, women did not refer enough high-quality women to offset men’s behavior.

We exploit random assignment of gender quotas for leadership positions on Indian village councils to show that prior exposure to a female leader is associated with electoral gains for women. After ten years of quotas, women are more likely to stand for, and win, elected positions in councils required to have a female chief councilor in the previous two elections. We provide experimental and survey evidence on one channel of influence—changes in voter attitudes. Prior exposure to a female chief councilor improves perceptions of female leader effectiveness and weakens stereotypes about gender roles in the public and domestic spheres.

Can targeting information to network-central farmers induce more adoption of a new agricultural technology? By combining social network data and a field experiment in 200 villages in Malawi, we find that targeting central farmers is important to spur the diffusion process. We also provide evidence of one explanation for why centrality matters: a diffusion process governed by complex contagion. Our results are consistent with a model in which many farmers need to learn from multiple people before they adopt themselves. This means that without proper targeting of information, the diffusion process can stall and technology adoption remains perpetually low.

We conducted an experiment providing fertilizer grants to female rice farmers in Mali. We found that women who received fertilizer used both more fertilizer and more complementary inputs such as herbicides and hired labor. This shows that farmers respond to an increase in one input by re-optimizing other inputs. Second, while the increase in inputs led to a considerable increase in output, we found no evidence that profits increased. Our results suggest that fertilizer's impact on profits is small compared to other sources of variation. This may make it difficult for farmers to learn about the returns to fertilizer.