Broadcasting Change: India’s Community Radio Policy and Women’s Empowerment
ESEM Award 2024 - best applied paper by a young researcher (<10 years post-PhD) at The Econometric Society’s European Meeting
Job Market Paper
In poor countries, the interaction of early marriage, early motherhood, and low educational attainment disempowers women and limits their life opportunities. Even as countries grow richer, gender inequality is often sustained by social norms, thereby limiting welfare gains from women’s empowerment. I investigate the use of media as a cheap and scalable policy to empower women. In 2006, India enacted a community radio policy that grants radio licenses to NGOs and educational institutions with the aim to foster local development. I collect original data on the content and coverage areas of all 250+ radio stations. I uncover women’s empowerment as a key theme through topic modeling and GPT-based analyses of radio show recordings. For identification, I exploit topography-driven variation in radio access and develop a novel econometric approach to deal with randomly displaced geolocated household data. The results show that women exposed to radio gain an additional 0.3 years of education and are 4.1pp (11%) more likely to obtain a secondary degree. In line with increased education, exposure reduces child marriages by 1.4pp (22%) and fertility of young women by around 10% while they are 11pp more likely to exhibit autonomy in household decisions. The findings demonstrate that community media can effectively address gender inequality.
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Yulia Evsyukova and
Wladislaw Mill
Accepted at The Quarterly Journal of Economics
We assess the impact of discrimination on Black individuals’ job networks across the U.S. using a two-stage field experiment with 400+ fictitious LinkedIn profiles. In the first stage, we vary race via A.I.-generated images only and find that Black profiles’ connection requests are 13 percent less likely to be accepted. Based on users’ CVs, we find widespread discrimination across social groups. In the second stage, we exogenously endow Black and White profiles with the same networks and ask connected users for career advice. We find no evidence of direct discrimination in information provision. However, when taking into account differences in the composition and size of networks, Black profiles receive substantially fewer replies. Our findings suggest that gatekeeping is a key driver of Black-White disparities.
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