Technology adoption is at the forefront of my research, and I am interested in how it influences the economy and society, particularly the most marginalised groups.  In my PhD research, I integrate computational and quantitative economic methods to study the impact of technology diffusion and use on gender inequality and violence against women and girls in India. Currently, I work as a researcher and lecturer at the United Nations University where I serve as an academic lead and coordinator for education and capacity development programmes. I have contributed to research and training projects commissioned and funded by UNICEF, UNESCO, ITU, and the European Commission. 

Here is a glimpse into my job market paper, which concerns one of the most pervasive forms of discrimination against girls - son preference:

We examine whether and how social media could challenge son preference for women by studying the effect of exposure to Twitter. However, since Twitter adoption is unlikely to occur randomly and may be correlated with unobservables, we employ an instrumental variables approach. Twitter usage surged when India's 'god of cricket', Sachin Tendulkar, retired. A hashtag campaign surrounding his retirement led to an influx of Tweets, and so we instrument Twitter use with interest in the cricketer at the height of the campaign using Google Trends data. We learn that social media can positively influence gender norms and lead to a reduction in son preference. We also find that preferences don't shift from sons to daughters, but rather women are less likely to discriminate on the basis of the sex of the child. We also examine this effect for men, and find similar results. While relevant, these findings prompt us to question how and why. Thus, we run a few additional analyses and find that Twitter can introduce women to content outside of their typical world-view, which could help explain the observed changes in preferences and social norms: 

1. By fine-tuning a cross-lingual sequence classifier and applying a qualitative approach, we find that conversations about children on Indian Twitter are progressive or neutral, but rarely regressive. 

2. By observing the effect of a popular campaign against son preference, #SelfieWithDaughter, which was endorsed by Prime Minister Narendra Modi, we learn that the effect of Twitter is amplified for campaign affected districts, with both short and long run effects. 

3. Son preference shapes not only fertility choices, but also has tangible and deleterious effects on girls' nutrition, health, education, and capabilities. By examining the effect of exposure to Twitter and nutritional outcomes for girls under the age of five, we find that some behavioural outcomes related to health are favourably influenced by social media exposure.  

If you are interested in reading the full JMP, the working paper is available here. 

You can reach me on my e-mail; visit my personal page here.