What are your research and engagement interests?
My research interests lie in applied microeconomics, econometrics, and development economics. A unifying theme is an interest in economic inequality and questions of what it is, how to measure it, why it exists, and how to address it. Recently I’ve become very interested in applications of machine learning (ML) algorithms to economic problems, “big data” and, relatedly, the differences between predictive and causal inference. Using ML to extract and scale economically meaningful signals from novel data sources (e.g. satellite data), is an exciting space, and there are a number of creative ML approaches that are generating new sources of data where reliable data on economic outcomes are missing, such as in tracking and targeting poverty in developing countries.
What has motivated your interests and journey? How do you hope to make difference?
We’ve all confronted inequality in some form. For me, just growing up in a “developing” country surrounded by displays of sometimes extremely contrasting ways of life was a sure-fire way to becoming rebellious. And actually, you see that this is a global challenge. Today, we see that within-country, income inequality is on the rise in Canada and many of its peer countries. This certainly has economic and political implications, but high inequality also raises moral questions regarding fairness and social justice. These are tough problems. I’m interested in ways I can contribute to academic research and evidence-based policymaking. For example, I’m part of the ‘Reach Project’ where student researchers undertake rigorous analyses of development intervention outcomes.
What’s the latest project you have been working on and would like to share with the SofC audiences?
As a Laidlaw Scholar, I spent the summer doing an independent research project wherein I studied sibling spillover effects in school achievement in Pakistan. This was a very cool opportunity, and I’d encouraged others to apply. It’s unconventional and forward-looking in that you get to do research with as much freedom as a PI. Sharing sole responsibility for the project and all facets of research meant I was really able to appreciate the interdependencies of theory, and data-driven modes of analysis. Recent expansions in empirical tools and strategies don’t displace a role for deductive reasoning. I was able to draw on insights in economic theory, specifically “human capital” literature, and investigate a known problem using novel data from an interesting cultural context.
As a student, researcher and or activist, what have you learned from the pandemic and its global impact?
This is perhaps an obvious point, but I think the pandemic and its outcomes really highlighted existing socioeconomic and health inequalities. This theme forms the bedrock of the ‘Cities Unmasked’ podcast produced by my colleagues and me from the Cities of Inequality, Urban Solidarities, and Community Activism group at SofC. Professor Kwame McKenzie, the CEO of the Wellesley Institute and a professor of psychiatry at the University of Toronto, further accentuates this point when he argues that the pandemic “discriminates” and that it has magnified existing issues in marginalized communities. In fact, limited city data shows that low-income and people of color make up a disproportionate percentage of COVID-19 cases in Toronto.
Please share with us your experiences at the SofC. How do you think being a member of the SofC Urban Leadership Fellowship and Academy Program has contributed to your scholarship and added to your experience as a student?
It has been a great opportunity for me to examine and think deeply about issues that form my academic interests in new and sometimes uncomfortable, but always interesting ways. I have had stimulating and fruitful conversations with excellent colleagues that shared parts of their diverse personal and intellectual histories through the ways they look at the world.