Aparajita Dasgupta

IEA – Could you walk us through the key moments that shaped your path — from your earliest exposure to economic thinking, to what sparked your interest in the field, and ultimately what drew you to academic research?

Aparajita – Although I studied science in higher secondary school, I knew I wanted to pursue something different. I considered economics, English, and biology before choosing economics for my undergraduate degree. I was fortunate to have teachers who were deeply passionate about their subjects and instilled in me a love for economics.

After my master’s, I briefly worked in the corporate world before exploring a different path. My MPhil in Development Studies exposed me to diverse perspectives from economics, history, and political science, and it was here that I discovered the joy of academic research.

My PhD training imparted rigour to the research process, while regular departmental seminars with leading economists from around the world exposed me to a wide range of fascinating questions and ways of thinking. Fieldwork also shaped my perspective. I was fascinated by how the same programme was perceived differently across households—for instance, how drought-affected families in rural Andhra Pradesh, India valued access to work, while landowners were concerned about the availability of agricultural labour. I also became interested in how social norms and reporting behaviour shape the data we observe.

What I find particularly rewarding is developing hypotheses from economic intuition, testing them using large-scale microdata, and uncovering patterns in complex individual decision-making. The availability of rich, publicly accessible data has been instrumental in this journey.

IEA – In rural India, why might positive rainfall shocks in early life lead to worse schooling outcomes, such as dropping out or falling behind in grade, in areas where women and children have high labour force participation (non-loamy soil areas), and why are these effects weaker in loamy areas?

Aparajita – A positive rainfall shock in rural India can raise agricultural incomes, but it can also increase the demand for household labour. In our paper (Dasgupta and Karandikar, 2026), we find that adverse schooling effects are particularly pronounced for girls in non-loamy areas, where agricultural production is more labour-intensive and rainfall-induced increases in labour demand are stronger.

Younger children  are more likely to be drawn into farm work, creating a sharper trade-off between schooling and work. In these settings, the opportunity cost of schooling appears to dominate the income effect of improved rainfall. These effects are weaker in loamy areas, where agricultural production is less responsive to rainfall through labour demand.

Interestingly, negative rainfall shocks, such as droughts, can generate learning gains for children especially girls in non-loamy areas, as lower agricultural labour demand reduces the opportunity cost of attending school. This highlights how girls’ schooling is particularly vulnerable to climate shocks in contexts where household labour allocation is shaped by gender norms. The broader insight is that understanding the effects of climate shocks on human capital requires us to look beyond the shocks themselves and examine the underlying institutions and constraints that shape individual decision-making.

IEA – Economists often assume that historically disadvantaged castes in India have more egalitarian gender norms, yet your study finds that Scheduled Castes and Other Backward Classes are no less conservative than other groups. Why might this assumption have persisted, and how does household economic status, such as land versus asset ownership, change the relationship between caste and gender norms?

Aparajita – The assumption that historically disadvantaged castes have more egalitarian gender norms often stems from observing higher female labour force participation. But labour market outcomes reflect both preferences and economic constraints, making it difficult to infer gender attitudes from behaviour alone.

In our paper (Dasgupta and Datta, 2026), we use vignette-based survey data to directly examine gender preferences across caste groups. We find that Scheduled Castes and Other Backward Classes are not systematically less conservative than the General category. Importantly, the relationship between caste and gender attitudes varies with household economic status and the type of wealth.

For SC women, greater asset ownership is associated with less conservative attitudes, but this relationship reverses when wealth is measured by land. Among General-category households, greater land ownership is associated with less conservative attitudes among both men and women, a gradient that is weaker among SC households.

These findings suggest that caste and economic position jointly shape gender norms, and that we need to move beyond treating caste identity as a sufficient predictor of gender attitudes.