Job Market Paper

Legal Segregation and Urban Inequality: Evidence and Theory from India’s Disturbed Areas Act

This paper leverages a unique legal context, the Disturbed Areas Act (DAA) in Gujarat, India, which imposes de jure restrictions on inter-religious property sales, to identify the effects of legal segregation on urban inequality. I constructed a novel, hand-collected dataset of all DAA notifications and enforcement boundaries by digitizing historical gazette records and electoral rolls, and complemented this with fieldwork in segregated neighborhoods. Using this newly assembled data, I estimate the causal effects of state-mandated segregation on neighborhood-level demographic change, housing market distortions, and access to education and public goods. The analysis combines event study designs with spatial difference-in-differences and reveals sharp reductions in religious integration, educational infrastructure, and price appreciation in DAA-imposed zones, relative to comparable neighborhoods.

Other Works in Progress

Endogenous Segregation and Intergenerational Mobility in India: Evidence from a Calibrated OLG Model

This paper builds a spatial overlapping generations (OLG) model of India’s dual economy, where high-productivity, well-serviced neighborhoods coexist with low-productivity, under-resourced areas, to examine how endogenous residential segregation shapes intergenerational mobility, education, and inequality. Households sort across neighborhoods based on caste, income, and amenities, and I calibrate the model using India Human Development Survey (IHDS) microdata from 2005 and 2012 on schooling, income, and public goods access. Simulations show that segregation-driven disparities can entrench inequality even when school access is equalized. This work offers a nationally scoped, macro-structural perspective on spatial inequality.

The Relationship between School Segregation and School Outcomes: Evidence from India (with Moumita Das, Gagandeep Sachdeva, and Kartik Srivastava)

We combine nationwide school census data (UDISE, 2005–2017) with village-level demographic composition from the Indian Census data to construct high-resolution measures of both residential and school-level caste segregation. Using school fixed effects and village-year controls, we document sharp nonlinear relationships between school outcomes such as infrastructure quality, teacher qualifications, and learning outcomes and SC concentration of a school relative to the village.

The Impact of the US-China Trade War on Indian Firms (with Pulak Ghosh,  Aakash Kalyani, and Manpreet Singh)

This project studies how Indian firms responded to the US-China trade war by exploiting firm-level panel data on exports, imports, and investments from the CMIE Prowess database. We construct industry-year level measures of exposure to US tariffs on Chinese products and estimate the differential investment response among Indian firms across trade categories. Using firm, year, and industry fixed effects in panel regressions, we find evidence that Indian exporters to the US, particularly those not heavily reliant on Chinese inputs, increased investment significantly post-tariffs, consistent with a substitution effect in global value chains. This investment response was heterogeneous by firm size and age, with younger and more productive firms driving the gains.