Up in Smoke: Educational Toll of Air Pollution
Abstract: While the impact of air pollution on child health outcomes is widely documented, the literature on the relation between air pollution and educational outcomes for primary school children in developing countries remains sparse. In this paper, I estimate this relationship using data on over 45,000 primary schools in Punjab, Pakistan. To circumvent endogeneity concerns, I leverage the crop residue burning practice prevalent in Punjab, Pakistan, to construct an instrument for air pollution based on wind direction from crop fires in Punjab, Pakistan, and India. I find significant negative impacts on numeracy and English and Urdu language skills, with a 100 µg/m³ increase in PM2.5 and a reduction of 0.3 standard deviations in average Math, English, and Urdu skills. I find that student attendance and teacher attendance are important factors driving these results. Additionally, I find that girls are more adversely affected compared to boys.
The impact of co-education on girls’ enrollment (co-authored with Kate Vyborny)
Existing literature on the impact of education on schooling outcomes remains inconclusive. While some papers find that single-sex schooling leads to an improvement in girls' and boys' exam scores, others find null or adverse effects. This paper adds to this debate, being the first to estimate the impact of restrictive gender and cultural norms on a low-income setting. I propose to assess the impact of a school consolidation policy in Punjab, Pakistan, under which single-sex public schools were consolidated into coeducation. I merge three rounds of MICS survey data comprising over 270,000 households with an administrative public school survey at the village level. I use a difference-in-difference framework to assess whether this policy worsened enrollment for girls and boys, particularly in more conservative areas.
UnpackingHousing Affordability in Developing Countries: A Focus on Spatial Heterogeneity in Lahore, Pakistan (co-authored with Kwan Lee Ok and Syed M. Hasan)
Draft available upon request
Spatial heterogeneity in housing affordability is more pronounced in Lahore, Pakistan, than incities in developed countries. Using online listing data, neighborhood-level geospatial information, and a large-sample geotagged household survey, we find that spatial sorting is inefficient across Lahore’s neighborhoods. Older, central neighborhoods with a high share of lower-cost housing are often occupied by middle- to higher-income residents. At the same time, many lower-income households reside in newer, suburban neighborhoods with higher housing costs. Low-income, younger homeowners, in particular, tend tosort into higher-cost neighborhoods compared to older households with similar incomes. Our regression analysis shows that neighborhood housing quality is a stronger predictor of unaffordability than amenities, especially for lower-income and younger households. In other words, either voluntarily opting or being forced to choose neighborhoods with higher-quality housing leads to greater affordability challenges for these groups. Therefore, efficient within-neighborhood sorting—where lower-income households can access affordable housing—is vital for affordability inLahore. However, such access is expected to be limited for younger, first-time homebuyerscompared to older homeowners with longer-term residency. Our study highlights that a single measure of housing affordability can obscure distributional challenges in developingcountries, where spatial sorting is less efficient.