Sayahnika Basu

Resource booms are often associated with adverse distributional effects across economies. We exploit temporal and spatial variation generated by the copper boom in the 2000s to measure the effect of mineral resource extraction on human capital investment in Zambia. Combining data from repeated cross-sections of households and mines, we find that adolescent girls near mines have lower school attendance and higher engagement in paid work. We argue that the main pull factor is the increase in the demand for labor among sectors where women typically dominate. As more adult women marry and married women live in households that benefit from the wealth generated by spouses, adolescent girls fill the gap previously met by adult women in the labor market. Our findings suggest that resource booms induce inequitable distributional effects across generations of women. 

Household labor reallocation provides a potentially important channel for rural households to adapt to changing weather patterns. Exploiting the temporal and spatial variation of drought occurrence in India, I find that drought reduces the share of agriculture labor hours by 110 hours (3% at the mean). This reduction is driven by households that do not own land. Motivated by these facts, I develop a model of labor allocation across the agriculture and non-agriculture sectors to analyze how droughts may affect structural transformation. My results imply that projected increase in the spatial extent of droughts over the coming years will induce landowning households to allocate 2% more labor to agriculture and induce landless households to reduce their agricultural labor. The net effect is a 1% reduction in agricultural labor. While small in percentage terms, this implies that 2.5 million individuals would leave agriculture. I use the model to analyze how projected climate change would affect the cost to the government of achieving its stated target of increasing the manufacturing share of GDP to 25% by 2035. Under climate change, I find that the government would need to subsidize non-agriculture wages by a higher margin due to the presence of land market frictions.

Droughts are becoming increasingly common in India, where 50% of the labor force works in agriculture, and most agricultural production is rainfall dependent. This paper investigates the extent to which rural households adapt to drought by reallocating labor from agriculture to other sectors of the economy. I use household-level fixed effects regressions to estimate to find that household agricultural jobs decline in the year following a drought. Further, I find that these effects are mediated by job skills and land ownership. I find that households with working members who have completed primary education account for most of the workers who exit the agricultural sector. In contrast, I find that households that own land increase their agricultural labor share after experiencing a drought. Thus, while I find that drought causes households to diversify away from agriculture on aggregate, the extent of this structural change is mitigated by the behavior of landowners.

 We evaluate the environmental impact of Special Economic Zones (SEZs), a place-based policy designed to foster economic development in India. Specifically, we identify the unintended effects of the policy on firms' energy usage and carbon emissions. Leveraging extensive firm data and a spatial RD-DiD design, we find that SEZs lead to a significant 30\% reduction in firms' carbon emissions. This substantial decline in emissions is predominantly driven by larger firms and those located in regions with access to cleaner energy. Complementary analyses indicate a shift among firms within SEZs from conventional energy to lower-carbon renewable alternatives, potentially contributing to the overall reductions in carbon emissions. These findings underscore the interplay between economic development and environmental conservation. 

We study how the effects of “Superfund” hazardous waste sites’ listing and deletion during the 2000’s differed across race, income, and health among US seniors. Using a random 20% sample of the US Medicare population from 1999 through 2013 and a spatial difference–in–difference regression method, we find the probability to move out is 5-7% higher for seniors who live within 3.5km of a site in response to the designation of a Superfund site compared to seniors living within 3.5-7km. On average, seniors who move away from sites reduce their exposure to PM2.5 and move further from other sites, but the reductions in pollution are smaller for poorer, sicker, and non-white movers. In addition, we find that Black, Hispanic, and poorer people are 5-6% more likely to move within 3.5km of a site that is not yet proposed to be cleaned up compared to 3.5-7km of a site. We find nearly symmetric results upon the completion of cleanup of a Superfund site. These findings add to the environmental justice literature by providing new evidence on pollution- exposure and sorting for the Medicare population who are defined by the EPA as a vulnerable group to pollution based on age, income, and health.