I am a Research Data Analyst at the Center on Food Security & the Environment at Stanford University. At Stanford, I work with Marshall Burke and Sam Heft-Neal on research aiming to identify causal relationships between climate and various health, social and economic outcomes. Recent research combines household surveys with remote sensing data to examine environmental drivers of child health.
My work at Stanford University and the University of Chicago has trained me in econometric research methods that I have applied in a variety of settings. I am also familiar with various machine learning algorithms to estimate heterogeneous effects in high dimensional setting.
- In recent decades, poor air quality has been recognized as one of the leading global health risks, with particularly severe adverse effects thought to occur in developing countries. However, due to limited data availability, most disease burden estimates for developing countries are extrapolated from wealthy countries. Using remote sensing data and a novel instrumental variable approach, we develop a new approach to identify most comprehensive estimates of global mortality risks from pollution in developing countries. Further, we characterize heterogeneous effects using the detailed set of individual, family, and village covariates collected in the surveys combined with machine learning inference algorithms.
- Health effects of temperature are poorly identified for most tropical regions with conflicting evidence on whether temperature helps or hurts outcomes. Based on prior research in epidemiology, we hypothesize and test a competitive temperature risk framework that allows for temperature to have opposite effects depending on the channel. We find evidence that a temperature increase improves health outcomes when malaria is a leading health risk and worsens health outcomes when it is not. We tease out pure temperature effect ( on health) and generate prediction scenerios under different future climate predictions.
Previously, I have worked as a field research associate with Karthik Muralidharan and Paul Niehaus for JPAL’s Payments and Governance Research Program. I also worked with Jeremy Magruder for a project estimating impact of new source of standardized information on search friction in Indian labor market. This gave me a valuable experience in running field surveys and managing government relations at multiple levels. My experience with J-PAL marked the begining of my obsession with state capacity and continues to shape my thinking in topics related to state capacity, development and governance.
I am very excited about research lying at the interaction of climate and society, governance, state capacity, and political economy. My interests can be grouped into two broad themes:
- Many parts of the world ( eg, Ganges basin in India and Bangladesh) are already dealing with extreme weather events with increasing frequency. I am interested in how society adapts, or under-adapts, to face these climactic events and the economic costs of such (under) adaptation.
- I am very interested in state capacity which seems to be highly predictive of a range of social and economic outcomes. Specifically, I am interested in using tools from public economics and political economy to address sub-optimal state capacity and leaky welfare delivery systems. The big picture goal here is to improve governance in developing countries as it seems to be the next frontier: affecting change through the State.
Lessons from this research are likely to be extremely important in the near future when as we are required to come up with immediate and effective ways to deal with climate change. Effectively building state capacity across many parts of the world is all the more crucial in our endeavor against minimizing social and economic damage resulting from climate extremes.
I hold a Masters in Research Methods (MACRM) from The University of Chicago Harris School and a Bachelors in Technology (B.Tech) from LNM IIT, India.
Please find the recent CV here.