Conference Agenda

India launched the National Clean Air Program (NCAP) in 2019 as a major policy initiative aimed at reducing particulate pollution in severely affected cities. This paper evaluates the effect of NCAP on PM2.5 concentrations using a matched, difference-in-differences identification strategy with high-resolution, daily PM2.5 data. I find that between 2021 and 2023, NCAP failed to significantly reduce average PM2.5 levels or the number of days exceeding the Indian guideline for ambient air quality. This null average effect, however, hides substantial heterogeneity. I find that sub-districts that had poorer air quality prior to the start of the program have reduced PM2.5 concentrations by an average of 8 percent under NCAP. I also find that PM2.5 concentrations in wealthier sub-districts have declined slightly, but that PM2.5 concentrations in the poorer sub-districts have increased by an average of 6 percent. These results show that aggregate null effects conceal meaningful heterogeneity: NCAP improved air quality where pollution was most severe, but may have worsened conditions for the least affluent.

We exploit seasonal crop residue burning as a source of pollution and use exogenous year-to-year variation in wind direction to estimate the impact of rural sources of air pollution on crime in India. We find that short-term pollution exposure leads to an increase in violent crime, public order offenses, and most worryingly, violent crimes against women. Estimates suggest an unaccounted social cost of USD 600 million just from pollution exposure in the rice harvest season. We explore three channels: (i) pollution-induced aggression and weakened impulse control, (ii) reduced visibility leading to poor deterrence, and (iii) income distress from reduced earnings. Heterogeneity by crime type and spatial variation in law enforcement capacity support these mechanisms. Our findings highlight the need to account for issues of public safety and social instability in environmental and agricultural policy in developing countries.

Can agricultural support policies generate large-scale environmental externalities? This paper examines the impact of India’s Minimum Support Prices (MSPs) and public grain procurement policies on crop residue burning and air pollution. Using variation in government procurement operations, I show that procurement delinks local grain prices from local supply conditions and ties them to national price floors. This incentivizes farmers to respond to MSP hikes by intensifying cultivation of procured crops, leading to greater specialization and more residue burning. The resulting pollution is associated with increased medical spending by 19 percent and generates mortality costs that outweigh producer gains from higher prices by USD 1 billion. These findings highlight an overlooked environmental cost of agricultural support policies, where assured prices and procurement-driven intensification can impose substantial health costs on society.

Little is known about the long-term, dynamic effects of temperature on human capital. We analyze impacts of life cycle heat exposure on school completion using panel data spanning over forty birth cohorts in India, combined with a dynamic framework that incorporates lagged weather shocks and parental investments. Contemporaneous heat exposure systematically reduces grade completion whereas early-life heat exposure is sometimes associated with increased grade completion, likely due to compensatory parental investments. Parental investments also increase with contemporaneous exposure, but these efforts do not fully mitigate heat damages. Our findings underscore the importance of examining temperature impacts over long time frames.

This study investigates the relationship between income and CO₂ emissions by integrating the role of renewable energy (RE) deployment into the Environmental Kuznets Curve (EKC) framework, using panel data from 76 countries over the period 1990-2021. Its contribution is threefold. First, it provides updated and disaggregated estimates of income elasticity of RE deployment, revealing strong and significant elasticity in high-income countries (0.80) and upper-middle-income countries (0.49), but a negligible and statistically insignificant elasticity in lower-middle-income economies (-0.01). These results indicate that income growth alone does not drive RE deployment in low-income countries, where structural and institutional constraints persist. Second, adopting a novel counterfactual analysis, this study quantifies that global emissions would have been substantially higher without RE deployment, particularly in high-income economies. Using counterfactual scenarios, we find a one-unit increase in the wind FIT-to-electricity price ratio is associated with approximately 0.45 to 0.6 tonnes of CO₂ avoided per capita annually in high-income countries. Third, among economies beyond the EKC turning point, CO₂ emissions are driven not by income growth but by structural and technological factors, with a larger service-sector share and greater RE deployment significantly lowering per-capita emissions. Specifically, a one-percentage-point increase in the service sector’s share of GDP reduces CO₂ emissions per capita by about 1%, while a 1% increase in RE per capita lowers emissions by approximately 0.14%. Overall, the results underscore that RE is not a passive outcome but a central lever for CO2 emissions reduction.

This paper examines the impact of self-reported drought and flood occurrences on farm income in sub-Saharan Africa using panel data from four countries covering the period 2009 to 2016. The results reveal robust and negative effects of drought on farm income, with particularly strong and heterogeneous impacts across income sources. Specifically, drought reduces crop net income by 9.8% and total agricultural net income by 5.9%. These findings underscore the vulnerability of farming systems to drought shocks, and highlight the crucial role of efficient input use and dependable irrigation access in reducing drought-related income losses. In contrast, flooding shows no statistically significant effects, suggesting the need for further research to better understand the pathways through which floods influence agricultural outcomes.

This paper uses the information in a novel data set on four hundred German counties to estimate the relationship between annual growth rates and climate, in the period 1995-2019. Typical measures of annual temperature and precipitation are supplemented with annual intra-seasonal temperature and precipitation variability, and local anomalies identified using fixed and moving historical thresholds. This paper finds that in a typical year, both high and low temperature anomalies are associated with 1.2 and 0.4 pp reductions in the growth rate of county GDP per-capita, irrespective of historical threshold. Precipitation anomalies are not statistically significant. Sectoral growth rates have heterogenous associations, with agriculture being more sensitive to fixed threshold, manufacturing being almost identically sensitive to both thresholds, and the transportation sector being more sensitive to moving thresholds.