Research

We examine whether the European Union’s Carbon Border Adjustment Mechanism (CBAM) generated anticipatory trade responses prior to implementation. Using bilateral monthly trade data from EU COMEXT between 2018 and 2023, we estimate an event-study specification comparing CBAM-covered sectors to non-CBAM-covered sectors across advanced and emerging market exporters to the EU. We find evidence of export frontloading following the announcement of CBAM, particularly among emerging market economies, with exports in CBAM-covered sectors rising by approximately 42–49 percent relative to non-CBAM-covered sectors within three quarters of the announcement. No comparable response is detected for advanced economies. The results suggest that climate-linked trade policy can influence international trade flows well before formal enforcement begins.

This paper studies the impact of lockdown-induced mobility shocks during the COVID-19 pandemic on employment outcomes in India. Using an individual-level panel from the Consumer Pyramids Household Survey (CPHS) merged with district-level mobility measures from Google Community Mobility Reports, we exploit cross-district variation in reductions in workplace mobility during the national lockdown as a measure of treatment intensity in a difference-in-differences framework with individual and time fixed effects. We find that while average effects on employment are modest, there is substantial heterogeneity: negative effects are concentrated among individuals in the lowest income quartile and among self-employed and salaried workers. We also document significant gender differences, with adverse effects for women but no statistically significant effects for men at the extensive margin. Decomposing employment dynamics, we show that these effects are driven primarily by an increase in job exits and a decline in job entry, with exit effects being substantially larger in magnitude. Overall, the results highlight the unequal labor market consequences of pandemic-induced mobility restrictions across socioeconomic groups.

We examine the effect of affordable high-speed mobile internet on children’s educational outcomes using the nationwide rollout of Reliance Jio’s 4G network in India in 2016 as a natural experiment. Jio’s entry led to an abrupt and unanticipated decline in mobile data prices and a rapid expansion of 4G coverage. Exploiting cross-district variation in early exposure to Jio’s network, we implement a difference-in-differences design using district-level test score data from the Annual Status of Education Report (ASER). We find that districts with greater initial access to low-cost 4G internet experienced statistically significant improvements of approximately 0.18 standard deviations in reading scores and 0.15 standard deviations in mathematics scores between 2016 and 2018. These effects are robust to alternative treatment definitions, a continuous treatment-intensity specification, and controls for local economic activity and demographic composition. Our results suggest that widespread access to affordable, mobile-first internet can complement traditional education inputs and improve learning outcomes in developing-country contexts.