Research

This paper explores the relationship between market concentration and environmental performance, with a particular focus on the aftermath of mergers. Drawing from foundational economic principles, I hypothesize that increased market power, typically associated with reduced output relative to competitive market conditions, could similarly influence a firm's emissions profile, potentially lowering GHG emissions. This hypothesis introduces a complex tension between two pivotal policy objectives: the reduction of emissions and the preservation of competitive market structures. Novel empirical findings suggest that mergers exhibit a comparable positive impact on environmental indicators. This insight paves the way for a broader discussion on the dual objectives of companies in merger scenarios — increasing their market power versus achieving environmental efficiency. 

This study investigates the intricate relationship between bankruptcy proceedings and climate risk. By constructing a unique dataset spanning business bankruptcies from 2000 to 2023 linked to companies' environmental indicators, we document that green and brown companies do not face different probabilities of experiencing distress and bankruptcy. However, bankrupted brown firms are more inclined to file for reorganization instead of liquidation and encounter lower bankruptcy costs. To mitigate endogeneity concerns in companies' bankruptcy decisions, we employ a randomized bankruptcy judge allocation approach to understand how bankruptcy affects firms' environmental performance. Using post-bankruptcy facility emission data, our findings show that firms undergoing reorganization tend to exhibit lower emissions when compared to their liquidated counterparts. This distinction highlights the significant but previously understudied impact that bankruptcy proceedings can have on a firm's environmental footprint, suggesting that reorganization efforts may worsen environmental performance. 

This paper investigates the impact of the 2022 energy price shock on firm-level employment, using detailed administrative data from the UK. We exploit variation in firms’ energy dependency, measured through both energy elasticity and energy share, to estimate the heterogeneous effects of rising energy costs on labor demand. The baseline OLS regression results indicate that the post-2021 period was characterized by a contraction in employment, particularly among energy-intensive firms. Our difference-in-differences (DiD) framework shows that firms in the top quintile of energy elasticity experienced significantly larger employment declines than those in the bottom quintile, suggesting that energy elasticity is a key determinant of firms’ vulnerability to energy shocks. Additionally, we estimate a counterfactual scenario in which energy prices remained constant, showing that around 1% of jobs in our sample were lost due to energy price increases in 2022 and 2023. We also document significant regional heterogeneity: firms located in rural and peripheral regions have higher energy elasticities than those in metropolitan areas. This is likely due to structural labor market differences, including lower worker mobility, fewer alternative job opportunities, and weaker infrastructure in rural areas. These findings highlight the broader implications of energy price volatility for labor markets, particularly in energy-intensive sectors and regions with limited labor market flexibility. Our results suggest that targeted policy interventions—such as energy price stabilization mechanisms and labor mobility programs—could help mitigate the adverse employment effects of energy shocks.