Research

How do schools vary in assigning grades to students for university admissions relative to a standardized exam regime where teachers have no grading discretion? I exploit a natural experiment in the United Kingdom during the COVID-19 pandemic, when teacher-assigned grades replaced in-person standardized A-level exams. I provide evidence of differing grading policies across schools, shaped by school type and institutional quality. These policies followed persistent patterns across consecutive years, though schools with stricter standards in the first year revised them downward in the second. Within schools, grades were assigned differently by students' gender, race, and economic affluence, with patterns varying across school quality tiers. Despite the regressive tendencies between student background and grade improvements, the impact of grade inflation on application success was limited for students from disadvantaged backgrounds. Overall, the findings highlight how non-standardized assessments shifted grade distributions but had limited effects on diversifying selective universities.

This paper explores the impact of increased female representation on organizational gender inequality. Utilizing a newly constructed, comprehensive personnel panel dataset (n > 200,000) of public servants in Tokyo, which includes positional and biographical details, we trace the augmentation of women's presence during the war and its enduring effects. We provide causal estimates of how exposure to female colleagues affects employees' future career trajectories, leveraging variations in office composition prompted by military drafting. Our analysis reveals that an increased proportion of women in an office enhances the gender balance within the future co-worker pool of employees. These findings underscore how wartime conditions compel organizations to reallocate internal labor resources and establish pathways for integrating underrepresented groups into their workforce.

This study evaluates the effectiveness of taxes as regulatory tools within two-sided markets, focusing on the ride-hailing industry in Chicago. Using a difference-in-differences approach, it examines how a city-wide per-unit tax impacts price levels and travel volumes. The analysis shows that tax pass-through rates vary with demand: approximately 70% during high-demand periods and 40% during low-demand periods. Additionally, ride-hailing usage decreased by 2% and 5% respectively, with minimal effects on congestion during peak hours. These results suggest that ride-hailing platforms adjust the tax burden based on price elasticity to maintain transaction volumes, demonstrating the complexity of using taxes as a regulatory mechanism in dynamic markets.

European power markets are in the midst of unprecedented changes, with a record-breaking surge in energy prices.This paper investigates the impact of green power resources on the level and volatility of wholesale electricity prices at a granular level, using monthly observations for a panel of 24 European countries over the period 2014–2021 and alternative estimation methods including a panel quantile regression approach. We find that renewable energy is associated with a significant reduction in wholesale electricity prices in Europe, with an average impact of 0.6 percent for each 1 percentage points increase in renewable share. We also find evidence for a nonlinear effect—that is, higher the share of renewables, the greater its effect on electricity prices. On the other hand, while quantile estimation results are mixed with regards to the impact of renewables on the volatility of electricity prices, we obtain evidence that renewable energy has a negative effect on volatility at the highest quantiles. Overall, our analysis indicates that policy reforms can help accelerate the green transition while minimizing the volatility in electricity prices.