Thought Leadership

This paper studies the impact of the US-China tariff war on China, using high-frequency night lights data and grid-level measures of tariff exposure. Exploiting within-grid variation over time and controlling extensively for grid-specific contemporaneous trends, we find that each one-percentage-point increase in exposure to the US tariffs was associated with a 0.59% reduction in night-time luminosity. This impact was highly skewed across locations: Grids with negligible direct exposure to the US tariffs accounted for 70% of China’s population. But the tail 2.5% of China’s population with the highest exposure saw an implied 2.52% (1.62%) decrease in income per capita (employment) relative to unaffected grids. These effects were moreover concentrated in locations with a high commuting openness. By contrast, we do not find significant effects from China’s retaliatory tariffs, and offer evidence of several channels through which the impact on imported inputs was mitigated. In a parallel analysis at the prefecture level, we confirm that the US tariffs had discernible negative aggregate consequences.

This paper studies the unintended effect of English language requirement on educational inequality by investigating how the staggered rollout of English listening tests in China’s high-stakes National College Entrance Exam (NCEE) affected the rural–urban gap in college access. Leveraging administrative data covering the universe of NCEE participants between 1999 and 2003, we find that the introduction of English listening tests significantly lowered rural students’ exam score percentile ranks relative to their urban counterparts, resulting in a 30% increase in the rural–urban gap in college access. Our back-of-the-envelope calculations suggest that, as a result of this policy change, more than 54,000 rural students lost college seats to their urban peers between 1999 and 2003, and another 11,000 rural students who elite colleges could have admitted ended up in non-elite colleges, causing them significant future income losses.

This paper explores the effects of public information such as accounting earnings in a competitive lending setting with risk shifting. Debt financing creates incentives for borrowers to take on excessive risks, in particular in bad states of the world. If a privately informed inside creditor bids against outside creditors to extend a loan, public information levels the playing field, which affects the bidding and risk shifting. Nonetheless, a perfect public signal would yield the least efficient outcome: introducing some measurement noise alleviates risk shifting by subjecting outside creditors to the winner’s curse, allowing borrowers in bad states cheaper access to loans. However, for pessimistic priors about the borrower, greater public signal precision can alleviate risk shifting, at the margin. We discuss implications for financial reporting regulations along the business cycle and for creditor turnover.