Hu Naiyuan
HU NAIYUAN
Ph.D Candidate in Economics
I am a job market candidate and I will be available for interviews.
REFERENCES
Professor Yuan MEI
Email: yuanmei@smu.edu.sg
Tel: +65 68085212
Professor Jing LI
Email: lijing@smu.edu.sg
Tel: +65 68085454
WORKING PAPERS
"Educational Migration in China", with Lin Ma (Job Market Paper)
Educational resources are distributed unevenly across space and could contribute to spatial inequality. We develop a dynamic spatial model with life-cycle elements to study the impacts of location-specific educational resources. In the model, individuals determine whether and where to attend college, weighing on the distance to home, the expected option value of education, and the educational resources in the destination. Locations with more colleges attract more students. Moreover, as mobility costs increase with age, many college graduates stay in the city of their alma mater, leading to long-term changes in skill composition. We quantify the model to the context of China and structurally estimate the cost of obtaining a college degree in each location. We show that the college expansion between 2005 and 2015 had minimal impacts on welfare and skill composition, as it diverts resources towards the locations already well-endowed with colleges. More evenly distributed colleges could improve aggregate welfare and reduce spatial inequality at the same time.
RESEARCH PAPERS
"(Trade) War and Peace: How Can International Sanctions Be Imposed Most Cost Efficiently?", with Gustavo de Souza, Haishi Li, and Yuan Mei, 2023. R&R Journal of Monetary Economics.
Trade sanctions are a common instrument of diplomatic retaliation. To guide current and future policy, we ask: What is the most cost-efficient way to impose trade sanctions against Russia? To answer this question, we build a quantitative model of international trade with input-output connections. Sanctioning countries simultaneously choose import tariffs to maximize their welfare (measured with real income) and to minimize Russia’s welfare, with different weights placed on these objectives. We find, first, the sanctioning countries can cause moderate economic damage in Russia, with Russian welfare falling 1.3% to 2.9%, depending on whether Russia retaliates or not. Second, for countries with a small willingness to pay for sanctions against Russia, the most cost-efficient sanction is a uniform, about 20% tariff against all Russian products. Third, if the European Union (EU) is willing to pay at least US$0.67 for each US$1 drop in Russian welfare, an embargo on Russia’s mining and energy sector products and about 50% tariffs on all other imports from Russia is the most cost-efficient policy. Finally, if countries target politically relevant sectors, a global embargo against Russia’s mining and energy sector is the cost-efficient policy even when there is a small willingness to pay for sanctions.
“Tariffs as Bargaining Chips: A Quantitative Analysis of US-China Trade War”, with Yuan Mei and Tong Ni
The Biden administration maintains Trump tariffs on Chinese imports, contrary to Biden's campaign commitments. We investigate the hypothesis that these tariffs serve as a leverage in future trade talks with China. Our quantitative model, incorporating disaggregated U.S. regions and international trade linkages, estimates bargaining power and simulates tariff bargaining outcomes. Results show consistent post-trade war negotiation improvements in U.S. welfare regardless of bargaining power. With an estimated U.S. bargaining power of 0.47, the post-war negotiation yields additional 0.04% gains for U.S. taking the trade war impacts into account.