Electronic Theses and Dissertations

Date

2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Economics

Committee Chair

Joonhyung Lee

Committee Member

Andrew Hussey

Committee Member

Duy Nguyen

Committee Member

Han Yu

Abstract

This dissertation includes two essays on international trade, and the previous US-China trade war is the main theme. The first essay focuses on an unintended economic impact of a third nation as tensions between the United States and China worsened. In particular, we question whether Vietnam, a neighboring nation of China, increased their exports to the US. The second essay examines the heterogeneous effect of US tariffs on China’s US exports by implementing a machine learning method called causal forest. Specifically, we focus on Chinese sectors with the following characteristics: comparative advantage in US exports, strong multinational corporation activities, and trade to third nations. In the first essay, we study how a third country was able to benefit from the US-China trade (2018-2019) war. Using Vietnam’s US exports as a case study, we examine the unintended consequences of the US-China trade war for third countries, focusing on trade reallocation mechanisms. Our analysis, based on HS8-digit US import data from 2017Q1 to 2020Q4, yields three key findings. First, Vietnam’s US exports increased by 8% post-trade war, though this average effect is statistically insignificant. Second, in sectors where China held a revealed comparative advantage (RCA) before the trade war, Vietnam’s exports grew significantly, indicating that Vietnam captured China’s competitive edge in these products. Third, sectors with rising Vietnam-to-US exports are strongly associated with high pre-trade war China-to-Vietnam exports and increased multinational corporation (MNC) activity, suggesting tariff circumvention through MNC-driven supply chain reallocation. These findings hold across extensive (new trade relationships) and intensive (growth in existing trade) margins, with MNC activity more strongly tied to the extensive margin, implying MNCs are relocating operations to Vietnam to enable exports of new products to the US. By quantifying the trade war’s impact on a bystander country, our study contributes to the literature on global value chain dynamics and the spillover effects of trade protectionism. In the second essay, we apply a causal machine learning algorithm to study heterogeneous treatments of the trade war. We implement causal forest to examine the heterogeneous impact of the US-China trade war on China’s US exports based on the sectoral characteristics. We find that the revealed comparative advantage (RCA) in US exports and the strength of multinational corporation (MNC) activities are strongly linked with the estimation of the conditional treatment effect. The subsequent 2 by 2 interactions based on these two variables suggest that the Chinese sectors with an RCA in US exports experienced the largest decline, as the percentage decrease ranges from approximately 74 to 80%. Although MNC-active Chinese sectors also faced a reduction in their US exports, the magnitude is less as it is between approximately 20 and 26%. For both RCA and MNC interactions, trade reallocation to other third countries was not effective against tariffs.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest.

Notes

Embargoed until 08-06-2027

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Available for download on Friday, August 06, 2027

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