Date of Award

6-26-2026

Date Published

August 2026

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Economics

Advisor(s)

Devashish Mitra

Second Advisor

Abdulaziz Shifa

Keywords

International Trade;Political Economy

Subject Categories

Economics | Social and Behavioral Sciences

Abstract

This dissertation is composed of three papers that explore how institutions, globalization, and trade shocks affect individuals' political preferences and firms' behavior. The first paper studies how mass protest events drive political change among citizens. I exploit the 2019 Anti-Extradition Law Amendment Bill Movement (ANTI-ELAB protest) in Hong Kong and its impact on the subsequent 2019 Hong Kong District Council Election. Taking advantage of a granular dataset of organized events during the protest, I exploit spatial variation in protest intensity, as measured by the number of events, across Constituency Areas. Empirical results show that in Constituency Areas with higher protest intensity, there were larger increases in voter turnout in the 2019 District Council Election compared to 2015. The effect is primarily driven by local events, suggesting that proximate mobilization and local interactions play a crucial role in shaping political engagement. To strengthen causal interpretation, I employ a set of public transportation accessibility measures as instrumental variables. Additional analyses reveal that protest intensity also affected people's political stances, leading to a potential (asymmetric) polarization and an overall shift toward the Pro-democracy camp. These findings contribute to the emerging literature on the political consequences of protest and offer new insights into studying within-city-level social unrest. The second paper, which is coauthored with Devashish Mitra and Yang Liang, studies how automation and Chinese import-competition shocks simultaneously affect the Republican vote share in the House and Presidential elections during 2000-2016. 2SLS estimates indicate that, by the 2016 House elections, a full interquartile-range robot exposure increase resulted in a 0.63 percentage-point Republican vote share increase. In fact, greater automation exposure consistently boosted the Republican vote share during our entire sample period. In the House, import penetration initially benefited Democrats but, post-2012 the effect turned insignificant, and recently even moved slightly positive for Republicans. On average, during 2000-2016, Chinese import penetration had a significant positive effect on the Republican vote share in the Presidential elections but not in the House elections. Our event study investigates causality. We also perform thorough analyses of labor-market channels and electoral competition. Counterfactual analyses show that small reductions in our shock(s) would have changed two Presidential election outcomes. The third paper, coauthored with Laura Connolly, Yang Liang, and Jiajun Lu, investigates how the U.S.–China trade war affected the survival of Chinese exporting firms. We construct a novel monthly firm-level panel dataset that links business registration records, export portfolios, and tariff exposure from 2017 to 2024. Using a continuous-treatment event study research design, we find that higher exposure to U.S. tariffs significantly increased the likelihood of permanent firm exit. A 10 percentage point increase in firm-level exposure to U.S. tariffs increases firm exit probability by 0.14 percentage points within six months, or a 15.6% increase relative to the mean exit rate. The effects are concentrated among smaller, narrowly specialized exporters that rely heavily on a single exported product. We also find suggestive evidence of positive local spillovers. In regions with more firms directly exposed to U.S. tariffs, exporting firms that do not ship to the U.S. market are less likely to exit, consistent with localized reallocation of resources.

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