My research agenda aims to explain how governments address challenges in delegating discretionary power to bureaucrats in weak institutional environments. To analyze this question, my dissertation leverages natural-language-processing (NLP) implementations and statistical inferences with large, textual datasets collected from government archives. I argue that to monitor bureaucrats, governments under weak institutions could employ alternative strategies, as "suboptimal" substitutes of formal oversight institutions in modern bureaucracies: (1) strategic rulemaking with top-down control as a means of oversight, (2) selection of politically loyal bureaucrats, and (3) informal patron-client relations across different government levels. Equally important, I explore the social and institutional consequences of these strategies, for example, how discretionary authority of the state reshapes the state and society relations in weak institutional environments. 

Empirically, I draw upon China as my case, and have developed extensive micro-level policy-document datasets, government-job-opening datasets, and formal game-theoretical models to analyze my research questions.

My research has received support from various institutions, including APSA DDRIG (Doctoral Dissertation Research Improvement Grant, sponsored by the National Science Foundation), Humane Studies Fellowship from the Institute of Humane Studies (IHS) at George Mason University, Summer Mini-Grant from the BU CISS (Center for Innovation in Social Science), and BU CAS/CISS/Spark!.