Municipal finance and fiscal constraint
I study how local debt, fiscal autonomy, and partisan signals shape municipal bond markets and local economic outcomes in the United States and China.
Greetings
I am a PhD student in the Department of Political Science at Yale and an MSc student in Computer Science at Yale. I received my Master’s in Chinese Economics and Political Affairs from the School of Global Policy and Strategy at UC San Diego, and my BA in Business Administration and China Studies from the Hebrew University of Jerusalem.
My research focuses on elite politics and elite speech, local governments, and politics and financial markets. Methodologically, I develop computational social science tools, especially text-as-data approaches using large language models and natural language processing, to measure political elite behavior and political speech. A central part of my research agenda examines municipal bond markets in the United States and China. I also work on projects about local-government economic outcomes, including pollution and growth, and how Central-Local Government Relations effect them. I alos have strong interest in how prediction markets affect politics.
Interests
- Political Economy
- Local Politics and Central-Local Government Relations
- Elite Politics and Political Communication
- Computational Social Science
Education
PhD in Political Science, 2024-2030 (expected)
Yale University
MSc in Computer Science, 2024-2026 (expected)
Yale University
Master in Chinese Economics and Political Affairs, 2022-2024
School of Global Policy and Strategy, UC San Diego
BA in Business Administration and China Studies, 2019-2022
The Hebrew University of Jerusalem
Research Agenda
How political elites, local governments, and financial markets shape one another.
Speech, ideology, and influence
My projects measure how political elites communicate, how ideology structures elite behavior, and how online platforms can reshape public perceptions.
Computational social science
I build text-as-data workflows using NLP, large language models, causal inference, and scalable data pipelines for political science research.
Selected Working Papers
Current projects from my CV.
R&R at China Quarterly
The End of Fiscal Autonomy: Rising Local Debt and Fiscal Constraints in Chinese Provinces
R&R at Science Advances
Foreign influencer operations: How TikTok shapes American perceptions of China
Preprint
How Prediction Markets Affect Political Speech
Experience
Research and data science roles.
Data Science Research Consultant
StatsLab, Yale
Visiting Researcher
Law, Economics and Data Science Group, ETH Zurich
Visiting researcher with Elliott Ash.
Student Researcher
China Data Lab, 21st Century China Center, UC San Diego
Responsibilities include:
- Develop natural language processing algorithms to conduct topic modelling on streaming corpora with millions of newspaper articles using machine learning frameworks
- Analyze the Chinese Local Bond Market using time series analysis, and fixed effect regressions
- Enhance an elite database by scraping data from official Chinese government websites and applying GPT API calls to extract relevant information
Software Engineering Research Intern
Data Science Institute, German Aerospace Center
Developed a machine learning type inference algorithm by combining machine learning and novelty detection; synthesized data with Python libraries including SpaCy, NumPy, Pandas, Matplotlib, and Annoy.
Research Project Manager
Digital Humanities Lab, Hebrew University of Jerusalem
Developed computational pipelines in Python using NLP models, data mining, big data analysis, and machine learning for research on human rights discourse in the UN.