Yi Pang

Profile

Yi Pang is a postgraduate researcher, working for his PhD thesis under Prof. Kausik Chaudhuri and Dr. Sandra Lancheros in Economics Department, Leeds University Business School.

He has rich experiences in academic writing and presentation. He is also very competent in coding-related skills, such as R, Matlab, Python, Stata, and Visual Basic. He is also familiar with Geo-software using shapefiles, such as ArcGIS and QGIS. His GitHub mainpage is https://github.com/kenforex.

Research interests

Yi Pang's research interests encompass both the study of applied / theoretical econometric models and empirical research. In the field of econometric models, his research primarily focuses on spatial econometric models, large-scale network models, panel data models with cross-sectional heterogeneity, panel data models with structural breaks, machine learning in casual inference, machine learning in financial and economic prediction, etc. Additionally, in empirical studies, he is primarily interested in regional studies, urban studies, property and stock price forecasting, and socio-economic inequality. He believes that through the quantitative analysis of financial and economic data, economists and investors can more easily extract useful information, thereby enhancing financial and economic forecasting as well as efficiency of policy implementation. As of now, he is dedicated to developing new econometric models that enable more effective estimation and inference, which could provide more useful tools for scholars in finance, economics, and the social sciences.

Qualifications

• Research Assistant for experiential learning innovation (partly funded by Curriculum Redefined)
• Teaching Assistant for LUBS1285, LUBS1951, LUBS2230, and LUBS3505 (2023 - 2025)
• PhD Candidate in Economics, Leeds University Business School (2021 - )
• MSc in Actuarial Finance, Leeds University Business School (2018 - 2019)
• BSc in Mathematics and Applied Mathematics, China University of Mining and Technology (2014 - 2018)