Econometric theory & causal inference
Identification, estimation, and inference for treatment effects, instrumental variables, and nonlinear models with high-dimensional covariates.
Associate Professor of Economics
Department of Economics
The Chinese University of Hong Kong
My research spans theoretical and applied econometrics, causal inference with machine learning, and high-dimensional portfolio analysis.
I develop methods for credible empirical work in data-rich environments, with applications in economics and finance.
Research agenda
I work across econometric theory and applied research, with a particular interest in reliable inference when datasets are large, complex, or high-dimensional.
Identification, estimation, and inference for treatment effects, instrumental variables, and nonlinear models with high-dimensional covariates.
High-dimensional portfolio construction, robust risk analysis, factor models, and machine-learning methods for investment decisions.
Empirical projects in labor economics, financial economics, management science, and decision-making in data-rich environments.
Resources
Code, software, data, and documentation supporting current and published research.
CRAN packages
hdcateConditional average treatment effects naiveregHigh-dimensional instrumental variablesFor more information, see Personal website
Work with me
I welcome inquiries from prospective full-time and part-time research assistants or fellows with strong quantitative and programming backgrounds.
View opportunitiesContact
Telephone+852 3943 8001
OfficeRoom 903
Esther Lee Building
DepartmentDepartment of Economics
The Chinese University of Hong Kong
Shatin, New Territories, Hong Kong
WebsitePersonal website