معرفی
Serena Ng is the Edwin W. Rickert Professor of Economics at Columbia University and an Affiliated Faculty member in the Department of Statistics. Her research spans econometrics, empirical macroeconomics, time series analysis, and big data methods, with a focus on factor models, missing data, and macroeconomic forecasting. She has developed influential datasets such as FRED-MD and FRED-QD, widely used in macroeconomic research.
Her research interests include:
- High-dimensional econometric modeling
- Factor analysis and principal components
- Missing data and matrix completion
- Dynamic modeling of disasters and climate shocks
- Macroeconomic forecasting and nowcasting
- Structural vector autoregressions and DSGE identification
Her recent publications (2021–2025) reflect a strong trend toward integrating machine learning and computational methods into econometric modeling, particularly in handling large datasets, imputing missing values, and analyzing the macroeconomic impact of climate and disaster shocks. She has also contributed to foundational work in uncertainty measurement and time-varying parameter models.
Her scientific contributions are recognized through extensive publication in leading journals. While no specific awards are listed, her editorial and collaborative roles (e.g., with the Journal of Econometrics) indicate high standing in the profession.
She advises doctoral students in economics and statistics, though no names are publicly listed. She has received funding from major institutions including the National Science Foundation and NIH for interdisciplinary research. Her work bridges econometrics with environmental and health economics, particularly in projects related to climate adaptation and disaster impacts.
She maintains a laboratory-like research group focused on macroeconometric modeling and big data analysis, contributing to the development of tools for real-time economic monitoring and policy analysis.
