To Prospective Postgraduate Students
I welcome students interested in econometric theory to pursue Ph.D. or M.Phil. I expect students to be well prepared in mathematics, statistics, economics, and programming (Python, R, or Matlab). Feel free to email me with your CV and self introduction.
To Prospective Research Assistants
Every year I receive multiple requests, mostly from undergraduates, volunteering research assistantship.
Genealogy
Supervisees
Papers with Supervisees
2023: #Ziwei Mei, Peter C.B. Phillips and Zhentao Shi, “The Boosted HP Filter Is More General Than You Might Think”
2023: #Ziwei Mei and Zhentao Shi, “On LASSO for High Dimensional Predictive Regression”
2023: #Ziwei Mei, Liugang Sheng and Zhentao Shi, “Hidden Nickell Bias in Panel Local Projection”
2023: Zhentao Shi and #Jingyi Huang, “Forward-Selected Panel Data Approach for Program Evaluation,” Journal of Econometrics, 234, 512-535.
2023: Wei Lin, Zhentao Shi, #Yishu Wang and #Ting Hin Yan: “Unfolding Beijing in a Hedonic Way,” Computational Economics, 61, 317-340.
2022: Ji Hyung Lee, Zhentao Shi, and #Zhan Gao: “On LASSO for Predictive Regression” Journal of Econometrics, 229(2), 322-340
2021: #Zhan Gao and Zhentao Shi: “Implementing Convex Optimization in R: Two Econometric Examples,” Computational Economics, 58, 1127-1135
2021: #Ka Yan Cheng, Naijing Huang and Zhentao Shi: “Survay-Based Forecasting: To Average or Not To Average,” in Vladik Kreinovich, Songsak Sriboonchitta, Woraphon Yamaka (eds.), Studies in Computational Intelligence: Behavioral Predictive Modeling in Economics, vol 897, pp 87-104, Springer-Verlag