Lab Director

Academic Positions: Tenured Professor; Director of Big Data Research Lab; Senior Research Fellowship, Harvard Law School; Cross Appointed to Statistics and Actuarial Science

Areas of specialization: Econometric Theory, Applied Econometrics, Functional Data Analysis, Machine Learning, Labour Economics

Research interests

I am primarily interested in theoretical econometrics, estimation and specification test of semi-parametric/nonparametric models in particular; and their applications in labor economics. I teach mathematical economics and econometrics both at the undergraduate and graduate level.

Biography

Tao spent his first 22 years in Shanghai, China. Before he became an Assistant Professor at the University of Waterloo, he was in graduate school for 9 years in New England, USA.

His research on econometrics is both theoretical and applied. The theoretical part focuses mainly on micro-econometrics and functional data analysis, and the major applied fields are labor and urban economics.

Tao is a big fan of basketball, Age of Empires and enjoys reading “A Global History: From Prehistory to the 21st Century”. This is his favourite quote: Imagination is more important than knowledge. -- Albert Einstein

Selected publications

• Chen, T., Y. Ji, Y. Zhou and P. Zhu, “Testing conditional mean independence under symmetry”, Journal of Business & Economic Statistics, 36 (2018), 615-627.
• Chen, T., "Semiparametric efficiency for censored linear regression models with heteroskedastic errors", Econometric Theory, 34 (2018), 228-245.
• Chen, T., and G. Tripathi, "A simple consistent test of conditional symmetry in symmetrically trimmed tobit models", Journal of Econometrics, 198 (2017). 

• Chen, T. and T. Parker, "Semiparametric Efficiency for Partially Linear Single-Index Regression Models", Journal of Multivariate Analysis, (130), 2014.