Yinchu Zhu

Assistant Professor of Economics

Departments/Programs

Economics
International Business School

Degrees

University of California, San Diego, Ph.D.
University of California, San Diego, M.A.
Bocconi University, M.S.
Zhongnan University of Economics and Law, B.A.

Expertise

Econometrics, Statistics, Machine Learning

Profile

Yinchu Zhu is an assistant professor in the Department of Economics and the International Business School. His research focuses on econometrics, statistics and machine learning. Prior to joining Brandeis in 2020, he served on the faculty at University of Oregon.

Courses Taught

ECON

184b

Econometrics

Scholarship

Bradic, Jelena, Jianqing Fan and Yinchu Zhu. "Testability of high-dimensional linear models with non-sparse structures." Annals of Statistics (2020). (forthcoming)

Komunjer, Ivana and Yinchu Zhu. "Likelihood ratio testing in linear state space models: An application to dynamic stochastic general equilibrium models." Journal of Econometrics 218. 2 (2020): 561-586.

Smith, Simon, Allan Timmermann and Yinchu Zhu. "Variable selection in panel models with breaks." Journal of Econometrics 212. 1 (2019): 323-344.

Chernozhukov, Victor, Kaspar Wuthrich and Yinchu Zhu. Exact and Robust Conformal Inference Methods for Predictive Machine Learning with Dependent Data. Proc. of the 31st Conference On Learning Theory. 2018.

Zhu, Yinchu and Jelena Bradic. "Linear Hypothesis Testing in Dense High-Dimensional Linear Models." Journal of the American Statistical Association 113. 524 (2018): 1583-1600.

Zhu, Yinchu and Jelena Bradic. "Significance testing in non-sparse high-dimensional linear models." Electronic Journal of Statistics 12. 2 (2018): 3312-3364.

Bradic, Jelena and Yinchu Zhu. "Comments on 'High-dimensional simultaneous inference with the bootstrap by Dezeure, Buhlmann and Zhang'." TEST 26. 4 (2017): 720-728.