Ping Yu
Prof. Ping YU
Associate Professor

2857 8358

KK 1110

Academic & Professional Qualification
  • Ph.D., M.S., University of Wisconsin-Madison
  • M.S., B.A., Peking University

Dr. Ping YU graduated from Peking University in 2000 with a B.S. in Mathematics and Economics, and in 2002 with an M.S. in Finance.  He obtained his M.S. in Economics in 2005, and Ph.D. in Economics in 2009, both from the University of Wisconsin-Madison.  Before joining the Faculty of Business of Economics at The University of Hong Kong as Assistant Professor in 2014, he was a lecturer at the University of Auckland, New Zealand for five years.

Ping’s research interests are in theoretical and applied microeconometrics, especially in threshold regression and treatment effects evaluation.  He has published several papers in academic journals including Journal of Econometrics, Econometric Theory, and Journal of Business & Economic Statistics among others.

Research Interest
  • Threshold Regression
  • Treatment Effects Evaluation
Awards and Honours
  • The Research Excellence Award 2013 by the University of Auckland Business School
  • The RBNZ-NZESG Award in Econometrics by the New Zealand Econometrics Study Group (NZESG), 2012
Selected Publications
  • “Threshold Regression With a Threshold Boundary,” (with Xiaodong Fan), Journal of Business & Economic Statistics, 39, 2021, pp. 953-971.
  • Robust Estimation of Derivatives Using Locally Weighted Least Absolute Deviation Regression“, (with Wenwu WangLu Linand Tiejun Tong), Journal of Machine Learning Research, 20(60), 2019, pp. 1-49.
  • “Threshold Regression with Endogeneity,” (with Peter Phillips), Journal of Econometrics, 203, 2018, pp. 50-68.
  • “Regression Discontinuity with Unknown Discontinuity Points: Testing and Estimation,” (with Jack Porter), Journal of Econometrics, 189, 2015, pp. 132-147.
  • “Adaptive Estimation of the Threshold Point in Threshold Regression,” Journal of Econometrics, 189, 2015, pp. 83-100.
  • “The Bootstrap in Threshold Regression,” Econometric Theory, 30, 2014, pp. 676-714.
  • “Likelihood Estimation and Inference in Threshold Regression,” Journal of Econometrics, 167, 2012, pp. 274-294.