Assistant Professor, Department of Statistics
Investigator, The Methodology Center
409 Thomas Building
Department of Statistics
The Pennsylvania State University
University Park, PA 16802
Ph.D., University of Chicago, 2007. (Statistics)
B.S., University of Science and Technology of China, China, 2002. (Statistics)
Research Interests & Collaborations
My research focuses on nonparametric modeling, longitudinal models, quantile regression, and financial econometrics. I work with Runze Li and my student Seonjin Kim on the development and application of longitudinal models. I am primarily interested in developing efficient estimation and inference methodologies using quantile regression approach. I collaborate with Zhijie Xiao at Boston College to study efficient estimations for time series models. In addition, I work with my student Xiaoye Li on non-stationary time series.
Robust Inference for Dependent Data
National Science Foundation
2013-2016; Role: Principal Investigator
Zhao, Z. (in press). Inference for local autocorrelation process in locally stationary models, Journal of Business and Economic Statistics.
Zhao, Z., & Xiao, Z. (in press). Efficient regressions via optimally combining quantile information, Econometric Theory.
Kim, S., & Zhao, Z. (2014). Specification test for Markov models with measurement errors. Journal of Multivariate Analysis, 130, 118-133.
Zhao, Z., Zhang, Y., & Li, R. (2014). Nonparametric estimation under strong dependence. Journal of Time Series Analysis, 35, 4-15.
Zhao, Z., Wei, Y., & Lin, D. (2014). Asymptotics of nonparametric L-1 regression models with dependent data. Bernoulli, 20, 1532-1559.
Yao, W., & Zhao, Z. (2013). Kernel density based linear regression estimates. Communications in Statistics: Theory and Methods, 42, 4499-4512.
Li, X., & Zhao, Z. (2013). Testing for changes in autocovariances of nonparametric time series models. Journal of Statistical Planning and Inference, 143, 237-250.
Zhao, Z., & Li, X. (2013). Inference for modulated stationary processes. Bernoulli, 19, 205-227.
Kim, S., & Zhao, Z. (2013). Unified inference for sparse and dense longitudinal models. Biometrika, 100, 203-212.