Zhibiao Zhao, Ph.D. | The Methodology Center

Zhibiao Zhao, Ph.D.

Zhibiao ZhaoAssistant Professor, Department of Statistics

Investigator, The Methodology Center

 

409 Thomas Building

Department of Statistics

The Pennsylvania State University

University Park, PA 16802

 

814-865-6552

Website

 

Education

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.

Recent Grants

Robust Inference for Dependent Data

National Science Foundation

2013-2016; Role: Principal Investigator

     

     

    Recent Publications

    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.  

     

    Like Us On Facebook or Tweet This Page