Xiaojun Song

Xiaojun Song is an Associate Professor in the Business Department at Peking University. Contact information includes an email address of sxj@gsm.pku.edu.cn and a phone number of 010-62747522. The professor's website is http://en.gsm.pku.edu.cn/faculty/sxj/. No specific research areas or additional details about the professor's academic background or achievements are provided.

Xiaojun Song is an Associate Professor of Business Statistics and Econometrics at Peking University, specializing in non/semiparametric methods, hypothesis testing, and bootstrap techniques. His research focuses on developing statistical methodologies for econometric analysis, particularly in the context of nonparametric and semiparametric models. Song's work addresses challenges in hypothesis testing, specification tests, and model checking, with applications in financial econometrics, time series analysis, and causal inference. His publications explore topics such as Granger causality, volatility functions, and spatial panel data models, contributing to the understanding of nonlinear relationships and heteroskedasticity in economic data.