- Mao， Guangyu
- Title: Associate Professor
- Department: Finance
Education Background
Bachelor：2003-09-2007-07，Double degree in science/Economics，Peking University （double degree in science and economics）
Ph.D.：2007-07-2013-07，Finance （Master and PhD），Peking University
Work Experience（Including Academic Visiting）
1.2016-12-01，School of Economics and Management， Beijing Jiaotong University，Associate Professor
2.2016-08-28，2017-08-29，University of Wisconsin-Madison，Visiting Scholar
3.2013-07-01，2016-11-01，School of Economics and Management， Beijing Jiaotong University，Lecturer
Research Interests
Econometrics
Research Project
1. Academic Research
1. (CO-PI)Research on financial contagion of multi-layer network interaction between emotion and financial distress,MOE，Department of Humanities and Social Sciences Youth,CO-PI:Xiao， D.(2020-03-20 - 2022-12-31).
2. (CO-PI)Study on the effect of urban traffic structure on carbon emission in Beijing and its optimization policy,Beijing High-End Think Tank Project,CO-PI:Ou， G.(2019-06-30 - 2019-12-31).
3. (CO-PI)A comparative study on systemic risk measurement methods of financial institutions in China,Major Cultivation Project Supported by Humanities and Social Sciences of Basic Scientific Research Operating Expenses,CO-PI:Zhang， X.(2019-03-15 - 2021-09-30).
4. (PI)Research on financial risk measurement based on extreme value theory,Major Cultivation Project Supported by Humanities and Social Sciences of Basic Scientific Research Operating Expenses,PI:Mao， G.(2018-03-01 - 2019-12-31).
5. (CO-PI)Research on regional optimization of transportation structure in China under the background of new urbanization,National Social Science Foundation of China Youth,CO-PI:Liu， T.(2017-06-30 - 2019-12-31).
6. (CO-PI)Research on traffic flow prediction and congestion conduction model based on time series mining,National Natural Science Foundation of China Youth Fund,CO-PI:Zhou， H.(2017-01-01 - 2019-12-31).
7. (PI)Research on model selection based on spatial econometric model,National Natural Science Foundation of China Youth Fund,PI:Mao， G.(2017-01-01 - 2019-12-31).
8. (PI)Study on covariance matrix test under big data environment,Beijing Natural Science Foundation,PI:Mao， G.(2017-01-01 - 2018-12-31).
9. (PI)Cross sectional correlation test research of large dimension panel data model,MOE，Department of Humanities and Social Sciences Youth,PI:Mao， G.(2016-07-12 - 2019-07-11).
10. (CO-PI)A study on the spatio-temporal differentiation of the relationship between urbanization efficiency and traffic line density in Beijing,Beijing Philosophy and Social Affairs Office,CO-PI:Liu， T.(2015-12-31 - 2020-12-04).
11. (CO-PI)Research on traffic congestion control based on big data rule mining,Beijing Philosophy and Social Affairs Office,CO-PI:Zhou， H.(2015-06-30 - 2019-06-30).
12. (PI)Research on the development and governance of metropolitan area,Basic Scientific Research Operating Expenses,PI:Mao， G.(2015-01-16 - 2015-12-30).
Teaching Courses
Undergraduate
Econometrics
Comprehensive Research on Finance （Part 2）
Financial Metrology
Experimental economics
Introduction to Financial Measurement
Postgraduate
Fixed income securities
Economic Research Methods
International Economic Topics （Bilingual）
Time series analysis and application
statistics
Time series analysis
Advanced Econometrics
Publications
1. Peer Reviewed Journals
1. Mao， G.,(2019).On high-dimensional tests for mutual independence based on Pearsons correlation coefficient,Communications in Statistics-Theory and Methods.
2. Mao， G.,& Shen， Y.(2019).Bubbles or fundamentals? Modeling provincial house prices in China allowing for cross-sectional dependence,China Economic Review.
3. Mao， G.,(2018).Testing for error cross-sectional uncorrelatedness in a two-way error components panel data model,Communications in Statistics-Theory and Methods.
4. Mao， G.,& Zhang， Z.(2018).Stochastic Tail Index Model for High Frequency Financial Data with Bayesian Analysis,Journal of Econometrics.
5. Mao， G.,(2018).Testing for sphericity in a two-way error components panel data model,Econometric Reviews.
6. Mao， G.,(2018).Testing independence in high dimensions using Kendalls tau Guangyu Mao,Computational Statistics & Data Analysis.
7. Mao， G.,(2017).Variance-corrected tests for covariance structures with high-dimensional data,Journal of Multivariate Analysis.
8. Mao， G.,(2017).Robust test for independence in high dimensions,Communications in Statistics-Theory and Methods.
9. Mao， G.,(2016).A note on tests for high-dimensional covariance matrices,Statistics and Probability Letters.
10. Mao， G.,(2016).Testing for error cross-sectional independence using pairwise augmented regressions,Econometrics Journal.
11. Mao， G.,(2016).Do Regional House Prices Converge or Diverge in China,China Economic Journal.
12. Li， Z.,Ou， G.， & Mao， G.(2016).Analysis on road transportation infrastructure and spatial correlation of regional economic development,Journal of Yunnan University of Finance and Economics.
13. Mao， G.,(2015).A note on testing complete independence for high dimensional data,Statistics and Probability Letters.
14. Mao， G.,(2015).Efficient penalized estimation for linear regression model,Communications in Statistics-Theory and Methods.
15. Mao， G.,(2015).Model selection of M-estimation models using least squares approximation,Statistics and Probability Letters.
2. Other publications
Teaching Development Articles
1.
Mao， G.. Consistency concept teaching based on Monte Carlo Simulation method. Innovation for the future to promote the construction of double first - class. 2017-12..
2.
Mao， G.. Some thoughts on improving the teaching effect of econometrics in undergraduates. The road to the cultivation and construction of undergraduate talents in world-class universities with distinctive features. 2016-04..
Others
1.
Mao， G.. Consistency concept teaching based on Monte Carlo Simulation method. Innovation for the future to promote the construction of double first - class. 2017-12. .
2.
Mao， G.. Some thoughts on improving the teaching effect of econometrics in undergraduates. The road to the cultivation and construction of undergraduate talents in world-class universities with distinctive features. 2016-04. .
