Prof. Lixiong Yang | Machine Learning | Best Researcher Award
Professor | School of Management, Lanzhou University | China
Dr. Lixiong Yang is a distinguished scholar and professor of economics at the School of Management, Lanzhou University, China. With a strong foundation in econometrics, financial econometrics, and machine learning, he has made significant contributions to advancing quantitative methods in economic research. His work focuses on developing theoretical models and applying them to capital markets, financial warning systems, and macroeconomic policy evaluation. Dr. Yang has authored numerous impactful publications, served as an external reviewer for esteemed journals, and supervised graduate theses. He is also a recipient of multiple awards, including recognition for his doctoral dissertation and academic mentorship.
Profile
Education
Dr. Yang received his Ph.D. in Economics from the Jinhe Center for Economic Research at Xi’an Jiaotong University in 2014. His dissertation, “A Method of Nonstationary Time Series Analysis Based on the Degree of Cointegration,” introduced innovative approaches to time-series econometrics. Before that, he earned his B.E. in Financial Mathematics from Sichuan University in 2009. His academic journey reflects a strong inclination toward econometric theory and its practical applications.
Experience
Dr. Yang has held various academic positions at Lanzhou University. He was appointed as a professor in December 2022, following his selection as a Cuiying Scholar in 2020. Earlier, he served as a junior professor (2019–2022) and lecturer (2014–2019). His teaching repertoire includes advanced econometrics, machine learning, and undergraduate econometrics. Additionally, he has actively contributed to the academic community as an external reviewer for prestigious journals such as the Journal of Econometrics and Studies in Nonlinear Dynamics and Econometrics.
Research Interests
Dr. Yang’s research spans econometric theory, panel data models, big data analysis, machine learning, and financial econometrics. His interests also extend to financial warning systems, capital markets, and macroeconomic policy. He has led and contributed to multiple national-level research grants, focusing on time-varying threshold models, high-dimensional data analysis, and fiscal policy effectiveness.
Awards
Dr. Yang’s academic excellence has been recognized through several awards. Notable among them are:
Excellent Supervisor of Lanzhou University Undergraduate Thesis (2021)
Excellent Doctoral Dissertation of Shaanxi Province (2017)
National Scholarship for Doctoral Students (2013)
He has also been commended for his mentorship, winning awards for guiding students in the “Challenge Cup” competition and other academic initiatives.
Publications
Dr. Yang has authored over 20 peer-reviewed articles, focusing on econometrics and its applications. Seven notable publications include:
Yang, L. et al., “Panel Threshold Model with Covariate-Dependent Thresholds and Unobserved Individual-Specific Effects,” Econometrics Review, 2024. Cited by: Advanced Studies in Econometrics.
Yang, L. et al., “Is There a State-Dependent Optimal Interval for Firms’ R&D Investment?” Applied Economics, 2024. Cited by: Industrial Innovation Reports.
Yang, L., “Threshold Quantile Regression Neural Network,” Applied Economics Letters, 2023. Cited by: Computational Finance Insights.
Yang, L., “High-Dimensional Threshold Model with Time-Varying Thresholds,” Studies in Nonlinear Dynamics and Econometrics, 2022. Cited by: Statistical Models Journal.
Yang, L., “Panel Threshold Spatial Durbin Models,” Economics Letters, 2021. Cited by: Urban Economic Analysis.
Yang, L., “Regression Discontinuity Designs with State-Dependent Unknown Discontinuity Points,” Studies in Nonlinear Dynamics and Econometrics, 2019. Cited by: Econometrics Advances.
Yang, L., “Debt and Growth: Is There a Constant Tipping Point?” Journal of International Money and Finance, 2018. Cited by: Global Economic Studies.
Conclusion
Dr. Lixiong Yang embodies the integration of theoretical rigor and practical application in economics. His commitment to advancing econometric methodologies, coupled with his impactful teaching and mentorship, solidifies his status as a leading scholar. Through his extensive research, he continues to shape the future of quantitative economic analysis and inspire the next generation of economists.