Dr. Renfang Tian

Assistant Professor

Phone:
Email: rtian2@uwo.ca

Education

• Ph.D. University of Waterloo
• M.A. University of Waterloo
• B.A. King's University College at Western University
• B.A. Dongbei University of Finance and Economics

Teaching

• Econometrics

Research

• Functional data analysis
• Econometric theory
• Applied econometrics

WORKING PAPERS AND WORK IN PROGRESS

• Historical-time functional linear model and its inference with cross-sectional dependence
• A martingale transformation approach of specification test under weak instrumental variables (with Tao Chen and Gautam Tripathi).
• Environmental provisions in trade agreements and globalization: A theoretical and empirical investigation (with Natalia Bezmaternykh and Paul Missios).
• Deep neural network empowered two-stage regression with a non-linear first stage (with Tao Chen and Wenzuo Xu).
• Bias-adjusted inference with unobserved confounding (with Tao Chen and Wenzuo Xu).
• A generalized functional dynamic factor model (with Tao Chen and Jiawen Xu).
• Fast variational Bayesian inference for correlated survival data: an application to invasive mechanical ventilation duration analysis (with Chengqian Xian, Felipe Rodrigues, Camila de Souza, and Wenqing He).
• VO2max in high-altitude populations: An exploratory study using censored semi-/non-parametric approaches (with Tao Chen, Chen Yu, and others).

Selected Publications

• Tian, R., Xu, J., Feng, H., & McFarlane, A. (2024). A maximum entropy bootstrap approach to financial development and economic growth in China. Economic Systems, 101219. https://www.sciencedirect.com/science/article/pii/S0939362524000414
• Xian, C., de Souza, C. P., He, W., Rodrigues, F. F., & Tian, R. (2024). Variational Bayesian analysis of survival data using a log-logistic accelerated failure time model. Stat Comput 34, 67. https://doi.org/10.1007/s11222-023-10365-6
• Chen, T., Li, Y., & Tian, R. (2023). A functional data approach for continuous-time analysis subject to modeling discrepancy under infill asymptotics. Mathematics, 11(20), 4386. https://www.mdpi.com/2227-7390/11/20/4386
• Guo, Z., Tian, R., Xu, W., Yip, D., Radyk, M., Santos, F. B., Yip, A., Chen, T., & Tang, X. S. (2022). Highly accurate heart failure classification using carbon nanotube thin film biosensors and machine learning assisted data analysis. Biosensors and Bioelectronics: X, 12, 100187. https://www.sciencedirect.com/science/article/pii/S2590137022000814
• Chen, T., Liu, H., Tian, R., Gan, R., Xu, W., Zhang, T., &Wang, J. (2022). Artificial intelligence-assisted niacin skin ush screening in early psychosis identification and prediction. General Psychiatry, 35(2). https://gpsych.bmj.com/content/35/2/e100753
• Chen, T., DeJuan, J., & Tian, R. (2018). Distributions of GDP across versions of the Penn World Tables: A functional data analysis approach. Economics Letters, 170, 179-184. https://www.sciencedirect.com/science/article/pii/S0165176518302179