Biography

Prof. Shi is Associate Professor at the Department of Economics. He specializes in econometric theory, with focus on estimation and inference of machine learning methods for economic and financial applications.

Research

• "On LASSO for High Dimensional Predictive Regression," forthcoming, with Ziwei Mei, Journal of Econometrics.

• "Boosted HP Filter Is More General Than You Think," forthcoming, with Ziwei Mei and Peter C.B. Phillips, Journal of Applied Econometrics.

• "L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis," forthcoming, with Liangjun Su and Tian Xie, Review of Economics and Statistics.

• "Forward-Selected Panel Data Approach for Program Evaluation," 2023, with Jingyi Huang, Journal of Econometrics, 234, 512-535.

• "Culling the Herd of Moments with Penalized Empirical Likelihood," 2023, with Jinyuan Chang and Jia Zhang, Journal of Business & Economic Statistics, 41, 791-805.

• "Transformed Estimation for Panel Interactive Effects Models," 2022, with Cheng Hsiao and Qiankun Zhou, Journal of Business & Economic Statistics, 40(4), 1831-1848.

• “Measuring Social Interaction Effects When Instruments Are Weak,” 2022, with Stephen L. Ross, Journal of Business & Economic Statistics, 40:3, 995-1006.

• "On LASSO for Predictive Regression," 2022, with Ji Hyung Lee and Zhan Gao, Journal of Econometrics, 229(2), 322-340.

• "Boosting: Why You Can Use the HP Filter," 2021, with Peter Phillips, International Economic Review, 62(2), 521-570.

• "Structural Estimation of Behavioral Heterogeneity," 2018, with Huanhuan Zheng, Journal of Applied Econometrics, 33(5), 690-707.

• "Identifying Latent Structures in Panel Data", 2016, with Liangjun Su and Peter Phillips, Econometrica, 84(6), 2215-2264.

• "Econometric Estimation with High-Dimensional Moment Equalities", 2016, Journal of Econometrics, 195, 104-119.

Courses Taught