Papers by topics

Machine learning theory

Panel data

• Zhentao Shi, Liangjun Su and Tian Xie (2023): “L2-Relaxation: With Applications to Forecast Combination and Portfolio Analysis,” Review of Economics and Statistics.

• Zhentao Shi and #Jingyi Huang (2023): “Forward-Selected Panel Data Approach for Program Evaluation,” Journal of Econometrics, 234, 512-535.

• Liangjun Su, Zhentao Shi and Peter Phillips (2016): “Identifying Latent Structures in Panel Data,” Econometrica, 84(6), 2215-2264.

Cross-sectional data

• Jinyuan Chang, Zhentao Shi and Jia Zhang (2022): “Culling the Herd of Moments with Penalized Empirical Likelihood,” Journal of Business & Economic Statistics, 41, 791-805.

• Zhentao Shi (2016): “Econometric Estimation with High-Dimensional Moment Equalities,” Journal of Econometrics, 195, 104-119.

• Zhentao Shi (2016): “Estimation of Sparse Structural Parameters with Many Endogenous Variables,” Econometric Reviews, 35(8-10): 1582-1608.

Time series

• “On LASSO for High Dimensional Predictive Regression”, with #Ziwei Mei, 2022.

• Ji Hyung Lee, Zhentao Shi, and #Zhan Gao (2022): “On LASSO for Predictive Regression,” Journal of Econometrics, 229(2), 322-340.

• Peter Phillips and Zhentao Shi (2021): “Boosting: Why You Can Use the HP Filter,” International Economic Review, 62(2), 521-570.

• “The Boosted HP Filter Is More General Than You Might Think,” with #Ziwei Mei and Peter C.B. Phillips, 2022.

Computation

• #Zhan Gao and Zhentao Shi (2021): “Implementing Convex Optimization in R: Two Econometric Examples,” Computational Economics, 58, 1127-1135.

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General econometric theory

• “Implicit Nickell Bias in Panel Local Projection,” with #Ziwei Mei and Liugang Sheng, 2023.

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

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

• Zhentao Shi and Huanhuan Zheng (2018): “Structural Estimation of Behavioral Heterogeneity,” Journal of Applied Econometrics, 33(5), 690-707.

• “A Structural Network Pairwise Regression Model with Unobservable Heterogeneity,” with Xi Chen and #Yapeng Zheng, 2023.

• James Chu, Liping Lu and Zhentao Shi (2009): “Pitfalls in Market Timing Test,” Economic Letters, 103(3), 123–126.

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Empirical Applications

Machine learning

• “Forecast Combination in Cryptocurrency Realized Volatility”, with Yue Qiu, Yifan Wang and Tian Xie, 2022.

• “Asset Prices and China’s Inflation Forecast: Based on Individual Stock Return and Machine Learning Algorithm,” with Naijing Huang, Yuqing Qi and Jie Liu, 2022

• Wei Lin, Zhentao Shi, #Yishu Wang and #Ting Hin Yan (2023): “Unfolding Beijing in a Hedonic Way,” Computational Economics, 61, 317–340.

• Ka Yan Cheng, Naijing Huang and Zhentao Shi (2021): “Survay-Based Forecasting: To Average or Not To Average,” in Vladik Kreinovich, Songsak Sriboonchitta, Woraphon Yamaka (eds.), Studies in Computational Intelligence: Behavioral Predictive Modeling in Economics, vol. 897, pp 87-104, Springer-Verlag.

Finance

• Zhentao Shi, Yuefei Zhang, and Yaogguang Chen (2006): [in Chinese] “A Comparative Research on the Efficiency of China Mainland and Hong Kong Stock Markets,” Journal of Financial Research (金融研究), 6, 33-40.

• Zhentao Shi and Liuyong Yang (2004): [in Chinese] “An Analysis of Long-run Gold Price Determinants,” Journal of Statistical Research (统计研究), 6 (2), 21-24.