Zhentao Shi
Biographic Data
| ID | 8880928 |
|---|---|
| NAME | Zhentao Shi |
| GIVEN NAMES | Zhentao |
| FAMILY NAME | Shi |
| SIGNATURE | SHI Z |
| AFFILIATIONS | Department of Economics, The Chinese University of Hong Kong, Sha Tin, New Territories, Hong Kong SAR, China |
| ORCID | 0000-0002-7289-2840 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
L 2 -Relaxation
We propose l2-relaxation, which is a novel convex optimization problem, to tackle a forecast combination with many forecasts or a minimum variance portfolio with many assets. l2-relaxation minimizes the squared Euclidean norm of the weight vector subject to a set of relaxed linear inequalities to balance the bias and variance. It delivers optimality with approximately equal within-group weights when latent block equicorrelation patterns dominate …
The boosted Hodrick‐Prescott filter is more general than you might think
The global financial crisis and Covid‐19 recession have renewed discussion concerning trend‐cycle discovery in macroeconomic data, and boosting has recently upgraded the popular Hodrick‐Prescott filter to a modern machine learning device suited to data‐rich and rapid computational environments. This paper extends boosting's trend determination capability to higher order integrated processes and time series with roots that are local to unity. The …
Culling the Herd of Moments with Penalized Empirical Likelihood
Models defined by moment conditions are at the center of structural econometric estimation, but economic theory is mostly agnostic about moment selection. While a large pool of valid moments can potentially improve estimation efficiency, in the meantime a few invalid ones may undermine consistency. This article investigates the empirical likelihood estimation of these moment-defined models in high-dimensional settings. We propose a penalized empi…
Transformed Estimation for Panel Interactive Effects Models
We propose a transformed estimator for the slope coefficients of panel models with interactive effects. The transformed estimation method does not require the prior knowledge of the dimension of factor structure. It is consistent and asymptotically normally distributed under fairly general conditions when N is fixed and T→∞ or T is fixed and N→∞, or when both N and T are large and NT→a≠0<∞. Moreover, because the transformation is equivalent to ag…
Measuring Social Interaction Effects When Instruments Are Weak
Studies that distinguish between exogenous and endogenous peer effects are relatively rare. To separate these effects, De Giorgi, Pellizzari, and Redaelli exploited partially overlapping peer groups where attributes of a student’s peers in one group provide instrumental variables (IV) for endogenous effects in another group. We apply this identification strategy to data from a period of transition at a Chinese university: dormitory roommate assig…
No prominent works on this page.
Transformed Estimation for Panel Interactive Effects Models
We propose a transformed estimator for the slope coefficients of panel models with interactive effects. The transformed estimation method does not require the prior knowledge of the dimension of factor structure. It is consistent and asymptotically normally distributed under fairly general conditions when N is fixed and T→∞ or T is fixed and N→∞, or when both N and T are large and NT→a≠0<∞. Moreover, because the transformation is equivalent to ag…
Measuring Social Interaction Effects When Instruments Are Weak
Studies that distinguish between exogenous and endogenous peer effects are relatively rare. To separate these effects, De Giorgi, Pellizzari, and Redaelli exploited partially overlapping peer groups where attributes of a student’s peers in one group provide instrumental variables (IV) for endogenous effects in another group. We apply this identification strategy to data from a period of transition at a Chinese university: dormitory roommate assig…
Culling the Herd of Moments with Penalized Empirical Likelihood
Models defined by moment conditions are at the center of structural econometric estimation, but economic theory is mostly agnostic about moment selection. While a large pool of valid moments can potentially improve estimation efficiency, in the meantime a few invalid ones may undermine consistency. This article investigates the empirical likelihood estimation of these moment-defined models in high-dimensional settings. We propose a penalized empi…
The boosted Hodrick‐Prescott filter is more general than you might think
The global financial crisis and Covid‐19 recession have renewed discussion concerning trend‐cycle discovery in macroeconomic data, and boosting has recently upgraded the popular Hodrick‐Prescott filter to a modern machine learning device suited to data‐rich and rapid computational environments. This paper extends boosting's trend determination capability to higher order integrated processes and time series with roots that are local to unity. The …
L 2 -Relaxation
We propose l2-relaxation, which is a novel convex optimization problem, to tackle a forecast combination with many forecasts or a minimum variance portfolio with many assets. l2-relaxation minimizes the squared Euclidean norm of the weight vector subject to a set of relaxed linear inequalities to balance the bias and variance. It delivers optimality with approximately equal within-group weights when latent block equicorrelation patterns dominate …
Econometrics (5 works) · Economics (5 works) · Computer Science (4 works) · Mathematics (3 works) · Monetary Policy and Economic Impact (3 works) · Statistics (3 works) · Applied Mathematics (2 works) · Asymptotic analysis (2 works) · Estimation (2 works) · Estimator (2 works)