Zhewen Pan
Biographic Data
| ID | 3934684 |
|---|---|
| NAME | Zhewen Pan |
| GIVEN NAMES | Zhewen |
| FAMILY NAME | Pan |
| SIGNATURE | PAN Z |
| AFFILIATIONS | Lingnan College, Sun Yat-sen University, Guangzhou, China |
| ORCID | 0009-0004-7426-6976 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Marginal Treatment Effects in the Absence of Instrumental Variables
We propose a method for defining, identifying, and estimating the marginal treatment effect (MTE) without imposing the instrumental variable (IV) assumptions of independence, exclusion, and separability (or monotonicity). Under a new definition of the MTE based on reduced‐form treatment error that is statistically independent of the covariates, we find that the relationship between the MTE and standard treatment parameters holds in the absence of…
On Semiparametric Estimation of the Intercept of the Sample Selection Model
This paper presents a novel perspective on the identification at infinity as identification at the boundary, for the intercept of the sample selection model, via a transformation of the selection index. This perspective suggests generalisations of estimation at infinity to kernel regression estimation at the boundary and further to local linear estimation at the boundary. The proposed kernel‐type estimators with an estimated transformation are pr…
Early-life access to primary healthcare and educational attainment
Penalized Pairwise Difference Estimation for a High-Dimensional Censored Regression Model
High-dimensional data are nowadays readily available and increasingly common in various fields of empirical economics. This article considers estimation and model selection for a high-dimensional censored linear regression model. We combine l1-penalization method with the ideas of pairwise difference and propose an l1-penalized pairwise difference least absolute deviations (LAD) estimator. Estimation consistency and model selection consistency of…
Semiparametric Estimation of a Censored Regression Model Subject to Nonparametric Sample Selection
This study proposes a semiparametric estimation method for a censored regression model subject to nonparametric sample selection without the exclusion restriction. Consistency and asymptotic normality of the proposed estimator are established under mild regularity conditions. A Monte Carlo simulation study indicates that the estimator performs well in various designs and outperforms parametric maximum likelihood estimators. An empirical applicati…
No prominent works on this page.
Semiparametric Estimation of a Censored Regression Model Subject to Nonparametric Sample Selection
This study proposes a semiparametric estimation method for a censored regression model subject to nonparametric sample selection without the exclusion restriction. Consistency and asymptotic normality of the proposed estimator are established under mild regularity conditions. A Monte Carlo simulation study indicates that the estimator performs well in various designs and outperforms parametric maximum likelihood estimators. An empirical applicati…
Penalized Pairwise Difference Estimation for a High-Dimensional Censored Regression Model
High-dimensional data are nowadays readily available and increasingly common in various fields of empirical economics. This article considers estimation and model selection for a high-dimensional censored linear regression model. We combine l1-penalization method with the ideas of pairwise difference and propose an l1-penalized pairwise difference least absolute deviations (LAD) estimator. Estimation consistency and model selection consistency of…
Early-life access to primary healthcare and educational attainment
Marginal Treatment Effects in the Absence of Instrumental Variables
We propose a method for defining, identifying, and estimating the marginal treatment effect (MTE) without imposing the instrumental variable (IV) assumptions of independence, exclusion, and separability (or monotonicity). Under a new definition of the MTE based on reduced‐form treatment error that is statistically independent of the covariates, we find that the relationship between the MTE and standard treatment parameters holds in the absence of…
On Semiparametric Estimation of the Intercept of the Sample Selection Model
This paper presents a novel perspective on the identification at infinity as identification at the boundary, for the intercept of the sample selection model, via a transformation of the selection index. This perspective suggests generalisations of estimation at infinity to kernel regression estimation at the boundary and further to local linear estimation at the boundary. The proposed kernel‐type estimators with an estimated transformation are pr…
Statistical Methods and Inference (4 works) · Estimator (3 works) · Statistical Methods and Bayesian Inference (3 works) · Advanced Statistical Methods and Models (2 works) · Mathematics (2 works) · Monte Carlo method (2 works) · Semiparametric regression (2 works) · Statistics (2 works) · Advanced Causal Inference Techniques (1 work) · Algorithm (1 work)