出口产品质量与技能溢价：理论机制及中国证据

本文基于出口产品“质”的视角，理论阐释并实证检验出口产品质量对技能溢价的影响及其作用机制。研究发现：出口产品质量提高显著提升了劳动力技能溢价，这种提升效应在高技术行业更为明显；出口产品质量升级主要通过增加对高技能劳动力相对需求、改善企业利润和绩效等机制提升技能溢价，但出口产品质量影响技能溢价的产品价格机制未得到验证；技能溢价与高技能劳动力供给之间呈倒“U”型关系。因此，为防止出口产品质量升级加剧技能工资不平等，需要采取加强人力资本投资、增加高素质劳动力供给、完善与高质量外贸发展相适应的相对公平的收入分配政策等措施。     

政治关联如何影响社会组织有效性？——组织自主性的中介作用和制度支持的调节作用

社会组织领域的政治关联现象日益显著，但政治关联究竟如何影响社会组织有效性，其隐藏的作用机制又是什么？这是学术界尚未明晰的重要课题。针对254家社会组织的问卷调查发现，社会组织政治关联会正向影响组织有效性，这一关系受到组织自主性的中介作用影响。更进一步的研究显示，制度支持能调节上述中介关系。具体而言，当制度支持水平较高时，这一效应将会增强；当制度支持水平较低时，政治关联通过组织自主性间接影响组织有效性的效应就会减弱。这一发现，一方面增进了我们对社会组织政治关联的理解，另一方面也为提升社会组织有效性的理论和实践提供了重要启示。     

Variable selection and estimation for high-dimensional spatial autoregressive models

Spatial regression models are important tools for many scientific disciplines including economics, business, and social science. In this article, we investigate postmodel selection estimators that apply least squares estimation to the model selected by penalized estimation in high-dimensional regression models with spatial autoregressive errors. We show that by separating the model selection and estimation process, the postmodel selection estimator performs at least as well as the simultaneous variable selection and estimation method in terms of the rate of convergence. Moreover, under perfect model selection, the ℓ₂ rate of convergence is the oracle rate of $\sqrt{s/n}$, compared with the convergence rate of $\text{◂√▸}\sqrt{s\log p/n}$ in the general case. Here, n is the sample size and p, s are the model dimension and number of significant covariates, respectively. We further provide the convergence rate of the estimation error in the form of $\sup$ norm, and ideally the rate can reach as fast as $\text{◂√▸}\sqrt{\log s/n}$.     

Estimation of the marginal expected shortfall under asymptotic independence

We study the asymptotic behavior of the marginal expected shortfall when the two random variables are asymptotic independent but positively associated, which is modeled by the so-called tail dependent coefficient. We construct an estimator of the marginal expected shortfall, which is shown to be asymptotically normal. The finite sample performance of the estimator is investigated in a small simulation study. The method is also applied to estimate the expected amount of rainfall at a weather station given that there is a once every 100 years rainfall at another weather station nearby.     

Inferences for a Partially Varying Coefficient Model With Endogenous Regressors

In this article, we propose a new class of semiparametric instrumental variable models with partially varying coefficients, in which the structural function has a partially linear form and the impact of endogenous structural variables can vary over different levels of some exogenous variables. We propose a three-step estimation procedure to estimate both functional and constant coefficients. The consistency and asymptotic normality of these proposed estimators are established. Moreover, a generalized F-test is developed to test whether the functional coefficients are of particular parametric forms with some underlying economic intuitions, and furthermore, the limiting distribution of the proposed generalized F-test statistic under the null hypothesis is established. Finally, we illustrate the finite sample performance of our approach with simulations and two real data examples in economics.     

A regularized variable selection procedure in additive hazards model with stratified case-cohort design

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.     

Reweighted estimators for additive hazard model with censoring indicators missing at random

Survival data with missing censoring indicators are frequently encountered in biomedical studies. In this paper, we consider statistical inference for this type of data under the additive hazard model. Reweighting methods based on simple and augmented inverse probability are proposed. The asymptotic properties of the proposed estimators are established. Furthermore, we provide a numerical technique for checking adequacy of the fitted model with missing censoring indicators. Our simulation results show that the proposed estimators outperform the simple and augmented inverse probability weighted estimators without reweighting. The proposed methods are illustrated by analyzing a dataset from a breast cancer study.     

复杂岩性地区岩性识别与储层预测

中国陆相地层岩性成分较为复杂,岩性波阻抗值常呈多极分布。水动能强度的急剧变化、高频率的水进水退等沉积背景造成了薄互层广泛发育的特点。储层间干涉现象普遍存在,直接影响到地震岩性解释的精度。针对复杂岩性地区岩性–波阻抗关系复杂的特点,系统分析了造成传统地震储层预测方法解释误差的原因。根据复杂岩性的地球物理响应特点,选取对区分复杂岩性敏感的测井参数。同时,将90° 相位化地震数据作为测井参数反演的相对波阻抗约束数据体。研究结果表明,该方法对复杂岩性进行了有效的区分,达到了精细描述复杂岩性地区储层空间发育及平面展布特点的目的。     

复杂山地高密度宽线地震采集技术及应用效果

通过多年持续攻关,塔里木盆地山地地震采集技术取得了长足进展,但仍有许多勘探难题需进一步解决。阐述了针对高大山体区地震资料的低信噪比问题和高陡复杂构造成像问题而提出的一种攻关采集方法。该方法以宽线采集技术为基础,在增强压噪能力、提高静校正精度、改善陡倾角地层成像效果等方面采取了针对性技术措施。这些技术措施的的应用大幅度改善了地震剖面的成像质量。