Quasi-minimax estimation in the partial linear model

This article discusses the minimax estimator in partial linear model y = Zβ + f + ε under ellipsoidal restrictions on the parameter space and quadratic loss function. The superiority of the minimax estimator over the two-step estimator is studied in the mean squared error matrix criterion.     

New Ridge Regression Estimator in Semiparametric Regression Models

In the context of ridge regression, the estimation of shrinkage parameter plays an important role in analyzing data. Many efforts have been put to develop the computation of risk function in different full-parametric ridge regression approaches using eigenvalues and then bringing an efficient estimator of shrinkage parameter based on them. In this respect, the estimation of shrinkage parameter is neglected for semiparametric regression model. Not restricted, but the main focus of this approach is to develop necessary tools for computing the risk function of regression coefficient based on the eigenvalues of design matrix in semiparametric regression. For this purpose the differencing methodology is applied. We also propose a new estimator for shrinkage parameter which is of harmonic type mean of ridge estimators. It is shown that this estimator performs better than all the existing ones for the regression coefficient. For our proposal, a Monte Carlo simulation study and a real dataset analysis related to housing attributes are conducted to illustrate the efficiency of shrinkage estimators based on the minimum risk and mean squared error criteria.     

Imposing and Testing for Shape Restrictions in Flexible Parametric Models

In many economic models, theory restricts the shape of functions, such as monotonicity or curvature conditions. This article reviews and presents a framework for constrained estimation and inference to test for shape conditions in parametric models. We show that “regional” shape-restricting estimators have important advantages in terms of model fit and flexibility (as opposed to standard “local” or “global” shape-restricting estimators). In our empirical illustration, this is the first article to impose and test for all shape restrictions required by economic theory simultaneously in the “Berndt and Wood” data. We find that this dataset is consistent with “duality theory,” whereas previous studies have found violations of economic theory. We discuss policy consequences for key parameters, such as whether energy and capital are complements or substitutes.     

空间面板杜宾模型的Bootstrap Wald-COMFAC检验研究

将共同因子约束(COMFAC)的Wald检验问题引入到空间面板模型中,讨论空间面板杜宾模型与空间面板误差模型的识别问题。蒙特卡洛模拟表明:在有限样本下,基于渐近临界值的Wald检验有着良好的检验功效,但存在着较为严重的尺度扭曲。进一步采用残差Bootstrap方法,在不损失检验功效的前提下,能够显著地降低检验的尺度扭曲。因此,残差Bootstrap方法是更为有效的检验方法。     

网络反腐中政府官员隐私权保护的适度边界

网络反腐是互联网时代反腐倡廉的新方式,它一方面强化了对政府官员个人权力的监督制约,另一方面也增加了侵犯政府官员民事权利特别是隐私权的法律风险.在网络反腐中,保护政府官员的隐私权不仅有利于维护人格尊严,而且有利于化解隐私权与知情权及监督权的冲突.但基于政府官员的特定身份,其隐私权保护应定位于公共利益除外标准,坚持适度保护原则,合理划定保护范围.     

身份政治与民族国家认同焦虑——对香港国际学校的一种解读

以香港的身份政治为背景,探讨香港国际学校是如何在一种奇特的身份政治中运作,以摆脱民族国家认同焦虑。     

Weighted Stochastic Restricted Estimation in Linear Measurement Error Models

This article discusses the consistent estimation of the parameters in a linear measurement error model when stochastic linear restrictions on regression coefficients are available. We propose some methodologies to obtain the consistent estimation when either the covariance matrix of the measurement errors or the reliability matrix of independent variables is known. Their finite- and large-sample properties are derived with not necessarily normal errors. A Monte Carlo simulation is carried out to study the the finite properties of the estimators.     

浅析翻译主体的能动性和受动性

在翻译过程中，译者作为翻译的主体，在尊重翻译对象的前提下，必须突破客观受动因素的制约，充分发挥主观能动性。译者一方面要对这些客观制约因素有清楚的理解和认识，同时又要善于在客观中发挥主体性，在制约中发挥能动性，真正做到有思想、有创新，延续原作的生命，搭建文化沟通的桥梁。     

阿坝州红色旅游资源的优势及其开发的制约因素和策略探析

阿坝州是国家重点培育的十二个"重点红色旅游区"之一,红色旅游资源丰富,开发其红色旅游资源对于打造当地藏羌文化走廊,推动地区经济快速发展具有重要意义.为此,文章概述了阿坝州红色旅游的资源优势,分析了开发其红色旅游资源的制约因素,并在此基础上提出了开发其红色旅游资源的策略.