嫩模现象：一种新兴青年文化

嫩模现象是个横空出世的新兴青年文化现象，亦是香港普及文化的重要一课。讨论嫩模现象的由来，以及在众声喧哗中隐含的各种文化政治，例如名人概念、青年概念、女性身体等，能检视社会主流论述对此等文化概念的意义转变和规训等。     

The Resilient Survivor—A Student Social Worker's Journey on Placement

This paper represents the continuation of my ‘personal and professional journey’ from social work student to social work practitioner focusing on my first Practice Learning Opportunity (PLO). Recognising the potential impact of childhood sexual abuse (CSA) in a classroom environment is as important as the potential impact on actual practice learning and practice. This is salient in the real world of social work practice as the potential misuse of a painful childhood experience has greater ramifications. Utilising the ideas and assumptions of social constructionism (including context and multivocality) the significance of silence from social work educators shall be examined in relation to self-disclosure as a means of aiding PLO learning and practice. This paper will also focus on the concept of critical reflection and its significance in exploring the transferability of a childhood experience such as CSA and personal and professional dilemmas regarding self-disclosure. This paper concludes by highlighting areas for consideration for both students and social work educators and conveys an important message regarding the importance of communication between students and social work educators.     

美国BIT范本的环境政策考量与变迁及其对中国的启示

美国从1981年启用第一个BIT范本,之后历经数次修订,形成不同版本。其中的环境保护条款从无到有、从简到繁,2012年版本对环境保护又有大力强化。虽然环境例外条款具有法律形态,但因其为缔约方保留环境规制的空间,没有消极影响,其他环境条款尤其专门环境条款则只具有政策形态,对缔约方只有倡导和督促作用,因而也不具有负面意义。基于此,对于中美BIT谈判,中国应该持有像实践WTO规则一样的心态,研究它、接受它,为投身国际实践走出第一步,为将来参与更大范围的规则制定做好准备。     

固定效应部分线性变系数面板模型的快速有效估计

本文将最小二乘支持向量机(LSSVM) 和二次推断函数法(QIF) 相结合，为个体内具有相关结构的固定效应部分线性变系数面板模型提供了一种新的快速估计方法；在一定的正则条件下，论证了参数估计量的渐近正态性和非参数估计量的收敛速度；采用Monte Carlo模拟考察了估计方法在有限样本下的表现并将估计技术应用于现实数据分析。该方法不仅保证了估计的有效性和统计推断力，而且程序运行速度得到较大幅度提升。     

Institutional voids,international learning effort and internationalization of emerging market new ventures

Much of the existing scholarly works portray institutional voids (IVs) in emerging economies as impeding forces against the development of new ventures. However, little attention has been paid to how such voids generate positive outcomes in emerging market new ventures. Drawing on the institutional theory, we propose IVs as crucial enablers of new venture internationalization. In addition, we investigate both how and when IVs enhance the degree to which new ventures internationalize by examining international learning effort (ILE) as a mediator and two domestic market environmental factors (i.e., environmental dynamism and competitive intensity) as important contingencies. We test our moderated mediation model using primary data gathered from 211 new ventures from Ghana. We found that ILE mediates the relationship between IVs and new venture internationalization and that both environmental dynamism and competitive intensity moderate the indirect relationship between home-country IVs and new venture internationalization. We discuss the theoretical and practical implications of this study.     

Testing for Serial Independence: Beyond the Portmanteau Approach

Portmanteau tests are typically used to test serial independence even if, by construction, they are generally powerful only in presence of pairwise dependence between lagged variables. In this article, we present a simple statistic defining a new serial independence test, which is able to detect more general forms of dependence. In particular, differently from the Portmanteau tests, the resulting test is powerful also under a dependent process characterized by pairwise independence. A diagram, based on p-values from the proposed test, is introduced to investigate serial dependence. Finally, the effectiveness of the proposal is evaluated in a simulation study and with an application on financial data. Both show that the new test, used in synergy with the existing ones, helps in the identification of the true data-generating process. Supplementary materials for this article are available online.     

Control Chart for Monitoring Autocorrelated Process with Multiple Exogenous Inputs

We propose to use AR-Sieve Bootstrap in the construction of a control chart of an autocorrelated process influenced by multiple exogenous inputs. The control charts are compared with Exponentially Weighted Moving Average (EWMA) control chart through a simulation study. AR-Sieve bootstrap control limits are narrower than EWMA control limits. While the proposed method yields a higher rate of false alarms, it is quick in detecting even minimal structural changes.     

空气污染治理与公众健康———来自“大气十条”政策的证据

为探究《大气污染防治行动计划》 (以下简称“大气十条”)的健康效应,本文基于中国健康与营养调查(CHNS)数据及省级面板数据,利用基于多项Logit模型的双重差分法(Logit-DID),从微观与宏观两个维度考察“大气十条”政策的健康改善效应及其传导机制,并进一步通过异质性分析探讨环境健康不平等的内在原因 研究发现:“大气十条”实施带来显著的健康效应,该政策不仅能有效控制与空气污染高度相关疾病的发病率和死亡占比,还能够间接降低受空气污染影响较小的疾病病情。其作用机理主要通过控制PM2.5浓度改善公众健康,同时该政策对二氧化硫(SO2)、氮氧化物、烟(粉)尘等其 他污染物浓度的下降起到了协同作用。进一步分析显示环境福利不公平的现象依然存在,“大气十条”政 策显著降低了疾病高发人群的发病率,且对女性、城镇居民和低、高年龄段等疾病高发人群的健康影响更显著。本文为政府构建环境健康公平发展路径,推进“健康中国”战略提供了经验证据和政策借鉴。     

Sparse group lasso for multiclass functional logistic regression models

Sparsity-inducing penalties are useful tools for variable selection and are also effective for regression problems where the data are functions. We consider the problem of selecting not only variables but also decision boundaries in multiclass logistic regression models for functional data, using sparse regularization. The parameters of the functional logistic regression model are estimated in the framework of the penalized likelihood method with the sparse group lasso-type penalty, and then tuning parameters for the model are selected using the model selection criterion. The effectiveness of the proposed method is investigated through simulation studies and the analysis of a gene expression data set.     

An m-estimation-based model selection criterion with a data-oriented penalty

In Wu and Zen (1999), a linear model selection procedure based on M-estimation is proposed, which includes many classical model selection criteria as its special cases, and it is shown that the selection procedure is strongly consistent for a variety of penalty functions. In this paper, we will investigate its small sample performances for some choices of fixed penalty functions. It can be seen that the performance varies with the choice of the penalty. Hence, a randomized penalty based on observed data is proposed, which preserves the consistency property and provides improved performance over a fixed choice of penalty functions.