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。     

Global Governance,neoliberalism and national responses: The case of Bangladesh’s ready‐made garment (RMG) sector

This article on the ready‐made garment (RMG) sector of Bangladesh shows how over‐reliance on foreign capital for development financing and deregulated investment—a hallmark of neoliberal economic arrangements—undermines the incorporation of SDGs’ and INGOs’ equity principles, contributing to biased policy responses yielding unequal outcomes. The article cautions that while countries prioritize economic growth over social and environmental nourishment and continue to adopt neoliberal economic policies to promote economic growth, inequity is unavoidable, if not inevitable. Thus, the way forward may be to shift the focus of ‘development’ from the economy to society, to building ‘good societies’ where institutions and strategies, including those that contribute to economic growth, are organized such that these complement not compromise the evolution of such societies.     

Global adjustment to US disengagement from the world trading system

US trade policy in the Trump administration is protectionist, raising tariffs outside of WTO rules, threatening trade wars, withdrawing from existing trade agreements, and negotiating new bilateral trade deals rather than free trade agreements. The reaction of the rest of the world has been to support the WTO rules-based trading system and to pursue new and expanded regional trade agreements that do not include the US. The result may be US disengagement from the world trading system, with countries diverting trade around the US. We use a global computable general equilibrium (CGE) model to analyze changes in trade and production patterns for a variety of scenarios, including US trade wars. We find that adjustment to US disengagement is feasible—the changes in trade shares as countries divert trade are modest and achievable, with very little impact on the volume of global trade. If the US engages in trade wars with major partners, the best response for other trade partners is to sit out the trade war, accept higher US tariffs, and gain markets from global trade diversion around the US. Finally, because of indirect effects, widespread tariffs fail to benefit the protected sectors—a fallacy of composition in a protectionist trade policy.     

Bayesian bridge-randomized penalized quantile regression estimation for linear regression model with AP(q) perturbation

Bridge penalized regression has many desirable statistical properties such as unbiasedness, sparseness as well as ‘oracle’. In Bayesian framework, bridge regularized penalty can be implemented based on generalized Gaussian distribution (GGD) prior. In this paper, we incorporate Bayesian bridge-randomized penalty and its adaptive version into the quantile regression (QR) models with autoregressive perturbations to conduct Bayesian penalization estimation. Employing the working likelihood of the asymmetric Laplace distribution (ALD) perturbations, the Bayesian joint hierarchical models are established. Based on the mixture representations of the ALD and generalized Gaussian distribution (GGD) priors of coefficients, the hybrid algorithms based on Gibbs sampler and Metropolis-Hasting sampler are provided to conduct fully Bayesian posterior estimation. Finally, the proposed Bayesian procedures are illustrated by some simulation examples and applied to a real data application of the electricity consumption.     

Complementary person-supervisor fit: An investigation of supplies-values (S-V) fit,leader-member exchange (LMX) and work outcomes

By applying the supplies-values (S-V) fit approach from the complementary person-environment (P-E) fit literature to the leader-employee perspective, and drawing upon social exchange theory, we examine how fulfillment of different work values is related to Leader-Member Exchange (LMX) and work outcomes. First, polynomial regression analyses combined with response surface analysis of data collected at two time points (N = 316) showed that LMX (Time 2) was higher the more the leader fulfills the employee's work values (Time 1). Second, LMX (Time 2) was higher when leader supplies (Time 1) and employee work values (Time 1) were both high than when both were low. Third, analyses of data from a sub-sample of matched leader-employee dyads (N = 140), showed that LMX (Time 2) played a mediating role on the relation between S-V fit (Time 1) and work outcomes (Time 2). Specifically, we found eight out of 10 relationships between S-V fit (Time 1) and leader-rated task performance and OCB (Time 2) to be fully mediated by LMX (Time 2). LMX (Time 2) partially mediated the relation between S-V fit (Time 1) and job satisfaction (Time 2) as only two out of five relationships were fully mediated.     

A Tiered Framework for Risk‐Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children's Study (NCS)

A challenge for large‐scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co‐occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure‐relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new “Tiered Exposure Ranking” (TiER) framework, developed to support various aspects of risk‐relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both “discovery‐driven” and “hypothesis‐driven” analyses. “Tier 1” applications focus on “exposomic” pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk‐relevant exposure metrics for populations and individuals. In this article, “tier 1” applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A “tier 2” application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk‐relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.     

On the enumeration of rectangular (0, 1)-matrices

The construction and enumeration of (0, 1)-matrices with given line-sums is described for the rectangular cases often encountered in applications. Improved approximations are provided for the number of such matrices. Some new enumeration results for semi-regular bipartite graphs are included, and the related category of the quasi-semiregular bipartite graphs is recognized. The range of certain elements of products of a (0, I)-matrix is considered as a function of the line-sums. This, in turn, is related to the range in the numbers of interchanges available. Improvements in statistical practice that come from these constructions and enumerations are described.     

语义场理论对科技术语翻译的启示从——“水资源管理”一词的英汉互译谈起

科技术语在不同语言之间的翻译是一个复杂的语义匹配过程，如何在考虑相关术语使用现状的基础上将新产生的科技术语准确翻译为其它语言是科技工作者和术语研究者关注的重要问题。以语义场理论为分析框架，通过分析以"水资源管理"及其相关术语为代表的英汉互译，结果发现：不同科技术语在同一语义场所涵盖的语义范围将会随着相关研究深化带来的术语界定细化而发生相应的动态变化；新兴科技术语的翻译要充分考虑其所在语义场其它相关科技术语的翻译先例和使用现状所带来的影响，在翻译准确性和解读便利性之间做出适当的平衡。这是造成"水资源管理"及相关术语英汉互译处理极为复杂的重要原因之一，需要科技翻译者在工作实践中多加注意。     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.