兰姆及其所著《麦克马洪线》

本文对英国学者兰姆的生平和学术生涯做了一个较为详细的梳理,在此基础上介绍了其著作《麦克马洪线:1904-1914年印度、中国和西藏关系史研究》,认为这是一部研究中印关系,特别是中印边界问题的经典著作。深入的分析、缜密的考证,以及比较客观的叙述,展现出作者严谨的治学态度。与西方大多数学者不同的是,兰姆在书中用事实有力地驳斥了印度政府妄图继承英帝国遗产的观点,提出了许多值得参考的看法。同时,也指出了该书存在的不足之处。     

医疗需求与中国医疗费用增长——基于城乡老年医疗支出差异的视角

在人口老龄化和老年医疗支出城乡差异凸显的背景下,中国医疗费用增长部分源于合理的健康需求。利用中国营养与健康调查1991—2011年的八轮数据,构造出生组跟踪样本,分别考察城乡居民医疗支出的年龄效应,估算城乡老年医疗需求导致的费用上涨,可以发现:城市居民的人均医疗支出随年龄显著增加,但农村居民的人均医疗支出随年龄增长的趋势并不明显。而忽略出生组效应,会低估城乡老年医疗支出的差距。城乡老年医疗支出差距缩小,将导致医疗费用在2010—2030年年均实际增长约5.2%。在控制医疗总费用上涨的同时,医疗保险制度需根据老年医疗需求,调整医疗资源配置结构。     

行业系统性风险的动态特征及其影响因素

现代经济主体间网络关联性越来越强,风险很容易在不同行业间扩散,因此有效识别并分析系统性风险是防范金融危机的关键步骤。基于条件风险价值(CoVaR)和边际期望损失(MES)两个指标,对巨潮行业指数系统性风险的静态和动态特征进行了研究。结果发现,各行业间系统性风险的相关性较强,动态特征显示2009年年初和2016年3月为系统性风险的两个峰值;从分行业来看,材料行业的系统性风险最高,而消费和医药行业的系统性风险最低。采用动态面板模型分析影响行业系统性风险的市场面因素发现,短期涨幅较高、长期涨幅较低及流动性较充分的行业,其系统性风险往往更低。因此,应加强对系统性风险较高行业的监管力度,建立好金融防火墙,防止外部金融风险的过度传染;同时应加强对各行业的实时监控,尤其是关注短期暴涨暴跌及流动性充分与否的监控。     

Testing equality of two normal covariance matrices with monotone missing data

Abstract

The problem of testing equality of two multivariate normal covariance matrices is considered. Assuming that the incomplete data are of monotone pattern, a quantity similar to the Likelihood Ratio Test Statistic is proposed. A satisfactory approximation to the distribution of the quantity is derived. Hypothesis testing based on the approximate distribution is outlined. The merits of the test are investigated using Monte Carlo simulation. Monte Carlo studies indicate that the test is very satisfactory even for moderately small samples. The proposed methods are illustrated using an example.     

非光滑复杂网络的混沌同步

通过广义哈密顿系统和观测器方法研究了一类非光滑复杂网络混沌系统的同步控制问题,消除了非光滑项,得到了光滑的误差系统,利用Lyapunov稳定性理论得到了误差系统渐近稳定的充分条件.     

Integrating Operational and Organizational Aspects in Interdependent Infrastructure Network Recovery

Managing risk in infrastructure systems implies dealing with interdependent physical networks and their relationships with the natural and societal contexts. Computational tools are often used to support operational decisions aimed at improving resilience, whereas economics‐related tools tend to be used to address broader societal and policy issues in infrastructure management. We propose an optimization‐based framework for infrastructure resilience analysis that incorporates organizational and socioeconomic aspects into operational problems, allowing to understand relationships between decisions at the policy level (e.g., regulation) and the technical level (e.g., optimal infrastructure restoration). We focus on three issues that arise when integrating such levels. First, optimal restoration strategies driven by financial and operational factors evolve differently compared to those driven by socioeconomic and humanitarian factors. Second, regulatory aspects have a significant impact on recovery dynamics (e.g., effective recovery is most challenging in societies with weak institutions and regulation, where individual interests may compromise societal well‐being). And third, the decision space (i.e., available actions) in postdisaster phases is strongly determined by predisaster decisions (e.g., resource allocation). The proposed optimization framework addresses these issues by using: (1) parametric analyses to test the influence of operational and socioeconomic factors on optimization outcomes, (2) regulatory constraints to model and assess the cost and benefit (for a variety of actors) of enforcing specific policy‐related conditions for the recovery process, and (3) sensitivity analyses to capture the effect of predisaster decisions on recovery. We illustrate our methodology with an example regarding the recovery of interdependent water, power, and gas networks in Shelby County, TN (USA), with exposure to natural hazards.     

Cross‐Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in disease‐specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and self‐efficacy (i.e., control). The 2015–2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved cross‐sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (March–May 2016) and one just after the first cases of local transmission (July–August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and self‐efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.     

基于评价理论的APEC领导人宣言分析

2005年到2014年的APEC领导人宣言中的评价资源以借言为主，正面评价突出，其中鉴赏资源丰富，语势较强，立场分明。这些既体现出对话的和谐，又表明了领导人的决心和信心。2014年的领导人宣言的特点是亚太国家成果众多且认可度更高，特别鼓励区域内，以及政府与私营企业的战略性合作。