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。     

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.     

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.     

四川盆地中三叠世盐盆分布与演化特征研究

四川盆地卤水分布广泛，资源丰富, 早为世人所瞩目，中三叠统雷口坡组是四川盆地最早开采天然气和盐卤的层系之一。根据盆地雷口坡组大量钻井资料研究表明，盆地雷口坡组主要成盐期分别为雷三2 期和雷四2 期，在盆地东部和南部由于受到古隆起的影响，盐岩地层已被剥蚀难以保存，现今盐岩主要分布在开江古隆起和泸州古隆起的西部以及天井山古隆起的南部（华蓥山以西—龙门山以东的川西—川中地区）。印支运动对盆地雷口坡组盐岩在平面的迁移起着十分重要的作用，根据不同时期盐岩统计数据看，两期盐盆在平面上具有向西迁移、叠加的特征，其中川中的GS1 井就钻遇了这两期的盐岩。     

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。     

Feminized Forestry: The Promises and Pitfalls of Change in a Masculine Organization

The gendering of forestry as a distinctly masculine profession has led to a wide range of negative outcomes, including legal actions concerning discrimination, poor public perceptions and poor environmental records. Forestry organizations have addressed these concerns by attempting to increase the number of women in the profession. These efforts have been largely ineffective. Using the case of community‐based forestry, I argue that when we begin to consider not only women but also normatively feminine values as agents of change, our understanding of the profession of forestry may be rejuvenated.