试析民间金融风险与应对策略

作为一种自发式的融资方式,民间金融在规范化、公开化过程中,其风险灾害可能对社会的稳定、金融体系的安全以及国家宏观经济的调控产生负面影响;民间金融发展中的主要风险及权重排序依次为内在制度风险、借贷利率风险、借贷“条件风险”和国家“政策风险”,必须按照风险管理的要求,采用风险回避、降低、转移、留存等不同策略来加强风险应对。以促进民间金融的可持续发展。     

项目制研究的现状与新路径

项目制作为一种新的国家治理体制,在中国经济与社会发展中发挥着日益深广的影响力。文献考察发现,国内研究围绕五个主要议题展开,研究成果较集中于近六年内;国外研究也有一定基础。既有研究尚存在两方面突出问题：一是研究视角有缺失,偏重宏观层面和政府视角而忽视了基层村庄社会的回应;二是研究议题失均衡,对项目制负面效应发生机理和防范机制研究还很薄弱。“村庄回应”是项目制研究值得重视的一条新路径,以此路径切入,可探寻“项目进村”的实践逻辑与问题成因,是有利于找到优化基层治理格局、提升项目制实践成效并防范“项目进村”负面效应的有效方法。     

基于时频分析的裂纹转子碰摩故障特征研究

为研究转子系统耦合故障特性,采用有限元方法建立了含有横向裂纹、转静碰摩的非线性转子动力学模型。首先研究了不同转速下裂纹、碰摩单一故障下转子系统的振动响应,其次研究了两种故障耦合情况下系统的振动响应特征。采用波形图、FFT谱图、瞬时频率和Hilbert-Huang时频谱(HHS)相结合的方法对故障转子振动信号进行了分析。分析结果表明:运用多种时频分析相结合的方法可以较为全面地了解转子的故障特征,裂纹转子在1/5、1/3临界转速时会发生较为明显的5X、3X谐波,且裂纹的产生会导致响应幅值增大,从而引起更为严重的碰摩。      

Tweeting about emergency: A semantic network analysis of government organizations’ social media messaging during Hurricane Harvey

While social media like Twitter have been increasingly adopted by public-sector organizations, it remains less explored as to how government and emergency management (EM) organizations use these platforms to communicate with the public in response to emerging natural disasters. Extending the Situational Crisis Communication Theory (SCCT) to the realm of social media, this study examines the emerging semantic networks from 67 government and EM organizations’ official tweets during Hurricane Harvey over a three-week period. It identifies how multiple crisis response strategies—including instructing information, adjusting information, and bolstering—are constituted of different issues, actions, and organizational actors before, during, and immediately after the disaster event. Results suggest that government agencies use the strategy of instructing information predominantly before and during the disaster, whereas adjusting information and bolstering strategies are utilized more during post-disaster recovery. The study offers theoretical and practical implications of using a semantic network approach to studying organizational crisis responses.     

Missing item imputation for quality-of-life instruments with application to asthma quality-of-life questionnaires

There has been increasing use of quality-of-life (QoL) instruments in drug development. Missing item values often occur in QoL data. A common approach to solve this problem is to impute the missing values before scoring. Several imputation procedures, such as imputing with the most correlated item and imputing with a row/column model or an item response model, have been proposed. We examine these procedures using data from two clinical trials, in which the original asthma quality-of-life questionnaire (AQLQ) and the miniAQLQ were used. We propose two modifications to existing procedures: truncating the imputed values to eliminate outliers and using the proportional odds model as the item response model for imputation. We also propose a novel imputation method based on a semi-parametric beta regression so that the imputed value is always in the correct range and illustrate how this approach can easily be implemented in commonly used statistical software. To compare these approaches, we deleted 5% of item values in the data according to three different missingness mechanisms, imputed them using these approaches and compared the imputed values with the true values. Our comparison showed that the row/column-model-based imputation with truncation generally performed better, whereas our new approach had better performance under a number scenarios.     

On estimating the distribution of data envelopment analysis efficiency scores: an application to nursing homes’ care planning process

Data envelopment analysis (DEA) is a deterministic econometric model for calculating efficiency by using data from an observed set of decision-making units (DMUs). We propose a method for calculating the distribution of efficiency scores. Our framework relies on estimating data from an unobserved set of DMUs. The model provides posterior predictive data for the unobserved DMUs to augment the frontier in the DEA that provides a posterior predictive distribution for the efficiency scores. We explore the method on a multiple-input and multiple-output DEA model. The data for the example are from a comprehensive examination of how nursing homes complete a standardized mandatory assessment of residents.     

Generally weighted moving average control charts with fast initial response features

The generally weighted moving average (GWMA) control chart is an extension model of exponentially weighted moving average (EWMA) control chart. Recently, some approaches have been proposed to modify EWMA charts with fast initial response (FIR) features. We introduce these approaches in GWMA-type charts. Via simulation, various control schemes are designed and then their average run lengths are computed and compared. Based on the overall performance, it is showed that the DGWMA chart is the best choice especially when the shift is moderate, and the GWMA charts provided with additional FIR feature have a good performance only in detecting large shifts during the initial stage.     

Improved randomized response in additive scrambling models

Randomized response models deal with stigmatizing variables appearing in health surveys. Additive and subtractive scrambling in split sample and double response yield unbiased mean and sensitivity estimators of high precision. The split sample method is protective of privacy. The double response method is as protective only conditionally. To achieve the maximum efficiency, the scrambling variables must be similar to each other and the probability of obtaining a true response must be as large as possible. The randomized response procedures yield more efficient estimates of the average total number of classes missed by university students.     

Improved estimation methods for unrelated question randomized response techniques

The randomized response technique (RRT) is an important tool, commonly used to avoid biased answers in survey on sensitive issues by preserving the respondents’ privacy. In this paper, we introduce a data collection method for survey on sensitive issues combining both the unrelated-question RRT and the direct question design. The direct questioning method is utilized to obtain responses to a non sensitive question that is related to the innocuous question from the unrelated-question RRT. These responses serve as additional information that can be used to improve the estimation of the prevalence of the sensitive behavior. Furthermore, we propose two new methods for the estimation of the proportion of respondents possessing the sensitive attribute under a missing data setup. More specifically, we develop the weighted estimator and the weighted conditional likelihood estimator. The performances of our estimators are studied numerically and compared with that of an existing one. Both proposed estimators are more efficient than the Greenberg's estimator. We illustrate our methods using real data from a survey study on illegal use of cable TV service in Taiwan.