Are there electoral cycles of emigration? An empirical investigation based on European data

Economic literature suggests that economic factors and the availability of amenities act as determinants of migration choices together with socio‐demographic factors. Migration has also been found to be the consequence of political instability. This article argues that specific political events, i.e., democratic elections, may be linked to migration flows. By using European data over the 1999‐2012 time period, our system GMM estimations reveal that there is an emigration political cycle across European democracies and across the young democracies of Central and Eastern European countries. We observe that regular elections tend to diminish emigration ratios, whereas endogenous elections have the opposite effect. These results suggest special challenges for governments and oppositions, which are also discussed.     

Risk Assessment for Hospital-Acquired Diseases: A Risk-Theory Approach

We introduce a new approach to hospital-acquired disease risk assessment from public health databases. In a spirit similar to actuarial risk theory, we define an adjustment coefficient that can quantify the risk associated with a hospital department, allowing comparisons of similar departments. The adjustment coefficient characterizes the tail of the distribution of the total patient length of stay in a department before the first disease event occurs. We show that this coefficient is the solution of a Lundberg-like equation, and we provide a nonparametric estimation procedure for this measure, based on a Cramér-Lundberg approximation for the tail of the distribution. Using simulations, we provide evidence of the robustness of the approximation to various individual risk models. In addition, we illustrate the relevance of this approach by evaluating the risk associated with a standard patient safety indicator in 20 hospitals of southeastern France.     

An Empirical Process View of Inverse Regression

A common approach taken in high‐dimensional regression analysis is sliced inverse regression, which separates the range of the response variable into non‐overlapping regions, called ‘slices’. Asymptotic results are usually shown assuming that the slices are fixed, while in practice, estimators are computed with random slices containing the same number of observations. Based on empirical process theory, we present a unified theoretical framework to study these techniques, and revisit popular inverse regression estimators. Furthermore, we introduce a bootstrap methodology that reproduces the laws of Cramér–von Mises test statistics of interest to model dimension, effects of specified covariates and whether or not a sliced inverse regression estimator is appropriate. Finally, we investigate the accuracy of different bootstrap procedures by means of simulations.     

The Comparison of Performances of Widely Used Cointegration Tests

The aim of this study is to compare performances of commonly cointegration tests used in literature in terms of their empirical power and type I error probabilty for various sample sizes. As a result of the study, it has been found that some tests are not appropriate in testing cointegration in terms of empirical power and type I error probability. As a result of simulation study, λ_max test for any values of ρ and sample sizes have been found most appropriate test in conclusion.     

New Shrinkage Parameters for the Liu-type Logistic Estimators

The binary logistic regression is a widely used statistical method when the dependent variable has two categories. In most of the situations of logistic regression, independent variables are collinear which is called the multicollinearity problem. It is known that multicollinearity affects the variance of maximum likelihood estimator (MLE) negatively. Therefore, this article introduces new shrinkage parameters for the Liu-type estimators in the Liu (2003) in the logistic regression model defined by Huang (2012) in order to decrease the variance and overcome the problem of multicollinearity. A Monte Carlo study is designed to show the goodness of the proposed estimators over MLE in the sense of mean squared error (MSE) and mean absolute error (MAE). Moreover, a real data case is given to demonstrate the advantages of the new shrinkage parameters.     

通俗唱法的声音训练研究

通俗唱法是多种歌唱艺术形式中的一种形式,有其鲜明的个性特征。围绕个性特征对通俗唱法呼吸状态、发声位置,以及歌唱的运动状态等进行有针对性的科学训练;发展歌唱者在精神上、技巧上和心理生理上对声音的控制能力;形成歌唱时发声器官有规律、有调节的稳定性运动;使歌唱者对通俗歌曲的演唱和声音表现由一般演唱状态进入到艺术演唱境界,并在实践中逐步形成对通俗唱法的理性认识。     

船舶反弯扭螺旋桨水力特性的数值模拟与分析

运用计算流体力学方法(CFD)对船舶反弯扭螺旋桨的水力特性进行数值模拟计算,获得了螺旋桨的推力系数、扭矩系数及敞水效率等水力特性参数,与试验结果进行了比较,两者吻合良好.模拟计算提供了详细的三维流场分布,可对反弯扭桨叶的工作特性和叶梢涡、尾涡及气蚀的分布状态进行深入的分析.在叶面邻近区域采用层叠式的半结构网格以适应边界层的计算要求,在边界层外的流动区域采用非结构网格,取得了较高的计算精度.