欧盟一体化过程给我们哪些启示

珠江三角洲经济一体化涉及到不同城市和地区之间的利益分配,涉及到区域资源共享、产业合作、市场开拓、基础设施合作等诸多领域的问题,是我国区域合作与发展中的一个新尝试.也将是东、中、西部经济互联互动、协调发展的新突破,有可能成为中国区域经济发展的一个新范式.欧盟区域经济一体化是世界上公认的比较成功的发展模式.虽然欧盟经济一体化是在一个超国家的政治格局下进行的.而珠三角一体化是在一个主权国家政治下开展的,但作为"区域经济一体化",两者之间存在着诸多相似之处.欧盟在一体化过程中实施的产业政策、区域政策、基金政策、贸易政策等各项政策和具体做法都有很多值得学习和借鉴的成功经验.     

詹姆斯·威尔逊与美国早期联邦制的演进

美国早期联邦制的演进是各种联邦制观点相互竞争和谈判的过程。詹姆斯.威尔逊的联邦制观点是其中最重要的一种。从美国独立战争前的政治辩论到1787年联邦宪法的制定和批准,威尔逊以他对政治理论和实践的深刻认识,阐释了整体与部分的关系及各自的权力和职责,从而在美国早期联邦制的演进过程中,扮演了重要的角色。     

公共政策传递过程中科层损耗的博弈分析及启示

在公共政策传递过程中,公共政策制定者和地方执行者之间的互动构成了一种博弈关系.当公共政策制定者的效用函数与执行者的效用函数发生偏差时,个人价值最大化动机将导致执行者对公共政策作出符合其自身利益的理解并予以修正式执行,从而造成公共政策地方科层损耗,导致公共政策实际社会效益低于预期效益.本文在对地方科层损耗形成机制及其效应进行经济学分析的基础上,构建博弈模型深入阐释,并提出了相应的政策建议.该分析突出了对公共政策传递过程的研究,弥补了相关领域研究的不足,为提升公共政策执行效率、确保公共政策预期社会效益提供必要的理论支持.     

壮族原生型民间宗教结构及其特点

壮族的宗教包括原始宗教、原生型民间宗教和外来创生型宗教三个层次,其中原生型民间宗教--麽教和师公教具有代表性.它们的内部结构比较完整,基本具备了宗教的构成元素.与世界各种创生型宗教相比,仅在无地区性和全民性宗教领袖、无绝对权威主神的不同.壮族宗教的特点主要有8个方面,其中多种宗教神灵和谐共处,为国内外少见.     

英汉壮思维器官跨语言文化比较

思维是人类具有的共同能力之一。不同的民族运用不同的身体器官来思维和表达情感并形成自己独特的民族文化。对这些文化差异的认知,我们可以通过语言层面做具体的分析比较获得。就思维器官跨语言文化比较角度而言,英语民族倾向于用脑智"mind"(脑),汉族倾向于用心智"heart"(心),而壮族则倾向于用喉智"hoz"(throat喉咙,即用喉咙思维和表达情感)。通过跨语言文化比较,可以加深我们对文化差异及文化多样性的认识和理解,更好地进行跨文化交际活动。     

t-Type corrected-loss estimation for error-in-variable model

In this article, we consider a linear model in which the covariates are measured with errors. We propose a t-type corrected-loss estimation of the covariate effect, when the measurement error follows the Laplace distribution. The proposed estimator is asymptotically normal. In practical studies, some outliers that diminish the robustness of the estimation occur. Simulation studies show that the estimators are resistant to vertical outliers and an application of 6-minute walk test is presented to show that the proposed method performs well.     

Testing homogeneity in semiparametric mixture case–control models

Parametric and semiparametric mixture models have been widely used in applications from many areas, and it is often of interest to test the homogeneity in these models. However, hypothesis testing is non standard due to the fact that several regularity conditions do not hold under the null hypothesis. We consider a semiparametric mixture case–control model, in the sense that the density ratio of two distributions is assumed to be of an exponential form, while the baseline density is unspecified. This model was first considered by Qin and Liang (2011 Qin, J., Liang, K.Y. (2011). Hypothesis testing in a mixture case–control model. Biometrics 67(1):182–198.[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], biometrics), and they proposed a modified score statistic for testing homogeneity. In this article, we consider alternative testing procedures based on supremum statistics, which could improve power against certain types of alternatives. We demonstrate the connection and comparison among the proposed and existing approaches. In addition, we provide a unified theoretical justification of the supremum test and other existing test statistics from an empirical likelihood perspective. The finite-sample performance of the supremum test statistics was evaluated in simulation studies.     

A new confidence interval in measurement error model with the reliability ratio known

For the slope parameter of the measurement error model with the reliability ratio known, this article constructs a fiducial generalized confidence interval (FGCI) which is proved to have correct asymptotic coverage. Simulation results demonstrate that the FGCI often outperforms the existing intervals in terms of empirical coverage probability, average interval length, and false parameter coverage rate. Two examples are also provided to illustrate our approach.     

Parallel and interacting stochastic approximation annealing algorithms for global optimisation

We present the parallel and interacting stochastic approximation annealing (PISAA) algorithm, a stochastic simulation procedure for global optimisation, that extends and improves the stochastic approximation annealing (SAA) by using population Monte Carlo ideas. The efficiency of standard SAA algorithm crucially depends on its self-adjusting mechanism which presents stability issues in high dimensional or rugged optimisation problems. The proposed algorithm involves simulating a population of SAA chains that interact each other in a manner that significantly improves the stability of the self-adjusting mechanism and the search for the global optimum in the sampling space, as well as it inherits SAA desired convergence properties when a square-root cooling schedule is used. It can be implemented in parallel computing environments in order to mitigate the computational overhead. As a result, PISAA can address complex optimisation problems that it would be difficult for SAA to satisfactory address. We demonstrate the good performance of the proposed algorithm on challenging applications including Bayesian network learning and protein folding. Our numerical comparisons suggest that PISAA outperforms the simulated annealing, stochastic approximation annealing, and annealing evolutionary stochastic approximation Monte Carlo.