地区金融发展与经济增长的空间效应研究

基于空间杜宾模型,本文对我国31个省市和地区2000-2014年金融发展与经济增长相关数据的实证分析,研究地区金融发展与经济增长的空间效应,同时考察经济开放下金融发展对经济增长影响的变化。研究发现：我国各省市和地区经济增长和金融发展均存在显著空间相关性;金融规模与经济增长存在正向相关关系,金融结构和金融相关比率分别与经济增长存在负向相关关系;经济开放水平的提高对我国金融积极作用的发挥反而带来抑制作用;金融发展对经济增长影响在不同经济增长阶段存在显著差异性;同样区域特征凸显,“丝绸之路经济带”和“长江经济带”两区域内金融规模系数显著大于全国水平,彰显了区域发展战略中金融规模的重要作用。     

国外城市雨洪管理再认识及其启示

针对近年中国城市雨洪灾害频发、灾害危害严重,以及雨洪管理理念和方法仍在摸索阶段的现实,文章通过横向对比发达国家雨洪管理过程、阶段,探索总结了国外雨洪管理体系的阶段性与多元化、发展历程的过程性和演进性、治理模式的综合性、空间特征的地域趋同性特征,并系统剖析其形成的深层城市发展原因,结合中国的城市实际情况,提出了未来城市雨洪管理可发展方向的思考,认为未来在多尺度水文条件下的雨洪灾害形成内因探索、复杂环境下多要素集成分析、多过程连续的雨洪灾害发生动力机制等方面是研究发展方向之一.     

区域旅游业碳排放的时空差异——以山东省为例

碳排放问题是区域旅游业发展不可忽视的环境问题之一。根据相关统计数据,按照"自下而上"分析法对2000-2015年山东省旅游业碳排放进行定量估算,并采用系统聚类法将山东省旅游业碳排放划分为高、中、低三类碳排放区域,具体剖析山东省旅游业碳排放的区域差异。结果表明:（1）碳排放总量、游客人均碳排放量和碳排放强度是衡量区域旅游业碳排放的重要指标。2000-2015年山东省旅游业碳排放总量持续增长,而游客人均碳排放量和旅游业碳排放强度则逐年下降,旅游业节能减排取得一定成效。（2）区域旅游业三大部门碳排放存在明显差异,旅游交通是区域旅游业碳排放的主要来源,旅游活动碳排放增长速度最快,而旅游住宿碳排放波动性较大。2000-2015年山东省旅游业累积碳排放总量为4 764.05万吨,其中,旅游交通、旅游住宿、旅游活动三大部门占比分别为66.52%、25.80%、7.68%。（3）区域旅游业碳排放水平空间差异显著。从空间分布上看,山东省旅游业碳排放总体上呈现东高西低、北高南低的特征,旅游业碳排放总量呈现出东部沿海 > 鲁中地区 > 鲁西地区,游客人均碳排放量和旅游业碳排放强度则是东部沿海 > 鲁西地区 > 鲁中地区;从碳排放指标上看,山东省大多数地市位于中高旅游业碳排放的行列,东部沿海是旅游业碳排放的主要来源区。     

中国省域碳排放的空间特征及影响因素

通过核密度分布和莫兰指数对中国2000—2015年30省份碳排放强度的动态趋势及集聚特征进行测度,并利用空间杜宾模型对其主要影响因素进行分析。结果显示:（1）中国30省份碳排放强度呈下降趋势,新常态以来低碳步伐加快;（2）碳排放强度的空间集聚性具有高水平集中、低水平集聚特征,空间溢出效应不断增强;（3）本省经济规模、产业结构对本省碳排放强度具有显著的正向影响,专利产出具有显著的负向影响;相邻省份的外商投资规模及能源消费结构变化对本省碳排放具有显著的空间溢出作用。因此,未来中国加快产业结构调整幅度、优化相邻省份间的产业空间布局以及大力发展绿色技术进步是中国促进区域低碳转型的主要方向,同时生态城镇化以及继续改善外商直接投资质量也是减排潜力因子,省域间的减排空间溢出效果不容忽视。     

Spatial Data Usage,Spatial Thinking and Spatial Knowledge Generation: The Case of Planning Practitioners in Arequipa,Peru

Spatial thinking and spatial knowledge generation in decision-making are still not mature fields of study in planning research, despite these being crucial elements in addressing the issues of the twenty-first-century city. This article contributes to their understanding by exploring their interrelationships with spatial data usage. Through storylines, it analyzes the arguments that planning practitioners offer in support of infrastructure-led decisions in Arequipa (Peru), before and after spatial data usage. The article concludes that spatial data usage improve spatial thinking to different extents, yet suggests aligning spatial data generation and the inclusion of GIS-based spatial analyses with the spatial knowledge needed by routine planning practice.     

扁平超宽连续箱梁桥空间受力性能分析与研究

扁平超宽箱梁桥由于具有较大的宽跨比，其受力性能呈现明显的空间效应，通常的单梁模型计算已不能满足设计的精度要求，主要体现在宽箱梁各腹板纵向受力的差异性以及明显的剪力滞效应，同时由于大宽跨比使得横向预应力的作用不仅增加了顶板的压应力，也使得整体箱梁截面下缘出现拉应力，造成边腹板底部纵向裂缝，这些都给宽箱梁的设计带来了不利。因此为研究宽箱梁的空间效应，本文运用ANSYS有限元软件建立了全桥实体模型，计算了各腹板纵向受力差异及剪力滞效应，以及横向预应力对箱梁横向受力的影响，得到了一些有益的结论，为设计人员提供一定的参考。     

Prediction intervals for future Weibull residual data

In reliability theory, risk analysis, renewal processes and actuarial studies, the residual lifetimes data play an important essential role in studying the conditional tail of the lifetime data. In this paper, based on some observed ordered residual Weibull data, we introduce different prediction methods for obtaining prediction intervals (PIs) of future residual lifetimes including likelihood, Wald, moments, parametric bootstrap, and highest conditional methods. Monte Carlo simulations are performed to compare the performances of the so obtained PIs and one data analysis is performed for illustration purposes.     

Hazard rate ordering of the second-order statistics from multiple-outlier PHR samples

In this paper, we compare the hazard rate functions of the second-order statistics arising from two sets of independent multiple-outlier proportional hazard rates (PHR) samples. It is proved that the submajorization order between the sample size vectors together with the supermajorization order between the hazard rate vectors imply the hazard rate ordering between the corresponding second-order statistics from multiple-outlier PHR random variables. The results established here provide theoretical guidance both for the winner's price for the bid in the second-price reverse auction in auction theory and fail-safe system design in reliability. Some numerical examples are also provided for illustration.     

The precision of regression-type estimator for incremental cost–effectiveness ratio

The estimation of incremental cost–effectiveness ratio (ICER) has received increasing attention recently. It is expressed in terms of the ratio of the change in costs of a therapeutic intervention to the change in the effects of the intervention. Despite the intuitive interpretation of ICER as an additional cost per additional benefit unit, it is a challenge to estimate the distribution of a ratio of two stochastically dependent distributions. A vast literature regarding the statistical methods of ICER has developed in the past two decades, but none of these methods provide an unbiased estimator. Here, to obtain the unbiased estimator of the cost–effectiveness ratio (CER), the zero intercept of the bivariate normal regression is assumed. In equal sample sizes, the Iman–Conover algorithm is applied to construct the desired variance–covariance matrix of two random bivariate samples, and the estimation then follows the same approach as CER to obtain the unbiased estimator of ICER. The bootstrapping method with the Iman–Conover algorithm is employed for unequal sample sizes. Simulation experiments are conducted to evaluate the proposed method. The regression-type estimator performs overwhelmingly better than the sample mean estimator in terms of mean squared error in all cases.