后危机视野下福建省经济格局演变及其影响机制

［目的］后危机时代是目前我国各地区经济发展面对的一个巨大变量，也是近年来区域经济发展关注的焦点话题。［方法］选取福建省县域经济的5项指标作为解释变量，利用探索性空间分析方法和地理加权回归模型，对2010—2015年福建省县域经济格局及其驱动机制进行探讨。［结果］（1）总体上看，福建省经济空间格局变化较小，呈现东南高西北低的态势，重心向福州、莆田地区转移，省内发展均质化与极化现象并存；（2）产业结构调整与城镇化水平提升主导省内经济重心在东西方向上的移动，两者的空间格局具有相似性；（3）创新投入与金融零售业的变化主导了经济重心南北向的移动，其与各市县的经济基础和产业调整政策密切相关。［结论］在后危机时代福建省需根据市场特征推进区域协同发展、实现产业结构调整、促进区域共同富裕； 地方经济政策应与自身经济发展特征相适应，实现区域经济可持续发展。     

Closeness matters. Spatial autocorrelation and relationship between socioeconomic indices and distance to departmental Colombian capitals

Socioeconomic indices that developing economies use to combat poverty may show a limited picture of all the variables related to the problem. This study analyzes spatial autocorrelation and clusters of three socioeconomic indices—living conditions, multidimensional poverty, and unsatisfied basic needs—in Colombia to explore the relation of the identified clusters with their physical distance from departmental capitals. Using a local index of spatial autocorrelation, it evaluates spatial patterns and the clustering of socioeconomic indices. Correlation analysis tests the relation between clusters and their distance from departmental capitals in three departments. The spatial patterns of indices in Colombia correspond to the model of economic development in the country and reveal the regions where socioeconomic characteristics form clusters of desirable/undesirable conditions and departments where the distance from main cities may be seen as a condition for a higher quality of life.     

村级尺度耕地产能空间分异及其影响因子分析

[目的]通过探究耕地产能空间分异规律与影响因子,识别地区粮食生产关键制约因素,提升高标准基本农田建设的针对性和建设效果。[方法]采用空间自相关模型刻画了村级尺度耕地产能空间分异规律,对比分析了线性回归模型和地理加权回归模型在耕地产能影响因子识别的效果,并依此划分产能提升类型区。[结果](1)海伦市耕地产能呈现中西部高北部偏低的态势,且具有较强的空间自相关特征。(2)海伦市耕地产能与黑土层厚度、出现障碍层深度、耕作距离、田块状况和质地等变量显著相关,且均呈正相关,但在空间上表现出不同程度的异质性。(3)基于地理加权回归模型的耕地产能影响因子,提出了产能保持区、耕作条件改良区、质地改良区、障碍层改良区和保护性耕作区5类耕地产能提升类型区。[结论]文章所采用的基于村级尺度耕地产能及其空间分异因素模型相关研究,能够较好揭示村级耕地产能空间分布特点、空间自相关性特征及影响因子分布特征,基于此所划分的耕地产能提升类型区较已有研究对耕地分类管理具有更精准的支撑作用。     

Distribution of residual autocorrelations for multiplicative seasonal ARMA models with uncorrelated but nonindependent error terms

In this paper, we consider portmanteau tests for testing the adequacy of multiplicative seasonal autoregressive moving‐average models under the assumption that the errors are uncorrelated but not necessarily independent. We relax the standard independence assumption on the error terms in order to extend the range of applications of the seasonal autoregressive moving‐average models. We study the asymptotic distributions of residual and normalized residual empirical autocovariances and autocorrelations under weak assumptions on noise. We establish the asymptotic behavior of the proposed statistics. A set of Monte Carlo experiments and an application to monthly mean total sunspot number are presented.     

Identifying the internal structure evolution of urban built-up land sprawl (UBLS) from a composite structure perspective: A case study of the Beijing metropolitan area,China

Differences in the internal composite structure during urban built-up land sprawl (UBLS) will generate different effects, and thus, a city’s spatial structure has important bearings on urban sustainability. This study investigates the spatial and temporal characteristics of the internal structure and allocation relationship of UBLS using multivariate spatial correlation and the Weaver-Tomas composite coefficient based on site data of granted built-up land parcels. Moreover, the composite structure evolution process of UBLS and its driving mechanism are examined in this study. The results reveal that the amount structure of the three types of UBLS (i.e. industrial land sprawl, residential land sprawl and commercial land sprawl) tended to be balanced during the study period. Following the transformation and upgrade of the urban industry structure, the overall composite structure of UBLS ranged from single residential land-use structure (Res.) to industrial-residential land-use structure (Ind.-Res.) In the early period of land marketization, the marketization land granting mechanism caused low spatial correlation between the various types of UBLS and a single composite structure, i.e. Res., single commercial land-use structure (Com.), and residential-commercial land-use structure (Res.-Com.). Subsequently, a dual-driving force including the market economy and government interventions caused a relatively high degree of spatial correlation and a multiple composite structure, i.e. Ind.-Res. and industrial-residential-commercial land-use structure (Ind.-Res.-Com.). However, the evolution characteristics of the composite structure in various regions illustrate some problems, such as the spatial isomorphism phenomenon of the composite structure and the dislocation of urban built-up land allocation. The urban internal built-up land spatial layout pattern is the embodiment of two dominant driving forces, the market and the government, interacting with each other according to natural and socioeconomic conditions. Therefore, we suggest that it is necessary to reform the future urban built-up land granting mechanism based on market guidance, and the composite structure of UBLS should be adjusted according to the regional function. The government should reinforce the macro-control of land-use planning for the dispersed granted land parcels so as to optimize the urban land-use structure.     

基于不同Logistic模型的土地利用格局模拟对比研究——以湖北省宣恩县和咸丰县为例

模拟土地利用空间格局分布规律对合理利用土地资源、制定土地利用规划、协调土地与经济、环境的关系具有十分重要的意义。土地利用格局存在空间异质性,对比不同地区格局特征规律对加深土地利用格局的认识具有重要意义。以邻接的湖北省宣恩县和咸丰县为研究对象,通过对比基于局地因子、自相关因子和邻域因子的3种Logistic模型的模拟参数的一致性和异质性来对比研究两地的格局分布规律。实验与分析结果表明,宣恩县和咸丰县的土地利用格局特征存在共同的驱动因子和聚集效应,具有共性;不同模型的模拟结果表明驱动因子在作用方向,大小方面存在差异,邻域因子在邻域尺度上表现出不同特征。研究结果对加深理解不同地区的土地利用分布格局特征的差异性,促进区域土地利用的规划、土地资源的合理开发与可持续发展战略的顺利实施具有一定的参考价值。     

The influence of neighborhood environment and household travel interactions on school travel behavior: an exploration using geographically-weighted models

Professional and popular interest in active school transportation (walking and cycling) is matched by an emerging literature on this topic. This paper explores school travel behavior of 11-year old children in Toronto, Canada. In particular, the effects of the neighborhood environment and caregiver-child travel interactions on travel mode choice were studied. Results indicate that the built environment near both home and school locations was associated with the odds of walking. However, predicted built environment effects were less accurate in some neighborhoods. Availability of adults at the time of school travel likely encouraged driving. School transportation interventions that broadly consider school and neighborhood-oriented policies and enable independent mobility may increase walking rates. Presence of spatial autocorrelation in the prevalence of walking suggests that more research is required to understand inter-household similarities in behaviors that are spatially structured.     

中国物流产业的空间集聚及成因分析

本文采用区位熵和空间自相关方法分析了我国物流产业集聚的时空演变特征。研究表明,我国物流业发展的空间分布存在显著的区域差异,物流增加值区位熵波动性显著,物流业集聚程度存在较强的空间自相关和空间异质性,总体上呈现集聚化发展倾向。借助主成分回归分析探讨我国物流产业集聚的影响因素,发现这7个因素对我国物流业集聚均为正向促进作用,影响程度由高到低依次为基础设施建设、经济发展水平、消费水平、工业发展水平、对外开放程度、人力资本和区位因素,以上7个要素每增长1％,相应的物流业增加值就依次上升0.205％、0.194％、0.192％、0.187％、0.145％、0.057％和0.019％。     

中国土地利用碳排放及其空间关联

基于研究单元全部土地利用类型数据,采用碳排放计算模型,估算了中国31个省区1990-2008年的土地利用碳排放强度,揭示其时空演变规律,并利用空间自相关方法,探讨了中国省级尺度土地利用碳排放强度的空间关联特征.结果表明:①1990-2008年,中国土地利用碳排放量从9.67×108t持续上升至32.37× 108t.建设用地是主要的碳排放来源,其碳排放量占总碳排放量的97.83％以上.林地是主要的碳汇,其碳排放量占总碳排放量的90％以上.②受经济发展水平和地形差异的影响,碳排放强度空间差异显著,重度碳排放区域集中分布在东部、北部沿海地区,轻度碳排放区域集中分布在西北、西南地区.③全局自相关Moran'sI值从1990年的0.1558持续上升至2008年的0.2734,说明中国土地利用碳排放强度在省级尺度上具有明显的空间集聚特征,且集聚程度不断增强.④集聚中心和孤立点的空间转移存在较强的规律性.⑤局域自相关分析表明,中国土地利用碳排放强度表现出十分明显的局部空间差异.碳排放强度高值集聚区和低值集聚区均表现出较强的空间锁定和路径依赖特征,体现为高值集聚区向沿海集中,低值集聚区向内陆迁移.     

Public information arrival and volatility persistence in financial markets

This paper explores the relationship between daily market volatility and the arrival of public information in four different financial markets. Public information is measured as the daily number of economic news headlines, divided in six categories of news. Statistical analysis of the news data suggests the presence of particular seasonality effects, as well as a strong degree of autocorrelation. Over the period 1994–1998, significant effects of specific news categories on the volatility of US stocks, treasury bills, bonds and dollar were detected. However, the effects – in size and duration – vary by news category and by financial market. It is demonstrated that most of the volatility persistence, as observed by GARCH models, tends to disappear when news is included in the conditional variance equation.