中国省际水资源利用效率与空间溢出效应测度

基于省际水足迹和灰色水足迹等的面板数据,本文利用带有考虑和不考虑非期望产出的数据包络分析方法测度了1997-2011 年中国31 个省市区的水资源利用效率;建立基于经济—空间距离函数的空间权重矩阵,探讨水资源利用效率的空间自相关关系;利用绝对β趋同模型验证水资源利用效率增长趋势存在绝对β趋同,考虑和不考虑非期望产出情况下达到1/2 趋同程度的时间分别约为52.6 和5.6 年;运用空间Durbin 计量模型研究了中国省际水资源利用效率的空间溢出效应。研究发现：（1） 考虑和不考虑非期望产出的中国省际水资源利用效率都具有显著的空间自相关性;（2） 考虑和不考虑非期望产出的空间自回归系数ρ分别为0.278 和0.507,且都在1%的水平上显著,说明中国水资源利用效率存在空间溢出效应;（3） 考虑非期望产出情况下中国各省市的教育经费、交通基础设施、工业和农业用水比重因素正向影响水资源利用效率,外商直接投资、万元工业增加值用水量、人均用水量、降水总量因素负向影响水资源利用效率;（4） 不考虑非期望产出情况下中国各省市的劳均GDP因素较大正向显著影响,而交通基础设施和万元工业增加值用水量因素变为不显著影响;（5） 不考虑非期望产出的水资源利用效率测度对中国水资源真实利用情况出现偏差估计及对政策制定产生误导,考虑环境因素到水资源利用效率测度更为合理。     

中国水资源利用效率驱动效应测度及空间驱动类型分析

综合考虑产业用水效率、产业用水结构、经济水平、水资源禀赋及水资源开发利用率5个因素对中国用水效率的影响,基于扩展的Kaya恒等式建立因素分解模型,应用LMDI分解方法对1997~2008年中国用水效率变化进行分解分析,计算各驱动效应因素的相对贡献率,测度它们的影响程度和方向。结果表明:产业用水效率效应和经济水平效应是影响中国用水效率变化的最显著因素。通过计算各驱动效应的绝对贡献率,采用最小方差法将中国31个行政区(港澳台除外)确定为4种空间驱动类型,进而分析用水效率变化驱动效应的分布特点。研究结果对于正确理解中国用水效率的变化与经济发展之间的关系以及产业结构的调整与可持续发展研究具有一定的参考价值。     

云南省旅游经济空间关联及溢出效应测度

为明确云南省旅游协同发展、旅游优质发展表现出来的实际效果如何,以空间面板计量方法为实践指导,从空间外部性的视角对云南省旅游经济空间特征以及溢出效应进行量化评价。结果表明:2006—2018年间较强的空间正相关性和高度的空间集聚性存在于云南省各州市的旅游经济发展过程中;云南省各州市表现出很强的近邻溢出现象,但区域间的旅游经济溢出效应价值并没有完全发挥出来,其中基础设施与旅游经济增长溢出负相关。     

中国干旱灾害评估与空间特征分析(英文)

Based on the monthly precipitation data for the period 1960-2008 from 616 rainfall stations and the phenology data of main grain crops,the spatial characteristics of drought hazard in China were investigated at a 10 km×10 km grid-cell scale using a GIS-based drought hazard assessment model,which was constructed by using 3-month Standard Pre-cipitation Index (SPI).Drought-prone areas and heavy drought centers were also identified in this study.The spatial distribution of drought hazard in China shows apparent east-west dif-ference,with the eastern part of China being far more hazardous than the western part.High hazard areas are common in the eastern and central parts of Inner Mongolian Plateau,the central part of Northeast China Plain,the northern part of Heilongjiang,the southeastern part of Qinghai-Tibet Plateau,the central and southern parts of Loess Plateau,the southern part of North China Plain,the northern and southern parts of Yangtze River Plain,and Yun-nan-Guizhou Plateau.Furthermore,obvious differences in drought hazard were found both within and between different agricultural zonings.     

中国城乡用地集约利用定量测度与影响机理(英文)

Land use issue is an important constraining force to limit economic sustainable development of China. Urban and rural rapid expansion depletes valued land resources under the background of rapid urbanization. An extensive use pattern might cause a serious waste of land resources. The study on influencing mechanism of land intensive use(LIU) in China at the county level is a key tool for effective LIU practice and policy-making. This paper uses OLS model, Spatial Panel Lagged model and Spatial Panel Error model to quantitatively analyze the influencing mechanisms of five class factors and 17 variables supported by GIS(Geographic Information System) and MATLAB. And a comprehensive data set was developed including physical geography and socio-economic information of 2286 counties. Meanwhile, the spatiotemporal pattern of LIU has discussed by means of GIS. The results show that Spatial Panel Data models are slightly superior to OLS model in terms of significance and confidence level. Regression results of these models indicate that industrialization, urbanization, economic development level, location, transportation and policy have significant impact on LIU of counties. The variables of physical geography are less significant than socio-economic variables. An ignored variable of historical factor, however, became the best significant factor. In the future, the LIU at the county level should take advantage of the new situation by enhancing favorable factors and reducing disadvantageous ones, which can be acquired by improving the entire level and quality of industrialization and urbanization. We argued that an efficient and complete land market and operating system should be built to reflect market-oriented activities at the first place, then, differential LIU regulation policies and measurements should be optimized according to regional differences. In the meantime, we should pay close attention to the carrying capacity of local resources and environments when conducting LIU practices.     

中国城市碳排放强度的空间溢出效应及驱动因素探究（英文）

In this study, we adopt kernel density estimation, spatial autocorrelation, spatial Markov chain, and panel quantile regression methods to analyze spatial spillover effects and driving factors of carbon emission intensity in 283 Chinese cities from 1992 to 2013. The following results were obtained.(1) Nuclear density estimation shows that the overall average carbon intensity of cities in China has decreased, with differences gradually narrowing.(2) The spatial autocorrelation Moran's I index indicates significant spatial agglomeration of carbon emission intensity is gradually increasing; however, differences between regions have remained stable.(3) Spatial Markov chain analysis shows a Matthew effect in China's urban carbon emission intensity. In addition, low-intensity and high-intensity cities characteristically maintain their initial state during the transition period. Furthermore, there is a clear "Spatial Spillover" effect in urban carbon emission intensity and there is heterogeneity in the spillover effect in different regional contexts; that is, if a city is near a city with low carbon emission intensity, the carbon emission intensity of the first city has a higher probability of upward transfer, and vice versa.(4) Panel quantile results indicate that in cities with low carbon emission intensity, economic growth, technological progress, and appropriate population density play an important role in reducing emissions. In addition, foreign investment intensity and traffic emissions are the main factors that increase carbon emission intensity. In cities with high carbon intensity, population density is an important emission reduction factor, and technological progress has no significant effect. In contrast, industrial emissions, extensive capital investment, and urban land expansion are the main factors driving the increase in carbon intensity.     

资源禀赋、外部效应与中国油气资源产业的空间地理分布(英文)

本文首先利用空间统计分析工具对我国油气资源产业的空间分布状况和规律进行了考察,然后运用空间计量经济模型对导致油气资源产业空间集聚的影响因素进行了实证检验。检验结果表明,我国油气资源产业发展呈现出产异化的空间分布状况,油气资源产业的上游集中于环鄂尔多斯区域,油气资源产业的下游没有出现空间集聚。而在影响我国油气资源产业空间集聚的因素中,外部效应是促使油气资源产业空间集聚的关键。同时,政府经济政策则是油气资源产业空间集聚的重要影响因素。     

中国陆地海岸线尺度效应研究(英文)

Spatial scale is a fundamental problem in Geography. Scale effect caused by fractal characteristic of coastline becomes a common focus of coastal zone managers and researchers. In this study, based on DEM and remote sensing images, multi-scale continental coastlines of China were extracted and the fractal characteristic was analyzed. The results are shown as follows. (1) The continental coastline of China fits the fractal model, and the fractal dimension is 1.195. (2) The scale effects with fractal dimensions of coastline have significant differences according to uplift and subsidence segments along the continental coastlines of China. (3) The fractal dimension of coastline has significant spatial heterogeneity according to the coastline types. The fractal dimension of sandy coastline located in Luanhe River plain is 1.109. The dimension of muddy coastline located in northern Jiangsu Plain is 1.059, while that of rocky coastline along southeastern Fujian is 1.293. (4) The length of rocky coastline is affected by scale more than that of muddy and sandy coastline. Since coastline is the conjunction of sea, land and air surface, the study of coastline scale effect is one of the scientific bases for the researches on air-sea-land interaction in multi-scales.     

中国能源生态效率的空间格局与空间效应（英文）

Energy eco-efficiency is a concept integrating ecological and economic benefits arising from energy utilization and serves as a measure of efficiency in the energy–environment–economy system. Using the slacks-based measure(SBM) model considering undesirable output, this study first measures the energy eco-efficiency of provinces in China from 1997 to 2012. It then analyzes the spatial distribution and evolution of energy eco-efficiency from three aspects: scale, intensity, and grain of spatial patterns. Finally, it examines the spatial spillover effects and influencing factors of energy eco-efficiency in different provinces by means of a spatial econometric model. The following conclusions are drawn:(1) The overall energy eco-efficiency is relatively low in China, with energy-inefficient regions accounting for about 40%. Guangdong, Hainan and Fujian provinces enjoy the highest energy eco-efficiency, while Ningxia, Gansu, Qinghai, and Xinjiang are representative regions with low efficiency. Thus, the pattern of evolution of China's overall energy eco-efficiency is U-shaped. Among local regions, four main patterns of evolution are found: increasing, fluctuating, mutating, and leveling.(2) At the provincial level, China's energy eco-efficiency features significant spatial agglomeration both globally and locally. High–high agglomeration occurs mainly in the eastern and southern coastal regions and low–low agglomeration in the northwestern region and the middle reaches of the Yellow River. Changes in spatial patterns have occurred mainly in areas with high–low and low–high agglomeration, with the most remarkable change taking place in the Beijing–Tianjin–Hebei region.(3) There exist significant spatial effects of energy eco-efficiency among provinces in China. For the energy eco-efficiency of a given region, spatial spillovers from adjacent regions outweigh the influence of errors in adjacent regions. Industrial structure has the greatest influence on energy eco-efficiency.     

中国互联网规模对技术效率的影响与空间溢出效应

以2003~2014年282个地级以上城市数据作为样本,采用随机前沿生产函数模型测算了中国各城市技术效率,并以互联网规模作为解释变量,构建空间杜宾模型实证检验了各区域互联网对技术效率的影响与空间溢出效应。研究结果表明,互联网规模对技术效率的影响与空间溢出效应存在显著区域差异,分区域检验互联网规模对技术效率的作用是有必要的;互联网规模对中国各区域技术效率具有显著提升作用,但是其提升作用依然较小;东部、中部、西部的城市均受到互联网规模的正溢出效应;东部、中部地区受到技术效率的正溢出效应,西部地区受到技术效率的负溢出效应;分区域检验互联网规模对技术效率的影响及其空间溢出效应,能为推动互联网与经济社会发展深度融合提供有效参考。     

中国海港空间效应的识别与测度

在全球化和世界产业转移浪潮推动下,沿海港口已成为全球生产链条与地方网络链接的地理枢纽。与此同时,港口发展演化在推动港口自身运输体系及港口空间演化的同时,对腹地经济发展产生重大影响。首先,从经济地理学视角,提出海港空间效应的概念及其内涵,从港口势能、港—腹引力、作用通道三个方面阐述海港空间效应的动力结构和形成要素。其次,以海港空间效应的动力结构为理论依据,建立海港空间效应的测度模型。最后,以我国东部沿海港口为研究样本,运用海港空间效应测度模型,得到海港空间效应指数。以港口吞吐量、集装箱吞吐量、外贸吞吐量为指标表征沿海港口对腹地的运输效应分布格局,以港口城市工业、对外贸易和金融指标表征沿海港口对腹地的非运输效应格局,对不同区域特点和差异进行比较分析,验证模型的准确性和可操作性。结果表明,模型可较好地从宏观尺度识别不同港口及其腹地的港口经济空间效应,对于揭示港口的区位本质,比较不同区域的临港化倾向,刻画港口—腹地型城市地域系统的空间联系具有指导意义。     

中国省区间制造业空间格局演变(英文)

This paper, concerning uneven development in China, empirically analyzes the core–periphery gradient of manufacturing industries across provinces(autonomous regions, municipalities), and assesses the extent to which these provinces have changed in recent years. Since China's reform and opening-up, the spatial structure of the economy has presented a significant core–periphery pattern, the core evidently skewing towards east-coastal areas. With the deepening of market reforms and expansion of globalization, industrial location is gradually in line with the development advantages of provinces. The core provinces specialize in those industries characterized by strong forward and backward linkages, as well as a high consumption ratio, a high degree of increasing returns to scale, and labor or human-capital intensity. However, it is the opposite with regard to peripheral provinces, in addition, energy intensive industries are gradually concentrating in these areas. To a certain degree, the comparative advantage theory and new economic geography identify the underlying forces that determine the spatial distribution of manufacturing industries in China. This paper indicates that the industrialization of regions along different gradients becomes unsynchronized will be a long-term trend. Within a certain period, regions are bound to develop industrial sectors in line with their respective characteristics and development stage. A core–periphery pattern of industries also indicates that industrial development differentials across regions arise because of not only the uneven distribution of industries but also the inconsistent evolving trends of industrial structure for each province.     

长三角城市创新空间的集聚与溢出效应

选取长三角地区各城市2001-2012年专利申请受理量作为表征各城市创新水平指标,采用变异系数、基尼系数、赫芬达尔指数和空间自相关指标和方法,考察长三角地区创新空间格局演变特征,并使用空间回归分析方法,探讨长三角地区创新空间差异的影响因素。研究表明:(1)长三角地区整体创新空间差异和创新集中度呈下降趋势,近年来已趋向稳定。(2)长三角地区创新空间格局仍处在动态变化之中,但已基本形成以上海、南京为端点的创新高值集聚带。长三角地区创新空间已表现出正的空间相关性,但呈现出波动变化特征,空间相关性并不显著,仍存在一定程度的空间异质性。(3)城市创新已表现出一定程度的空间溢出效应。创新综合投入、创新环境和创新规模是长三角地区创新空间差异的主要影响因素。     

京津冀地区经济发展的空间溢出效应

在实施京津冀协同发展战略的背景下,将修正的Conley-Ligon模型与空间马尔可夫链分析法相结合,探讨了京津冀县域经济发展过程中的溢出效应空间格局及其对经济水平空间格局演变的影响。研究发现：2000-2013年,京津冀地区的县域间存在显著的空间溢出效应,溢出效应在空间上呈现出与经济发展水平和空间距离紧密相关的具有梯次性特征的核心-外围结构,经济发达的地区发出正向溢出效应的同时也获取了正向溢出效应,但总体上县域溢出效应的类型以负向溢出为主;受溢出效应的空间格局和以负向溢出为主要类型的影响,京津冀县域经济水平类型发生转变的概率较小,经济水平较低的县域难以发生类型的转移,经济水平类型发生转移的县域多分布在地级以上城市市辖区的邻接地带;在邻接县域间显著的空间溢出效应作用下,相邻县域的经济水平类型的转移具有显著的同向性特征。     

中国科技资源配置效率测度及其时空格局演变特征(英文)

According to the connotation and structure of science and technology resources and some relevant data of more than 286 cities at prefecture level and above during 2001–2010, using modified method—Data Envelopment Analysis(DEA), science and technology(ST) resource allocation efficiency of different cities in different periods has been figured out, which, uncovers the distributional difference and change law of ST resource allocation efficiency from the time-space dimension. Based on that, this paper has analyzed and discussed the spatial distribution pattern and evolution trend of ST resource allocation efficiency in different cities by virtue of the Exploratory Spatial Data Analysis(ESDA). It turned out that:(1) the average of ST resource allocation efficiency in cities at prefecture level and above has always stayed at low levels, moreover, with repeated fluctuations between high and low, which shows a decreasing trend year by year. Besides, the gap between the East and the West is widening.(2) The asymmetrical distribution of ST resource allocation efficiency presents a spatial pattern of successively decreasing from Eastern China, Central China to Western China. The cities whose ST resource allocation efficiency are at higher level and high level take on a cluster distribution, which fits well with the 23 forming urban agglomerations in China.(3) The coupling degree between ST resource allocation efficiency and economic environment assumes a certain positive correlation, but not completely the same. The differentiation of ST resource allocation efficiency is common in regional development, whose existence and evolution are directly or indirectly influenced by and regarded as the reflection of many elements, such as geographical location, the natural endowment and environment of ST resources and so on.(4) In the perspective of the evolution of spatial structure, ST resource allocation efficiency of the cities at prefecture level and above shows a notable spatial autocorrelation, which in every period presents a positive correlation. The spatial distribution of ST resource allocation efficiency in neighboring cities seems to be similar in group, which tends to escalate stepwise. Meanwhile, the whole differentiation of geographical space has a diminishing tendency.(5) Viewed from LISA agglomeration map ofST resource allocation efficiency in different periods, four agglomeration types have changed differently in spatial location and the range of spatial agglomeration. And the continuity of ST resource allocation efficiency in geographical space is gradually increasing.     

中国城市脆弱性的综合测度与空间分异特征（英文）

The urban vulnerability poses a serious challenge to achieving sustainable development. With the concentration of the population and the economy,cities must manage the higher frequencies and risks of various hazards and are becoming more vulnerable. Research on the assessment and regulatory control of urban vulnerability is of great significance for both urbanization quality improvement and sustainable development in China or other countries in the world. Because of the complexity of cities and vulnerability concepts,existing studies have focused on different aspects of urban vulnerability. And the research content of urban vulnerability is scattered and relatively independent,leading to a lack of comparability among the research data and resulting in tremendous difficulties in summarizing the conclusions through comparison of independent research data. Therefore the goal of this study was to construct urban vulnerability index(UVI) from the perspective of sustainable development that could assess urban vulnerability comprehensively. In this study,we selected 10 subindexes involving 36 specific parameters from four aspects(resources,eco-environmental systems,economics,and social development) to construct a comprehensive index system. We also established the standard values of measurements. Then we take 288 prefecture-level cities in China as a study area and evaluate its overall urban vulnerability and its spatial differentiation. Results indicate that urban vulnerability of China has a remarkable spatial differentiation of both "gradient distribution" and "clustered distribution"; the extent of urban vulnerability corresponds to city size,the bigger the city,the lower its vulnerability; resource-based cities are more vulnerable than comprehensive cities; a city's economic growth rate does not reflect the extent of its urban vulnerability. Further,we offer a few suggestions to cope with urban vulnerability in China.     

中国水资源利用效率及其影响因素研究

科学地评价我国水资源利用效率的地区差异,对推进社会可持续发展具有重要意义。将水足迹作为投入指标纳入水资源利用效率的分析框架之中,提出Shephard水资源距离函数,并依据2009—2018年我国大陆30个省份（西藏除外）的面板数据,运用基于Shephard水资源距离函数的随机前沿分析模型对我国区域的水资源利用效率及其影响因素进行了实证分析。结果表明：（1）在研究期间,我国水足迹总量及其年增长率均有较大的波动,我国各省份的水足迹总量之间的差异较为明显;（2）东部、中部、西部的水资源利用效率存在显著差异,呈现出自东向西依次递减的区域分布特点;（3）经济发展水平与水资源利用效率呈正相关,水资源禀赋、城镇化进程和产业结构（第三产业比重）均与水资源利用效率呈负相关。研究结果有利于探寻促进我国水资源可持续利用和统筹协调发展的有效途径。     

中国区域全要素生产率的空间溢出关联效应研究

运用空间计量模型对1990~2011年中国全要素生产率进行研究,发现：此间中国省域全要素生产率在大部分年份呈现了空间自相关性,表明这22 a间中国省域全要素生产率并不是完全的随机状态,受其它区域的影响。进一步运用空间计量经济模型从空间维度探究了区域全要素生产率的影响因素,研究表明：经济的集聚水平越高,全要素生产率会得到显著改善;人力资本对经济增长与效率的提升有着显著地积极作用,并表现一定程度的溢出;政府干预和产业结构对全要素生产率的影响为负,说明政府部门要减少对经济的干预;同时表明了中国的产业结构可能存在不合理的地方;信息化水平、基础设施水平对全要素生产率的影响为正,但基础设施水平在统计学意义上并不显著;民营化所占比重的提升对全要素生产率的改进是显著的,因为私有化致使企业的权力下放有助于提高技术效率;经济开放水平显著提升了中国的区域全要素生产率;中国部分省份土地投入规模过大而出现规模不经济的问题。从全要素生产率在各个地区间溢出的证据出发,各个地方政府在统筹区域经济发展的过程中不仅需要考虑本地区经济发展的实际,需要打破目前行政区经济的界限,实现跨区域的协调与合作,实现共赢,最终实现所有地区全要素生产率的提高。     

中国城市碳排放强度的空间溢出效应及驱动因素

采用核密度估计、空间自相关、空间马尔科夫链和面板分位数回归等方法对1992-2013年全国283个城市碳排放强度的空间溢出效应和驱动因素进行了分析。① 核密度估计结果表明,中国城市碳排放强度总体均值下降,差异在逐步缩小。② 空间自相关Moran's I指数表明城市碳排放强度存在显著的空间集聚性且空间集聚性在逐渐增强,但空间集聚水平的变化逐年缩小。③ 空间马尔科夫链分析结果表明：第一,中国城市碳排放强度存在马太效应,低强度与高强度的城市在相邻年份转移过程中呈现维持初始状态的特征。第二,城市碳排放“空间溢出”效应明显,且不同区域背景下溢出效应存在异质性,即若与碳排放强度低的城市为邻,该城市的碳强度能够增加向上转移的概率,反之亦然。④ 面板分位数结果显示：在碳排放强度低的城市,经济增长、技术进步、适当的人口密度起到减排作用;外商投资强度与交通排放是使碳强度增大的主要因素。在碳排放强度高的城市,人口密度是重要的减排因素,技术进步暂时没起减排作用;工业排放、粗放式的资本投资以及城市土地蔓延则是碳强度上升的主要因素。