旅游产业集聚与区域旅游经济增长的关系——基于2001—2017年中国省际面板数据

基于空间自相关分析法,综合考察2001—2017年中国30个省区（不含西藏自治区和港澳台地区）旅游经济增长的空间相关性特征,继而构建空间杜宾模型探讨区域旅游经济增长的影响因素,并着重解析旅游产业集聚对区域旅游经济增长的空间溢出效应。结果表明：中国旅游产业集聚整体呈波动上升态势,且区域间差距日渐缩小;中国旅游经济增长具有显著空间相关性,局域空间分布以“H-H”和“L-L”类型为主;区域经济发展水平、城镇化水平、产业结构和区域创新能力是推动本省区及邻近省区旅游经济增长的重要因素,旅游产业集聚显著促进本省区旅游经济增长,对邻近省区则是负向影响,而交通设施条件对本省区旅游经济增长具有负向抑制效应,对邻近省区影响不明显,地区开放程度对旅游经济增长的作用不显著。     

中国建设用地与区域社会经济发展关系的空间计量研究

利用空间计量模型,对中国大陆地区的30个省、市、自治区2008年的建设用地面积与社会经济发展之间的关系进行了研究。研究表明:30个省、直辖市和自治区地区建设用地面积、GDP、总人口和城市化率都有显著的空间相关特征,一个区域社会经济的发展不仅会驱动自身区域建设用地的扩张,而且会带动邻近区域的建设用地的增长。传统上只从时间维度出发的研究思路,忽视空间维度的相关性和异质性,低估了区域社会经济发展对建设用地增长的作用,必须在普通面板线性回归模型中描述的基础上引入空间变量进行修正。计量模型检验表明,城市化水平对建设用地总规模的影响不甚显著。说明中国大部分省份的农村居民点用地的利用效率普遍偏低。因此,农村居民点用地的调整与优化已迫在眉睫,从长远看来,提高城市化水平,打破城乡二元化的土地制度,建立统一的土地市场,是缓解土地资源紧缺、提高土地利用效率的有效途径。     

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。     

改革开放以来中国城市化的时空演变及其影响因素分析

改革开放以来,中国城市化进程进入稳定快速发展时期,国家的经济宏观调控政策以及区域发展战略在时间和空间上均对中国的城市化产生了巨大的影响。在此影响下,中国城市化水平的区域空间格局也由北南差异转变为东中西差异,同时,中国省级城市化水平的差距正在逐渐缩小。在影响中国城市化省际差异的因素方面,传统的农业发展水平对城市化的影响正逐渐减弱,乡镇企业及外商直接投资成为20世纪90年代后期中国城市化发展的重要影响因素。     

Mega-towns in China: Their spatial distribution features and growth mechanisms

As a special outcome of urbanization, mega-towns not only play an important role in the process of socio-economic development, but also are important contributors to urbanization. Based on a spatial database of mega-towns in China, this paper explores the spatial distribution features and growth mechanisms of China's 238 mega-towns using the nearest neighbour distance method, kernel density estimation, regression analysis, global autocorrelation, local autocorrelation and other spatial analysis methods. Results of spatial distribution features show that:(1) on the national scale, the existing 238 mega-towns mainly gathered in the southeast coastal areas of China; they formed two spatial core agglomerations, several secondary ones and a southeast coastal agglomeration belt;(2) on the regional scale, each economic region's index was less than 1, indicating that mega-towns in each region tended to be spatially agglomerated due to the close relationship with regional development level and their number;(3) on the provincial scale, 68% of provincial-level units in China tended to be a spatial agglomeration of mega-towns; only one province had a random distribution; the number of mega-towns in those evenly-distributed provinces was generally small. The growth of mega-towns was determined by a combination of various natural and humanistic factors, including topography, location, economy, population, traffic, and national policy. This paper chose digital elevation model(DEM), location advantage, economic density, population density, and highway density distribution as corresponding indicators as quantitative factors. By combining their local autocorrelation analysis, these factors all showed certain influence on the spatial growth of mega-towns and together scheduled it. In the future, provinces and cities should make full use of the mega-town functions to promote their socioeconomic development, especially the central and western regions in China.     

沿黄九省工业水资源效率及其影响因素的时空异质性

科学评估工业水资源效率并识别其影响因素是缓解水资源供需矛盾的重要前提。基于非期望产出的超效率EBM（Epsilon-based measure）模型测度了沿黄九省2010—2019年的工业水资源效率,然后构建Tobit模型分析其全局影响因素,在此基础上选取显著性影响因素纳入时空地理加权回归模型,探究各影响因素的时空异质性。结果表明：沿黄九省工业水资源效率均值为0.77,未达到有效水平,但呈现出波动上升态势。各省份之间效率差异明显,山东最高（1.064）,宁夏最低（0.424）。在影响因素的宏观层面,技术水平和工业化程度对工业水资源效率攀升有正向促进作用;水资源禀赋、社会发展水平、工业用水强度和政府规制程度皆存在抑制效应,但显著程度不同,且高显著性影响因素的效应具有不同的时间演化趋势;在微观层面,各省份工业水资源效率的主导影响因素及其效应存在空间差异。     

我国东部沿海省区城镇化水平影响因素的空间差异

本文利用2000年截面数据,用因子分析法考察了我国东部沿海省区人口城镇化影响因素的差异、特征和类型。分析结果表明,沿海省区的城镇化水平受到多种因素不同程度的影响,各省区城镇化水平的影响因素及其影响作用呈现出明显的差异化特征,既有明显受到转型期要素流动影响的省份如广东省;也有综合经济实力提高推动城镇化的区域如沪苏和浙江省;还有表现为典型的工业化带动城镇化的传统模式的省份如山东省等。省区间差异化的城镇化影响因素表明,我国沿海省区的城镇化具有明显的个性化特征。     

中国省域间生态地租分异特征及其影响因素(英文)

Ecological land rent is the excess profit produced by resource scarcity, and is also an important indicator for measuring the social and economic effects of resource scarcity. This paper, by calculating the respective ecological land rents of all the provinces in China for the years 2002 and 2007, and with the assistance of the software programs ArcGIS and GeoDA, analyzes the spatial differentiation characteristics of ecological land rent; then, the influencing factors of ecological land rent differentiation among the provinces are examined using the methods of traditional regression and spatial correlation analysis. The following results were obtained: First, ecological land rent per unit of output in China shows stable distribution characteristics of being low in the southwestern and northeastern provinces, and high in Hebei and Henan provinces. There is also an increasing tendency in the central and western provinces, and a decreasing one in the eastern provinces. In general, the spatial distribution of ecological land rent per unit of output in China is quite scattered. Second, the total ecological land rent shows significant spatial aggregation characteristics, in particular the provinces in China possessing high total amounts of ecological land rent tend to be adjacent to one another, as do those with low total amounts, and the spatial difference characteristics of the eastern, central and western provinces are distinguished. The Bohai Rim, Yangtze River Delta and Pearl River Delta are shown to be highly clustering regions of total ecological land rent, while the western provinces have very low ecological land rent in terms of total amount. Third, population distribution, economic level and industrial structure were all important influencing factors influencing ecological land rent differentiation among provinces in China. Furthermore, population density, urbanization level, economic density, per capita consumption level and GDP per capita were all shown to be positively related to total ecological land rent, which indicates that spatial clustering exists between ecological land rent and these factors. However, there was also a negative correlation between ecological land rent and agricultural output percentage, indicating that spatial scattering exists between ecological land rent and agricultural output percentage.     

中国能源消费增长特征及影响因素分析

以煤炭消费为主、总量增长迅速、结构演进缓慢、使用效率低下使得中国目前能源消费调控问题面临诸多困难。本文使用多元回归模型和通径分析法确定了中国能源消费增长的主要因子及各因子的作用机理,结果发现：影响中国能源消费的主要因素按照影响程度依次为经济增长、城市化水平、对外贸易、人口总量、能源消费结构及能源利用效率,其中经济增长、人口规模扩大是直接推动中国能源消费增长的原因,而城市化水平和对外贸易规模则通过间接作用推动能源消费增长,能源消费结构的改善和能源利用效率的提高表面上看起来会引发能源消费增加,但是其间接影响都是负的,从而使得这两个因素整体上表现为减缓了能源消费增长。     

Air transportation in China: Temporal and spatial evolution and development forecasts

This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province’s future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows: (1) Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low. (2) Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others. (3) Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising 221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.     

基于空间计量模型的氮氧化物排放驱动因素分析：基于卫星观测数据

基于卫星观测技术核算出中国26个省份2007-2016年的氮氧化物排放量数据。首先,对省域氮氧化物排放的时空分布特征进行了详细分析。然后,采用空间面板数据模型对影响氮氧化物排放的社会经济驱动因素进行了实证研究。结果表明：① 以重工业发展为主的河北、山西、山东、河南、内蒙古以及经济较为发达的江苏和广东是氮氧化物污染的重灾区。② 中国省域氮氧化物排放存在显著的空间正自相关现象。③ 空间计量模型估计结果显示：氮氧化物排放存在显著的空间溢出效应。地区经济发展水平提高、第二产业比重提升以及煤炭消费量增加是引起氮氧化物排放的重要驱动因素。然而,地区技术水平升级以及外商直接投资则可以有效地减少氮氧化物排放,改善环境质量。     

中国入境旅游者购物消费的省际差异及影响因素——基于面板数据模型的分析

采用面板数据模型,对1999~2008年的中国各省区(港澳台除外)经济发展水平、旅游业发展水平、资源丰度、群体参照、口岸等因素对入境游客购物消费的影响进行了实证分析。结果表明,入境游客购物消费水平主要受以旅游住宿业的发达程度为代表的区域内经济及旅游发展水平和上年接待入境游客人数为代表的群体参照的影响,而口岸资源丰度对入境旅游者购物消费水平的影响呈现出两极化态势,资源丰度与入境游客购物消费之间存在空间错位。     

中国城镇化影响能源消耗的效应分解及机制探析

依据2000~2012年的省级面板数据,以空间杜宾模型为基础对全国及东部、中部、西部三大地区城镇化影响能耗强度的实际效应进行分析,利用求偏微分法将影响效应分解为直接效应与间接效应,解析城镇化影响能源消耗的内在机制。分析发现,当前城镇化对能耗强度具有正向促进作用,不同地区的城镇化进程对能耗强度的影响存在显著差异;全国范围内城镇化影响能源强度的总效应中间接效应显著为正,直接效应不明显,而东部、中部及西部三大地区呈现出不同的模式;中国城镇化对能源消耗的影响是规模效应、技术效应、结构效应、阶段性效应及空间效应综合作用的结果。     

中国省际生态福利绩效测算及影响因素研究

采用非期望产出SBM模型对2001~2015年中国省际生态福利绩效进行测算研究,运用空间自相关方法和空间误差模型对中国省际生态福利绩效的空间分布特征及影响因素进行检验。结果表明:① 中国生态福利绩效总体水平较高,但呈现出下降态势;各省市之间差异性明显,仅有北京、上海等6个省市实现有效,其他省市均存在不同程度的无效率状态;区域之间也存在差异性,总体呈现出东部>西部>中部的分布格局。② 中国省际生态福利绩效呈现正向空间自相关性,存在明显的集聚状态。③ 中国省际生态福利绩效的主要影响因素有技术进步、绿化程度、社会性支出、医疗水平、城镇化、产业结构和环境规制。     

Spatiotemporal dynamics of carbon intensity from energy consumption in China

The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%-45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spatiotemporal dynamics and dominating factors of China’s carbon intensity from energy consumption in 1997–2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China’s carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP (11.72%). Secondly, the trend of Moran’s I indicated that China’s carbon intensity has a growing spatial agglomeration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel econometric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China’s carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.     

中国土地利用变化生态环境效应的空间分异性与形成机理

中国复杂的自然要素、社会经济要素、区域发展战略和政策调控形成了当前中国不均衡的经济发展空间格局、土地利用空间格局和生态环境质量空间格局。厘清中国生态环境质量的空间格局及形成机理对中国土地资源的可持续利用和生态环境的有效保护具有重要的实践意义和价值。以往研究缺乏对中国县域尺度土地利用/土地覆被变化生态环境效应的空间分异性及形成机理的相关研究,本研究基于1995—2015年间中国土地利用现状遥感监测数据,尝试采用生态环境质量指数方法测度中国土地利用变化的生态环境效应,并且综合运用重心分析、热点分析工具（Getis-Ord G_i*）和地理探测器等研究方法,分析1995—2015年中国生态环境质量时空演变特征及形成机理。研究结果如下：① 东部季风区生态环境质量指数高于青藏高寒区和西北干旱区,东部季风区生态环境质量低值区主要分布在人口和经济集聚的城市群以及省会城市周边地区。研究期间中国生态环境质量重心持续向西北方向迁移;② 1995—2015年间中国生态环境质量变化的热点区域主要分布在西藏地区、新疆、重庆、贵州以及位于黄土高原的省份（青海、甘肃、宁夏、内蒙古、山西、陕西以及河南）境内,冷点区域主要分布在长江经济带沿线地区省份以及东南部沿海地区省份;③ 土地利用程度对于生态环境质量影响力显著强于其他因子,东部季风区的社会经济和交通区位因子对生态环境质量影响力强于青藏高寒区、西北干旱区和生态大区过渡带;④ 影响因子之间相互作用主要包括非线性增强作用和双因子增强作用两种类型,以非线性增强作用为主。     

中国航空运输的时空格局演变与发展预测（英文）

This paper analyses the features and dynamic changes of the spatial layout of air transportation utilization among different provinces in China. It makes use of data for the airport throughput and socio-economic development of every province throughout the country in the years 2006 and 2015, and employs airport passenger and cargo throughput per capita and per unit of GDP as measures of regional air transportation utilization, which is significant for refining indicators of regional air transportation scale and comparing against them. It also analyzes the spatial differences of coupling between the regional air transportation utilization indicators and the key influencing factors on regional air transportation demand and utilization, which include per capita GDP, urbanization rate, and population density. Based on these key influencing factors, it establishes a multiple linear regression model to conduct forecasting of each province's future airport passenger and cargo throughput as well as throughput growth rates. The findings of the study are as follows:(1) Between 2006 and 2015, every province throughout the country showed a trend of year on year growth in their airport passenger and cargo throughput per capita. Throughput per capita grew fastest in Hebei, with a rise of 780%, and slowest in Beijing, with a rise of 38%. Throughput per capita was relatively high in western and southeastern coastal regions, and relatively low in northern and central regions. Airport passenger and cargo throughput per unit of GDP showed growth in provinces with relatively slow economic development, and showed negative growth in provinces with relatively rapid economic development. Throughput per unit of GDP grew fastest in Hebei, rising 265% between 2006 and 2015, and Hunan had the fastest negative growth, with a fall of 44% in the same period. Southwestern regions had relatively high throughput per unit of GDP, while in central, northern, and northeastern regions it was relatively low.(2) Strong correlation exists between airport passenger and cargo throughput per capita and per capita GDP, urbanization rate, and population density. Throughput per capita has positive correlation with per capita GDP and urbanization rate in all regions, and positive correlation with population density in most regions. Meanwhile, there is weak correlation between airport passenger and cargo throughput per unit of GDP and per capita GDP, urbanization rate, and population density, with positive correlation in some regions and negative correlation in others.(3) Between 2015 and 2025, it is estimated that all provinces experience a trend of rapid growth in their airport passenger and cargo throughput. Inner Mongolia and Hebei will see the fastest growth, rising221% and 155%, respectively, while Yunnan, Sichuan, and Hubei will see the slowest growth, with increases of 62%, 63%, and 65%, respectively.     

转型期省际城市化效率格局演变与成因探析

以中国31个省域单元为例（未涉及港、澳、台地区）,从城市投入和产出2个基本维度上建立效率指标体系,应用改进DEA模型计算2000―2012年的省际城市化效率;并通过空间自相关分析模型、效率重心模型等方法对转型期中国省际城市化效率格局演变及成因展开实证探讨。研究表明：1）2000年以来中国省际城市化效率区域不均衡性显著,东部地区主要表现为技术效率驱动模式,而中西部地区表现为规模效率驱动模式;2）2000―2012年省际城市化综合效率、技术效率及规模效率全局上均呈现出正的空间自相关性,而局部上综合效率及规模效率具有相似集聚演化特征;城市化综合效率与技术效率的重心主要向东南方向偏移,而规模效率的重心主要向西南方向偏移;3）区位条件及禀赋、产业结构差异、区域发展政策及其市场化水平是影响转型期省际城市化效率空间格局演变的主要成因。     

东北地区城镇化与生态环境的脱钩分析

以2003~2012年东北地区34个地级市数据为基础^①(① 本文提及的地级市包括哈尔滨、长春、沈阳和大连4个副省级城市。),通过构建城镇化指数、生态环境压力指数,分析东北地区的城镇化发展及生态环境压力发展的时空演变特征,测度东北地区城镇化与生态环境的脱钩指数,判断其城镇化与生态环境的脱钩关系并探讨其发生变化的影响因素。结果表明：① 生态环境压力是城镇化累积作用的结果,呈现出一定的时空滞后效应;② 近10 a来,东北地区的城市发展经历了城镇化与生态环境由脱钩状态为主体向脱钩状态与负脱钩状态并举的演变过程,城市个体城镇化对生态环境效应的稳定性差;③ 投资驱动、资源型经济、生态环境倒逼和创新转型驱动等是东北地区城镇化对生态环境产生脱钩差异的根本原因。资源型经济和投资驱动是城镇化对生态环境产生压力的主要动因;生态环境倒逼和创新转型发展是摆脱城镇化对生态环境压力的关键动力。     

新时代老龄化与养老资源适配度时空差异及其影响因素分析

运用核密度估计、耦合协调模型、空间杜宾模型等方法对中国老龄化、养老资源配置、养老资源配置与老龄化适配度的演化格局进行了探讨,并揭示空间适配的影响因素,研究发现：① 中国老龄化程度不断上升,且呈现“东高西低”空间特征;② 中国养老资源配置整体水平提高,空间分布上离散程度上升,各省（区、市）之间的绝对差异随着时间的推移呈扩大态势;③ 各省（区、市）养老资源与老龄化的空间适配度明显改善,适配度呈现东部沿海向中西部递减的发展格局,空间集聚程度不断提高;④ 养老投资、政策关注度、养老相关志愿者、老年人抚养比均推动本地养老资源与人口老龄化的空间适配,养老相关志愿者、老年人抚养比还具有明显的正向溢出效应,而老年人协会则抑制周边地区养老资源空间适配。