Global multidimensional poverty has arouse great attention from the public. It is of great theoretical and practical significance to explore the spatial and temporal changes of multidimensional children poverty and its influencing factors. Taking 25 provinces (municipalities and autonomous regions) of China as an example, this study uses the A-F method to measure children multidimensional poverty of China during 2010-2016, and examines its spatio-temporal pattern and influencing factors with spatial autocorrelation and the geodetector. The results demonstrated the following: (1) During 2010-2016, the children multidimensional poverty index in eastern, central and western China showed a downward trend, and poverty in the dimensions of living standards, care, education and health were effectively improved. (2) The children multidimensional poverty index and each dimensional poverty index had spatial differences, which was manifested as "high in the east, medium in the central region, and low in the west". (3) Urban and rural children multidimensional poverty in China has been improved, and the index spatial pattern has gradually changed to "east, middle, west; high, middle, and low", however, the multidimensional poverty index of rural children has been far higher than that of urban children. (4) Family environment and urbanization level are important factors affecting children multidimensional poverty. Ability of raising children, economic level and educational environment are secondary factors. The interaction between the factors has a far greater impact on children multidimensional poverty than a single factor. Educational environment and ability of raising children, urbanization level and medical resources, and family environment are the main interactive factors leading to children multidimensional poverty.

儿童是社会发展的未来,相对于具有劳动能力的成年人,儿童群体更易陷入严重的多维贫困状态,因此探讨儿童多维贫困的时空动态变化及其影响因素具有重要的理论价值和实践意义。以中国25个省、市、自治区为研究区,使用A-F法从住房、照料、教育、健康、营养维度对2010—2016年中国儿童多维贫困进行测度,并结合空间自相关、地理探测器等方法对其时空格局及影响因素进行研究。结果表明：① 2010—2016年中国东中西部儿童多维贫困指数均呈下降趋势,儿童多维贫困在住房、照料、教育、健康、营养各维度均得到有效改善;② 2010—2016年中国儿童多维贫困、各维度贫困存在空间分布差异,呈现“东—中—西”部儿童多维贫困指数阶梯式递增的空间特征;③ 2010—2016年中国城市、农村儿童多维贫困情况均得到改善,空间分布向着“东—中—西”贫困指数阶梯式递增的格局转变,但农村儿童多维贫困指数始终远高于城市;④ 家庭情况、城镇化水平是影响儿童多维贫困空间分异的重要因素,抚养能力、经济水平、教育环境是影响儿童多维贫困的次要因素。综合来看,各影响因素的交互作用对儿童多维贫困空间分异的影响远超过单因素,教育环境与抚养能力、城镇化水平与医疗资源、家庭情况与抚养能力为影响儿童多维贫困的主导交互因素。

Green development is becoming increasingly important. The Fifth Plenary Session of the 18th CPC Central Committee established green development as an important development concept of the 13th Five-Year Plan (2016-2020). Urban agglomerations in China that perform as core areas are likely to play vital roles in the promotion of green development. This study focuses on Chinese urban agglomerations as the research object, and proposes a comprehensive index system for the assessment of green development. In addition, methods such as the projection pursuit model, Pearson correlation, coefficient of variation, and Theil index are used to measure the level of green development, spatial and temporal evolution characteristics, and heterogeneity in urban agglomerations of China. Results show that: (1) since 2005, the level of green development has been increasing, although by fluctuating amounts. When divided into layers, the green development results indicate a certain degree of hierarchical structure. Based on the overall performance of China's urban agglomerations over the past decade, their green development can be divided into five grades: highly advancing area, rapidly advancing area, steadily advancing area, preliminarily advancing area, and starting area. (2) The economic development element dominates the green development, followed by the social progress element, and then the ecological civilization element, which is improving gradually. Different levels of urban agglomerations show diverse characteristics at different stages when it comes to the evolution of dominant element. National urban agglomerations are dominated by economic development element, the dominant element in regional urban agglomerations is complex, and the provincial ones generally lack dominant element. Besides, there are also significant differences in the same hierarchy urban agglomeration. (3) The green development level of urban agglomerations mismatch the level of central cities and this phenomenon needs to be treated differently. (4) According to the Theil index value, differences in green development reveal a divergent trend, mainly owing to variations among the layers. (5) Finally, several policies are proposed to raise the level of such green development in China, including the exchange and cooperation among urban agglomerations, resource sharing, and the innovation and promotion of environmental policy.

绿色发展日益重要,党的十八届五中全会把绿色发展确立为“十三五”时期的一项重要发展理念,而作为中国发展核心区域的城市群必然对绿色发展的推进起着至关重要的作用。以中国城市群为研究对象,构建绿色发展综合评价体系,采用投影寻踪模型、Pearson相关、变异系数、Theil指数等方法,综合分析中国城市群绿色发展时空特征及异质性。结果表明：① 2005年以来中国城市群绿色发展水平波动上升,且呈一定的层级格局;城市群绿色发展差异显著,分为：高度推进区、快速推进区、稳步推进区、初步推进区、初始起步区5类。② 经济发展要素为中国城市群绿色发展主导支撑、社会进步要素次之,生态文明要素逐步加快;不同层级城市群不同阶段主导要素演化不同;同一层级内差异同样显著。③ 不同层级城市群中心城市与城市群绿色发展等级匹配存在异质性,需区别对待。④ 中国城市群绿色发展水平差异呈一定发散趋势,层级间差异成为绿色发展差异的最主要原因。⑤ 最后,提出全面提升中国城市群绿色发展水平的建议：加强城市群交流与合作、实现资源共享,加大环境政策的创新以及推行力度。

Understanding the geographical pattern and driving factors of China's population migration in the first 20 years of the 21st century has become a pivotal issue in promoting the construction of the new-type urbanization and interaction development between regions during the 14th Five-Year Plan period (2021-2025). Supported by the data of the sixth and seventh national population censuses and 2005 and 2015 national 1% population sample surveys, this paper aims to investigate the spatiotemporal evolution characteristics and influencing factors of interprovincial migration in China from 2000 to 2020. Relevant population geospatial analysis and the eigenvector spatial filtering Poisson pseudo-maximum likelihood estimation (ESF PPML) gravity model are employed. The following conclusions are drawn: (1) China's population migration patterns were generally stable from 2000 to 2020, where notable imbalance and network spillover effects were also detected. A large number of migrants from central, western and northeast parts of China tended to move to the eastern region. (2) The overall migration patterns between 2000 and 2020 revealed several changing characteristics. The degree of imbalance and spatial agglomeration of migration patterns gradually weakened. Yet, a north-south differentiation emerged. It is also found that the out-migration trend of the northeast region increased with the elaspe of time. (3) The ESF PPML model indicated that gravity factors (population scale, geographical distance), regional socio-economic factors (wage disparity, proportion of investment in science and technology and education, medical care), social network factors, environmental comfort (PM2.5 concentration) and living costs (proportion of housing price) drove the interprovincial migration pattern between 2000 and 2020. (4) The influence of regional economic differences on interprovincial migration reflected a weakening trend. The pattern of population migration gradually turned into the decision-making of diversified demands for the economy, public services and urban amenities, while the living cost factor represented by housing price had played a gradually significant part. The conclusion of this paper provides policy references for the construction of the new-type urbanization and coordinated development between regions during the 14th Five-Year Plan period in China.

准确认识和把握21世纪前20年中国人口迁移的地理格局和影响因素，是推动新型城镇化建设及区域均衡发展的关键科学问题。借助特征向量空间滤波泊松伪最大似然估计（ESF PPML）引力模型，基于第六次和第七次全国人口普查数据、2005年和2015年全国1%人口抽样调查数据，研究了2000—2020年中国省际人口迁移的时空演化特征及影响因素。主要结论为：① 2000—2020年间人口迁移格局总体稳定，具有较强的不平衡性和网络溢出效应，大量人口从中部、西部、东北地区迁移至东部地区；② 人口迁移格局稳中有变，不平衡程度和空间集聚程度逐渐减弱，人口迁移和人口分布显现出南北分异趋势，东北地区人口迁出强度不断增强； ③ 传统引力模型因素（人口规模、地理距离）、地区社会经济发展因素（工资差异、科技教育投入占比、医疗水平）、社会网络因素、环境舒适度（PM_2.5浓度）以及生活成本（住宅价格占比）共同影响人口迁移格局；④ 区域经济差异对省际人口迁移的影响作用逐步弱化，人口迁移逐渐转变为对工资收入、高质量公共服务、环境舒适度等多因素考虑的决策过程，生活成本逐渐对人口迁移产生显著影响。

Based on the comprehensive evaluation method combining fixed base range entropy weight method and fixed base equal weight assignment method, kernel density estimation and exploratory spatial data analysis methods, this paper analyzes the spatio-temporal evolution characteristics of public health level of 284 cities in China from 2003 to 2018, and uses the generalized spatial two-stage least square method to investigate its influencing factors. The results show that: (1) During the study period, the urban public health level is on the rise as a whole in China, but the difference of public health level among cities has expanded, and there is always a phenomenon of multi-level differentiation. (2) The kernel density curves of the four plates have their own evolution forms in the position of gravity center, the height of main peak, the number of wave crests, the length of trailing and the thickness of trailing, which is the result of the coupling and superposition of time characteristics and regional characteristics. (3) There are positive spatial spillover effect and spatial “Peer Effects” in China's urban public health level, and the spatial agglomeration type has transformed from LL type to HH type. (4) Income level, population density, technological progress, industrialization and health system reform have an impact on urban public health, but the impact of various factors on different regions is heterogeneous.

采用定基极差熵权法与定基等权赋值法相结合的综合评价方法、核密度估计、探索性空间数据分析等方法,分析2003—2018年中国284个地级以上城市公共健康水平的时空演化特征,并运用广义空间两阶段最小二乘法考察其影响因素。结果发现：① 研究期内中国城市公共健康水平整体呈上升趋势,但各城市间公共健康水平差异有所扩大,且始终存在多级分化现象;② 四大板块核密度曲线在重心位置、主峰高度、波峰数量、拖尾长度、拖尾厚度上均有各自演化形态,是一种时段特征与地区特色相互耦合叠加的结果;③ 中国城市公共健康水平存在正向空间溢出效应和空间“同群效应”,空间集聚类型实现了由LL型为主体向HH型为主体的转化;④ 收入水平、人口密度、科技进步、工业化程度、卫生体制改革对城市公共健康具有影响,但各因素对不同区域的影响存在异质性。

Coordinated development of basic public services and the economy is an important part of inclusive growth. Based on entropy method, coupled coordination degree model and Kernel density estimation method, this paper studies the spatio-temporal characteristics of coupling coordination between basic public services and economic development in the Guangdong-Hong Kong-Macao Greater Bay Area from 2009 to 2019. The results show that: 1) The comprehensive level of basic public services and economic development shows an upward trend of fluctuation, but with obvious stage characteristics, and the development of the two is not completely synchronous. 2) Basic public services and economic development have a strong coupling effect, and their coordination is gradually improved. However, there is no transition in the level of coupling coordination, which is always a kind of forced coupling coordination, forming a spatial pattern of low peripheral and high center. 3) The oupling coordination subtype heterogeneity of 11 cities is obvious, and the peripheral Jiangmen, Huizhou and Zhaoqing all belong to the lagging type of economic development. From a regional point of view, the lag of economic development is mainly distributed in the West, while the lag of basic public services is mainly concentrated in the East and the Middle. 4) The coupling coordination degree of the low value area shows an upward trend, the difference between the cities in the high value area is gradually narrowing, and the polarization phenomenon is formed between the cities in the high value area and the low value area. The results can provide a theoretical basis for relevant departments to coordinate policies for economic and basic public services in the Guangdong-Hong Kong-Macao Greater Bay Area.

基本公共服务与经济耦合协调度发展是包容性增长的重要内容。论文运用熵值法、耦合协调度模型和核密度估计方法,研究粤港澳大湾区2009—2019年基本公共服务与经济发展耦合协调的时空特征。结果表明：① 基本公共服务与经济发展综合水平均呈现波动上升趋势,但具有明显的阶段性特征,且二者发展不完全同步。② 基本公共服务与经济发展耦合作用强,协调性逐渐改善,但耦合协调等级没有发生跃迁,始终为勉强耦合协调类型,形成外围低中心高的空间格局。③ 11个城市耦合协调亚类型异质性明显,外围的江门、惠州、肇庆均属于经济发展滞后型。分区域看,经济发展滞后型主要分布在研究区西部(澳珠中江),基本公共服务滞后型主要集中在研究区东部(深港莞惠)和中部(广佛肇)。④ 低值区耦合协调度呈上升趋势,高值区城市之间的差异性在逐渐缩小,高值区与低值区城市间形成了两极分化现象。该成果能为相关部门在制定粤港澳大湾区经济与基本公共服务建设协调政策时提供理论依据。

The insurance industry is playing an increasingly important role in China's economic development, transformation and industrial upgrading. Based on the city panel data of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) from 2006 to 2019 and using entropy weights, kernel density estimation, and spatial econometric methods, this study examined the spatial-temporal characteristics of the development level of the insurance industry in the area and its impact on economic growth. The findings are as follows: 1) The comprehensive index of insurance industry development level increased with fluctuation. The insurance industry development level in 11 cities of the GBA showed the characteristics of Hong Kong, Macao, and Guangzhou leading in the eastern, central, and western regions, and Guangzhou, Shenzhen, and Zhuhai leading in the three economic circles of Guangzhou-Foshan-Zhaoqing, Shenzhen-Dongguan-Huizhou, and Zhuhai-Zhongshan-Jiangmen. 2) The development level of the insurance industry in the 11 cities is polarized, but the absolute difference between high-value and low-value regions tends to decrease, and the gap between low-value areas tends to widen. 3) The development of the insurance industry has a significant positive impact on regional economic growth. If other influencing factors remain unchanged, each 1% increase in the development level of the insurance industry will result in a regional economic growth of 0.0538%. The development of the insurance industry has negative spillover effect, but it does not pass the significance test. The research results provide a theoretical basis for relevant departments in the Greater Bay Area to formulate industrial policies that promote the insurance industry and economic development mutually.

保险业在中国经济发展、转型和产业升级等方面发挥着越来越重要的作用。论文利用粤港澳大湾区2006—2019年的市级面板数据,运用熵权、核密度估计和空间计量等方法,研究粤港澳大湾区保险业发展水平时空特征及其对经济增长的影响,结果表明：① 保险业发展水平综合指数在波动中上升,11个城市保险业发展水平呈现香港、澳门和广州单核领跑大湾区东、中、西部的特征,珠三角9市呈现广州、深圳和珠海单核领跑广佛肇、深莞惠和珠中江三大经济圈的特征;② 11个城市保险业发展水平存在两极分化现象,但高值区与低值区的绝对差异有缩小趋势,低值区城市之间的差距有扩大趋势;③ 保险业发展对本地区经济增长产生了显著的正向影响,在其他影响因素保持不变的情况下,保险业发展水平每提升1%,本地区经济增长0.0538%。保险业发展具有负溢出效应,但未通过显著性检验。研究成果为粤港澳大湾区相关部门制定保险业与经济发展相互促进的产业政策提供了理论依据。

It is of great theoretical and practical importance to measure and examine tourism ecological security in the Yellow River Basin (YRB). The purpose of this study is to promote coordinated and sustainable development of the tourism economy and ecological environment. From the perspective of watershed sustainable development, this paper constructs the theoretical framework and index system of tourism ecological security in the YRB based on DPSIR system model, and analyzes its dynamic evolution characteristics and driving factors by using improved TOPSIS method, kernel density estimation, spatial autocorrelation, traditional and spatial Markov chains and quantile regression panel method. The results showed that: (1) There has been an evolutionary trend toward a dual-core form of tourism ecological security over time, as its average value fluctuates and then rises. The overall tourism ecological security level was relatively low (0-0.55), shifting from the predominant risk level in 2008 (accounting for 89.04%) to the levels of predominant risk and deterioration in 2017 (60.27% and 31.51%, respectively). A large downward risk remains. (2) In terms of dynamic evolution characteristics, the transfer of tourism ecological security risks and sensitive levels had "path dependence" and "self-locking" effects. In practice, however, the probability of maintaining the initial state of the deterioration level and the critical safety level was relatively small. And the type of transfer was usually accomplished during a subsequent level transfer. Its dynamic change process was strongly influenced by regional factors. Its characteristics of dynamic evolution were characterized by significant spatial and temporal heterogeneity. (3) Tourism ecological safety was most significantly influenced by environmental pollution in lower-level units. The tourism load level had a greater positive marginal effect on higher-level areas; however, economic development and level of tourism development have a greater positive marginal effect on areas with lower ecological tourism security levels.

科学测度与审视旅游生态安全对促进黄河流域旅游经济和生态环境协调可持续发展具有重要的理论和实践价值。从流域可持续发展视角,基于DPSIR系统模型构建黄河流域旅游生态安全理论框架和指标体系,采用改进TOPSIS法、核密度曲线、空间自相关、传统和空间马尔可夫链及面板分位数回归方法对其动态演化特征和驱动因素进行探析。结果表明：① 时间上,旅游生态安全均值波动下降后上升,呈收敛趋势,且有向“双核”形态演变的趋势。空间上,旅游生态安全值整体较低（0~0.55）,由2008年以风险级为主（占89.04%）转变为2017年以风险级和恶化级为主（分别占60.27%和31.51%）,且仍存在较大下行转移风险。② 动态演化特征上,不考虑邻域条件下,旅游生态安全风险级、敏感级转移具有“路径依赖”与“自身锁定”效应。而恶化级、临界安全级保持初始状态概率较小,且类型转移通常发生在相邻等级递次转移。邻域背景在其动态变化过程中起着重要作用,且其动态演化特征具有显著时空异质性。③ 影响因素方面,环境污染对低层级单元的旅游生态安全负向抑制作用较为明显,旅游负荷水平对较高层级地区旅游生态安全的正向边际效应略大,而旅游发展水平、经济发展水平等变量则对较低等级单元旅游生态安全的正向边际效应较大。

Considering the new-type urbanization background, the nearby urbanization model provides a practical approach toward eliminating the disadvantage of trans-regional urbanization and promoting urbanization. This study establishes the indexes of the nearby urbanization rate (NU), contribution to nearby urbanization (CNU) and trend of contribution to nearby urbanization (TNU), to analyze the spatial differentiation features of nearby urbanization in central and western China from 2000 to 2015. Moreover, this study explores the determinant factors and influencing mechanism of the spatial differentiation of nearby urbanization in the study region. Results show that: (1) From 2000 to 2015, the population of nearby urbanization increased from 196 million to 347 million and the NU increased from 28.16% to 46.89%. (2) Based on the analysis of the CNU, we found that the main source of nearby urbanization was the population registered in the local town, but the contribution of local town to nearby urbanization (CNUt) gradually declined over the study period. The areas with high CNUt were widely distributed in central and western China in 2000, but by 2015, they were restricted to Sichuan province. Meanwhile, the contribution of local county to nearby urbanization (CNUc) increased and the contribution of local province to nearby urbanization (CNUp) varied slightly. Most areas with high CNUp were provincial capital cities, resource-based cities or pastural cities. (3) Based on the analysis of the TNU, the trend of the contribution of local county to nearby urbanization (TNUc) exceeded the trend of the contribution of local province to nearby urbanization (TNUp), while the trend of the contribution of local town to nearby urbanization (TNUt) exhibited the least influence. Therefore, examining nearby urbanization based on the county-level spatial unit was advantageous in most regions; however, in the northwestern border regions and provincial capital cities, the provincial level was more applicable. (4) The spatial differentiation of nearby urbanization was determined based on the integrated results of various influencing factors, including natural environment, economic development, non-agricultural industries, urban public services, transportation accessibility, and the influence of local administration.

就近城镇化是中国中西部地区破除异地城镇化模式弊端、推进新型城镇化健康发展的现实路径选择。通过构建就近城镇化率、贡献力和贡献势指标,从本省、本县和本镇3个城镇化尺度,系统分析2000—2015年中国中西部地区就近城镇化空间分异特征,并深入剖析其驱动机制。研究发现：① 2000—2015年中西部地区就近城镇人口总数从1.96亿增加到3.47亿,就近城镇化率从28.16%上升到46.89%。② 从贡献力看,中西部地区就近城镇化的主要来源是本镇户籍人口,但本镇贡献力呈下降趋势,本县贡献力波动上升,本省贡献力变化不大。③ 从贡献势看,本县贡献势>本省贡献势>本镇贡献势,县域尺度是中西部大部分地区就近城镇化的优势空间单元。④ 中西部地区就近城镇化空间分异是自然环境背景、经济增长和非农产业发展、城市公共服务供给、交通运输条件和地方行政力量等多重因素的综合作用结果。

Population and economy are essential problems of human social development and many studies have proved that there is a close correlation between them. Population flow is an important reason affecting the process of regional economic equilibrium, while regional economic disequilibrium is a vital driving force of population flow. Their spatio-temporal pattern and current relationship are constraint and support for regional sustainable development. Unbalanced development has become increasingly prominent in China, but the underdeveloped regions have not received enough attention. As minority autonomous region and southwest frontier region of China, Tibet has long been the only provincial concentrated contiguous poverty-stricken area. It is of great significance to examine the relationship between population and economy of this kind of area. This article made a spatial-temporal study on the inequality pattern of population-economy in Tibet during 2009-2018 by combining geographic concentration, Gini coefficient and inconsistent index. Panel data regression and spatio-temporal weighted regression model were used to analyze the factors affecting the inconsistency of population and economy distribution. The results show that the population and economy agglomeration demonstrate a stable and disequilibrium pattern which is characterized by high in the southeast and low in the northwest. The area with high geography concentration has strong coupling with the distribution of river valley plains, traffic trunks and administrative centers. The overall imbalance of population-economy is weakening. However, the spatial distribution and development trend of inconsistent index are disparate in different counties. Human capital, economic strength and industrial structure are the leading factors affecting the inconsistency of population-economy whose absolute value of the influence coefficient are more than 10%, followed by government regulation capacity, road infrastructure, physical capital and medical infrastructure. The effect of social consumption level is not significant. Spatial differences in effects on inconsistent index indicate that the effect of human capital and industrial structure on most counties are more reflected in attracting population. The influence of economic strength, physical capital, medical infrastructure and government regulation capacity are mainly reflected in promoting economic development, and the reach of economy strength covers all counties. Compared with other influencing factors, the spatial heterogeneity of the impact of road infrastructure and social consumption on inconsistent index are the most obvious.

选择地理集中度、基尼系数、不一致指数等指标，研究2009—2018年西藏人口与经济非均衡时空格局，并采用面板数据回归和时空地理加权回归模型对其影响因素进行分析。结果发现：西藏人口与经济分布表现出稳定的非均衡格局，呈现“东南高、西北低”的特征，地理集中度高值区与河谷平原、交通干线、行政中心的分布耦合性较强。西藏人口与经济空间匹配的整体非均衡性不断减弱，县区人口与经济不一致指数的空间分布和发展态势差异明显。人力资本、经济实力和产业结构水平是影响人口与经济不一致性的主导因素，三者影响系数绝对值均大于10%，其次是政府调控能力、道路基础设施、物质资本和医疗基础设施，而社会消费水平的作用不显著。各因素对不一致指数影响的空间异质性表明，人力资本和产业结构水平对大部分县区的影响更多体现在吸引人口方面，经济实力、物质资本、医疗基础设施、政府调控能力对县区的影响主要体现在推动经济发展上，其中经济实力的影响范围囊括所有县区;与其他影响因素相比，道路基础设施、社会消费影响的空间差异最为明显。