健康公平理念下社区养老设施的空间分布研究——以上海市中心城区为例

提要:健康公平是当前联合国倡导的可持续发展重要目标,也是"健康中国"国策的重要战略目标.本文聚焦社区养老设施这一重要健康资源,采用基尼系数和洛伦兹曲线,比较分析上海市中心城区多种类型社区养老设施的空间分布公平性,并运用LISA方法辨析社区养老设施与老年人口的空间分布关联格局,识别存在高需求但低配置问题的供需显著失衡区域...     

时空交互视角下的中国入境客流分布动态分析

运用探索性时空分析框架(ESTDA),从时空交互视角分析1987-2013年入境港澳台和外国人市场的客流省区分布动态。研究发现:(1)省区差异趋于缩小,空间集聚增强。(2)港澳台市场全域极化突出,外国人市场局部时空模式多元;港澳台市场局部空间稳定性由西南部向中北部递减;东南省区间时空依赖效应较强,西北省区较弱。外国人市场局部空间稳定性由沿海、沿边向内陆递减;西部省区间时空依赖效应较强,东南省区较弱。(3)各省区的市场地位相对稳定,外国人客流空间格局变动性相对较高。(4)客流变动以省区协同增长为主,竞合格局因市场和局部区域而异。提出进一步壮大中西部旅游增长极;构建无障碍旅游区;区域合作差异化;加大宣传力度等对策。     

A Geospatial Analysis of China's Exports, 1991-2008

Three Taiwan-based economists employ a range of exploratory spatial data analysis tools (e.g., Moran's I and LISA statistics) to investigate trends in the growth of China's exports over the period 1991-2008. A particular focus is on the detection of spatial correlations between China and 40 export destination countries in major world regions. Emphasis in the paper on the key years of 1991, 2001, 2006, and 2008 has enabled the authors to analyze the impacts on China's trade of such major events as the country's accession to the World Trade Organization and the global economic crisis of 2008-2009. The results of the spatial analysis reveal the continuing importance of the U.S. and Asian countries in China's export trade (despite changes in the character of trade relations) and identify the spatial outliers (e.g., in Latin America) that may serve as the basis for new export markets for China in the future.     

GPS-based measurement of geographic spillovers in tourism – example of Polish districts

The agglomeration phenomenon in tourism often spreads beyond the borders of territorial units what is referred to as geographic spillovers. However, the measurement of spatial concentration of tourism demand and economic activity is usually based on statistics collected within regional administrative boundaries and omits the spatial interdependency between neighboring regions. Recognition of such spatial interdependency in the standard procedure to define neighborhood relies on the distance between geometric means (centroids) of territorial units which, however, rarely reflects real ‘centers’ of tourism agglomerations and leads to errors and biased results. Hence, we propose to modify the measures of the neighborhood with the use of GPS coordinates of tourism firms and attractions in order to designate their regional central tendencies and thus to correct (shift in space) localization of centroids of territorial units. We test the usefulness of the new approach to obtain a more precise measurement of spatial concentration when tourism spills over beyond the boundaries of territorial units using the example of Polish districts. We employ the exploratory spatial data analysis (spatial statistics) and spatial regression models – to assess the difference between using traditional centroids and GPS coordinates in defining neighborhood and determining spillover effects in regional analysis. Furthermore we apply the new method into the model of tourism potential in order to identify spillover effects in Polish regions. We use the data collected by Central Statistical Office (tourists staying overnight in 379 districts in 2014) and by Polish Tourist Organization (14,390 GPS coordinates of individual entities: tourism firms and attractions). The neighborhood determined with the use of GPS coordinates to measure the distance between centers of tourism agglomerations eliminates the dependence of the results on the administrative boundaries – but only to some degree. The challenge is to identify tourism agglomeration phenomenon as such, based on the mobility of tourists in space.