摘要
文章以人均GDP表征经济增长,采用时空自相关方法探讨1985-2016年间中国大陆330个地级市经济不平等的时空关联格局及演变。结果表明:中国地市经济增长存在较强的正向时空关联性,且关联性逐年增强,关联特征上则保持着与经济发展差异变化的一致性。中国地市经济增长局部时空关联呈现"东高西低"的态势,HH(高高)型地市与主要城市群的空间分布大致重合,从时间演变来看,HH型时空关联地区的辐射范围有不断扩大态势,其他类型变化相对稳定。中国地市经济增长的时空关联具有一定的路径依赖或空间锁定特征,局部时空关联类型保持稳定演化的概率最低为65.6%,最高达89.2%,但中国地市经济增长的时空关联仍有跨越式提高或降低的可能性。
This paper,by characterizing the economic growth with per capita GDP and applying the spatial-temporal correla-tion method,discusses the the spatial-temporal correlation pattern and evolution of economic inequality of 330 prefecture-lev-el cities in China. The results show that: China's economic growth at prefecture-level has a strong positive spatial-temporalcorrelation,and the correlation increases year by year. The correlation characteristics maintain the consistency with the differ-ences of economic development. The local spatial-temporal correlation of economic development at prefecture-level presentsthe trend of"high value regions in the east and low value regions in the west". The spatial pattern of HH(High-High) type re-gions coincides almost with the main metropolitan areas. From the time evolution,the type of HH tends to expand its radiationscope,whereas other types relatively keep stable. There is a certain path-dependence or space-locked effect in the spatial-temporal correlation of economic development at prefecture-level,the lowest probability of being stable evolution in the localspatial-temporal correlation type is 65.6%,and the maximum is up to 89.2%. However,there is possibility to increase or de-crease by leaps and bounds among these types of spatial-temporal correlation.
引文
[1]WEI Y D.Spatiality of regional inequality[J].Applied Ge-ography,2015,61:1-10.
[2]LIAO,F H F,WEI Y D.Dynamics,space,and regional in-equality in provincial China:A case study of Guangdongprovince[J].Applied Geography,2012,35(1/2):71-83.
[3]LIAO F H,WEI Y D.Space,scale,and regional inequalityin provincial China:A spatial filtering approach[J].Ap-plied Geography,2015,61:94-104.
[4]FAN C C,SUN M.Regional Inequality in China,1978-2006[J].Eurasian Geography and Economics,2008,49(1):1-18.
[5]REY S J,JANIKAS M V.Regional convergence,inequality,and space[J].Journal of Economic Geography,2005,5(2):155-176.
[6]REY S J,SMITH R J.A spatial decomposition of the Ginicoefficient[J].Letters in Spatial and Resource Sciences,2013,6(2):55-70.
[7]YU D L,WEI Y H D.Spatial data analysis of regional de-velopment in Greater Beijing,China,in a GIS environment[J].Papers in Regional Science,2008,87(1):97–117.
[8]梅志雄,徐颂军,欧阳军.珠三角县域城市潜力的时空关联结构演变[J].地理学报,2014,6(4):497-509.
[9]王劲峰,葛咏,李连发,等.地理学时空数据分析方法[J].地理学报,2014,69(9):1326-1345.
[10]CLIFF A D,ORD J K.Space-time modelling with an appli-cation to regional forecasting[J].Transactions of the Insti-tute of British Geographers,1975,64:119-128.
[11]MARTIN R L,OEPPEN J E.The identification of regionalforecasting models using space-time correlation functions[J].Transactions of the Institute of British Geographers,1975,66:95-118.
[12]PFEIFER P E,DEUTSCH S J.A three-stage iterative pro-cedure for space-time modeling[J].Technometrics,1980,22(1):35-47.
[13]LóPEZ H F A,CHASCO Y C.Time-trend in spatial de-pendence:specification strategy in the first-order spatialautoregressive model[J].Estudios de Economía Aplicada,2007,25(2):631-650.
[14]HARDISTY F,KLIPPEL A.Analysing spatio-temporal au-tocorrelation with LISTA-Viz[J].International Journal ofGeographical Information Science,2010,24(10):1515-1526.
[15]韩卫国,王劲峰,高一鸽,等.区域交通流的时空预测与分析[J].公路交通科技,2007,24(6):92-96.
[16]赵玲,王佳璆,邓敏,等.基于行车时间的道路网络时空自相关模型研究[J].中南大学学报:自然科学版,2012,43(10):4114-4122.
[17]陈绍宽,韦伟,毛保华,等.基于改进时空Moran's I指数的道路交通状态特征分析[J].物理学报,2013,62(14):527-533.
[18]王佳璆.时空序列数据分析和建模[D].广州:中山大学,2008.
[19]王艳辉,贾利民,王卓,等.基于时空序列的铁路客运量数据挖掘预测[J].中国铁道科学,2005,26(4):130-135.
[20]王劲峰.空间分析[M].北京:科学出版社,2006.