摘要
利用空间统计方法，对于1993～2008年中国省域刑事犯罪率的分布及演变进行分析，结果发现：①在空间整体分布上，高刑事犯罪率地区逐渐向沿海地区转移。②在空间关系上，刑事犯罪率的空间集聚程度不断加强，高犯罪率区域集聚在沿海地区，低犯罪率区域集聚在中部地区，形成两极分化。③就刑事犯罪率增长而言，存在“俱乐部趋同”现象。同时，构建空间面板计量模型，研究刑事犯罪率影响因素，结果发现：①在考虑时间和空间异质效应的条件下，流动人口与刑事犯罪率之间没有显著相关；但在与行业收入差距共同作用的情况下，流动人口与刑事犯罪率显著相关。②行业收入差距对刑事犯罪率影响显著，其稳健性极强；城乡收入差距和省域收入差距对刑事犯罪率没有影响。③空间邻近效应是影响刑事犯罪率的极重要因素，其作用程度和稳健性都比流动人口和收入差距对刑事犯罪率的影响来得更为强烈。
By the methods of ESDA, Markov Chains, and based on the data of crime rates at province evel in China from 1993 to 2008, the spatio-temporal pattern change of crime rates were discussed. The results are shown as follows. First, on the overall distribution of space, the higher criminal rates gradually transferred to coastal areas. Second, The crime rates showed a strong trend of spatial correlation, the similar units cluster in space, the higher level spatial units were concentrated in the provinces of eastern China, and the lower level spatial unites were mainly in the provinces of middle China. There was an obvious trend in the ＂Polarization＂ of crime rates development level. Third, there exited a phenomenon of ＂Club Convergence＂ in crime rates development level in the study area, spatial discrepancy of crime rates development level has become greater. Referring to the previous studies, the relationship among income inequality, floating population and crime rates. In order to improve the overall predicting ability for crime rates at province level, the ＂spatial effect＂ is incorporated into the panel econometric model. The panel econometric model includes two effects, fix effect and random effect. Generally speaking, the fixed effect model is favored when the regression analysis is applied to a precise set of regions; random effect, instead, is an appropriate specification if a certain number of individuals are randomly drawn from a large region of reference. For this reason, the fixed effect panel model is cho- sen, which is extender to include spatial error autocorrelation or a spatially lagged dependent variable autocor- relation. This article uses spatial lag fixed effect panel regression model to analyze the relationship between macro factors and crime rates. The regression results show that considering the effect of time and spatial heterogeneity of conditions, there is no significant correlation between floating population and crime rates; but under the common role of the industry and the incom
出处
《地理科学》
CSCD
北大核心
2013年第5期529-537,共9页
Scientia Geographica Sinica
基金
教育部人文社会科学研究规划基金项目(10YJA790083)资助
关键词
刑事犯罪
时空演变
流动人口
空间效应
crime
spatio-tempoml pattern of crime rate
floating population
neighborhood effect
