长三角城市群旅游经济空间溢出效应分析——基于空间杜宾面板模型实证研究

Analysis of the Spatial Spillover Effect of Tourism Economy in the Yangtze River Delta Urban Agglomeration:An Empirical Study Based on the Spatial Dubin Panel Model

以长三角41个城市为研究单位,采用探索性空间数据分析和空间杜宾模型的实证方法,检验了2011—2018年间长三角城市群旅游经济空间关联属性及其影响因素的空间溢出效应。结果表明:(1)长三角城市群旅游经济整体上呈现正的空间自相关性,局部地区空间关联属性以高-高集聚和低-低集聚为主,高-高集聚地区主要集中在上海、苏南和浙北地区,低-低集聚主要集中在苏北和皖北地区。(2)长三角城市群旅游经济空间溢出系数是0.470,反映了长三角城市群旅游经济存在正向溢出效应,即周边城市旅游经济发展会带动本地旅游城市发展。(3)从影响因素上看,各因素影响路径和作用强度大不相同。从空间溢出角度看,经济发展水平和对外开放程度两种因素是正向的空间溢出效应,旅游资源禀赋则是具有负向的空间溢出效应。此外在对比空间面板模型时,普通固定面板模型容易会高估影响系数的值,进而会夸大这些因素的作用强度。

Taking 41 cities in the Yangtze River Delta as the research unit,using exploratory spatial data analysis and the empirical method of spatial Dubin model,the spatial spillover effects of the tourism economy spatial correlation attributes and influencing factors of the Yangtze River Delta urban agglomeration from 2011 to 2018 are studied.The results show that:(1) The tourism economy of the Yangtze River Delta urban agglomeration shows positive spatial autocorrelation as a whole.The spatial correlation attributes of local areas are mainly highhigh agglomeration and low-low agglomeration.The high-high agglomeration areas are mainly concentrated in Shanghai and Shanghai.In southern Jiangsu and northern Zhejiang,low-low agglomeration is mainly concentrated in northern Jiangsu and northern Anhui.(2) The tourism economy spatial spillover coefficient of the Yangtze River Delta urban agglomeration is 0.470,reflecting the positive spillover effect of the tourism economy of the Yangtze River Delta urban agglomeration,that is,the development of the tourism economy of surrounding cities will drive the development of local tourist cities.(3) From the perspective of influencing factors,the influence path and intensity of each factor are quite different.From the perspective of spatial spillover,two factors,the level of economic development and the degree of opening to the outside world,are positive spatial spillover effects,while the endowment of tourism resources has a negative spatial spillover effect.In addition,when comparing spatial panel models,ordinary fixed panel models tend to overestimate the value of the influence coefficient,and then exaggerate the strength of these factors.