我國(guó)知識(shí)密集型服務(wù)業(yè)空間集聚的實(shí)證研究——基于286個(gè)地級(jí)及以上城市的經(jīng)驗(yàn)證據(jù)
經(jīng)濟(jì)問(wèn)題探索
頁(yè)數(shù): 13 2019-11-01
摘要: 為深入探究我國(guó)知識(shí)密集型服務(wù)業(yè)的空間集聚態(tài)勢(shì)及影響因素,利用我國(guó)286個(gè)地級(jí)及以上城市的面板數(shù)據(jù),采用聚類分析、計(jì)量回歸模型等方法對(duì)問(wèn)題展開(kāi)了探討。結(jié)果表明:首先,總體上不論是基于行業(yè)分類還是地區(qū)分類,我國(guó)知識(shí)密集型服務(wù)業(yè)都存在集聚程度較低且發(fā)展不均衡的現(xiàn)象;其次,具體到城市來(lái)看我國(guó)大致呈現(xiàn)出以直轄市和東部地區(qū)發(fā)達(dá)城市為知識(shí)密集型服務(wù)業(yè)集聚中心的空間分布態(tài)勢(shì),且教育專業(yè)化程度對(duì)于提升非省會(huì)城市的集聚水平作用更加明顯;最后,從影響因素角度來(lái)看較高的信息化水平、人力資本能促進(jìn)知識(shí)密集型服務(wù)業(yè)空間集聚,而制造業(yè)集聚發(fā)展水平目前尚未達(dá)到與知識(shí)密集型服務(wù)業(yè)發(fā)展相匹配的狀態(tài)。 In order to study the spatial agglomeration situation and influence factors of Chinese knowledge-intensive business service,this paper applies the panel data of 286 prefecture and above level cities and adopts the cluster analysis,dynamic regression model and other methods to expand the discussion. The results demonstrate: firstly,in general,whether based on the industrial classification or regional classification,Chinese knowledge-intensive business service encounter the low agglomeration degree and unbalanced development; then,viewing from the specific cities,Chinese knowledge-intensive business service mainly distributes in the direct-controlled municipalities and eastern developed cities as well as the education professional degree could play a significant role in promoting the agglomeration function of non-capital cities; finally,from the perspective of the influence factors,the higher informationalized level and human resource capital could drive the agglomeration of knowledge-intensive business service so that the manufacturing industry agglomeration development level could not catch up with the development state of the knowledge-intensive business service.