Influence mechanism and measurement of

doi:10.3969/j.issn.1004-9479.2023.11.20220012

Abstract

Abstract:

Under the background of China's proposal to build a new development pattern of "a dual cycle" dominated by domestic large cycle, regional space such as metropolitan area and urban agglomeration has become an important carrier of dual cycle and a basic unit to participate in global competition, but the administrative region system barrier has not been completely broken. The term "institutional distance" comes from new institutional economics. Under the realistic background of insufficient and unbalanced regional development and significant regional institutional differences in China, "institutional distance" can be introduced into the study of regional economic space. The administrative division system distance can be divided into "boundary" and "resources". At the same time, the regional factor flow is regarded as a vector model with direction and scale, and the influence mechanism of institutional distance on regional economic integration is constructed. For further quantitative research, firstly, the evaluation index system of institutional distance is established, and multi-source big data such as population migration and investment between cities are used to analyze the coupling coordination degree between institutional distance and factor flow level. Based on the empirical study of Yangtze River Delta urban agglomeration, it is found that: (1) the barrier effect of border institutional distance on capital factors is usually higher than that on people flow factors, while there is no significant difference in resource institutional distance; (2) The spatial pattern of the two types of institutional distance is relatively similar. The coupling and coordination level in the metropolitan area is generally higher than that outside the metropolitan area, showing an obvious metropolitan area pattern; (3) There are obvious differences among the three metropolitan areas. The institutional distance barrier intensity of Shanghai metropolitan area is generally low, while that of Hangzhou metropolitan area and Nanjing metropolitan area is higher in turn. Finally, this paper puts forward some countermeasures, and believes that it is the key to solve the problem of weakening the institutional distance barrier of factor cross administrative region flow through the construction of flexible regional institutional space "Administrative region economy" and other regional segmentation problems, and an effective governance path to promote the strengthening of regional economic spatial ties.

Key words: regional economic integration, administrative region, institutional distance, coupling coordination degree, Yangtze River Delta urban agglomeration

摘要：

“双循环”新发展格局背景下，都市圈、城市群等区域空间成为国内大循环的重要载体，但阻碍我国区域要素自由流动的行政区制度壁垒仍待打破。将新制度经济学中的“制度距离”概念引入区域经济空间研究中，将行政区制度距离分为“边界”与“资源”两种类型，构建了制度距离对区域经济一体化的影响机制。首先建立了制度距离的评价指标体系，采用了人口迁徙与跨市投资等多源大数据，构建了制度距离与要素流动水平之间的耦合协调度模型。基于长三角城市群42组相邻城市的实证研究发现：（1）边界制度距离对资金要素的阻碍作用通常高于对人流要素的作用，而资源制度距离则没有明显差异；（2）两类制度距离的空间格局较为相似，都市圈内的耦合协调水平普遍高于都市圈外，呈现明显的都市圈格局；（3）都市圈之间存在明显差异，上海都市圈的制度距离阻碍强度普遍较低，而杭州都市圈、南京都市圈则依次较高。通过柔性的区域制度空间的建构，削弱要素跨行政区流动的制度距离阻碍，是破解“行政区经济”等区域分割难题、推动区域经济空间联系加强的有效治理路径。

关键词: 区域经济一体化, 行政区, 制度距离, 耦合协调度, 长三角城市群

Yu WANG, Jinxiang ZHANG, Yujie WANG, Jieying YANG. Influence mechanism and measurement of "institutional distance" of administrative regions in regional economic integration:[J]. World Regional Studies, 2023, 32(11): 141-154.

王雨, 张京祥, 王玉洁, 杨洁莹. 行政区“制度距离”对区域经济一体化的影响机制及其测度[J]. 世界地理研究, 2023, 32(11): 141-154.

Figures/Tables 12

Fig.1 The influence mechanism of institutional distance on regional economic space

Fig.2 Research scope

Tab.1 Composition of metropolitan area members in the study area

都市圈	成员组成
上海都市圈	上海、苏州、无锡、常州、南通、嘉兴、宁波、舟山、湖州
南京都市圈	南京、镇江、扬州、淮安、马鞍山、常州
杭州都市圈	杭州、湖州、嘉兴、绍兴、衢州

Fig.3 Boundary system distance scoring rules

Tab.2 Evaluation index system of institutional distance

制度类型	评价方式	选取指标/单位	指标方向
边界制度距离（ $X 1$ ）	制度空间边界一体化程度	是否为同一省份	－
		是否为同一行政级别	－
		是否为同一都市圈内部	－
		是否同为2010年前的经济协调会成员	－
		是否为同一城市群内部	－
资源制度距离（ $X 2$ ）	制度空间资源差距	地方一般公共预算支出之差/万元	+
		每万人拥有专利授权数之差/件/万人	+
		每万人拥有公共汽（电）车数之差/辆/万人	+
		每万人拥有执业(助理)医师数之差/人/万人	+
		每万人拥有专任教师数之差/人/万人	+
		公共图书馆图书藏量之差/万册	+
		城镇职工基本医疗保险覆盖面之差/%	+

Tab.2 Evaluation index system of institutional distance

制度类型	评价方式	选取指标/单位	指标方向
边界制度距离（ $X 1$ ）	制度空间边界一体化程度	是否为同一省份	－
		是否为同一行政级别	－
		是否为同一都市圈内部	－
		是否同为2010年前的经济协调会成员	－
		是否为同一城市群内部	－
资源制度距离（ $X 2$ ）	制度空间资源差距	地方一般公共预算支出之差/万元	+
		每万人拥有专利授权数之差/件/万人	+
		每万人拥有公共汽（电）车数之差/辆/万人	+
		每万人拥有执业(助理)医师数之差/人/万人	+
		每万人拥有专任教师数之差/人/万人	+
		公共图书馆图书藏量之差/万册	+
		城镇职工基本医疗保险覆盖面之差/%	+

Tab.3 Types of coupling coordination degree and its classification criteria

耦合协调度（D）	0＜D≤0.3	0.3＜D≤0.4	0.4＜D≤0.5	0.5＜D≤0.7	0.7＜D≤1
耦合协调等级	严重失调	濒临失调	中度协调	良性协调	优质协调

Tab.4 Measurement of scale and direction of factor flow

要素类型	流动规模（双向和）	流动方向(双向差）
人口要素	$S L = L i j$ + $L j i$	$D L = L i j$ - $L j i$ \|
资金要素	$S V = V i j + V j i$	$D L =$ \| $V i j - V j i$ \|

Tab.4 Measurement of scale and direction of factor flow

要素类型	流动规模（双向和）	流动方向(双向差）
人口要素	$S L = L i j$ + $L j i$	$D L = L i j$ - $L j i$ \|
资金要素	$S V = V i j + V j i$	$D L =$ \| $V i j - V j i$ \|

Fig.4 Flow of people and capital in the Yangtze River Delta

Fig.5 The coupling coordination pattern of boundary institutional distance and factor flow scale

Tab.5 The city-pairs of various administrative barriers intensity of people flow elements of people flow elements and capital elements

行政壁垒类型	强度	城市组
人流要素行政壁垒	低	上海-苏州、南京-镇江、无锡-常州、宁波-绍兴、扬州-泰州、南京-马鞍山、杭州-金华、合肥-马鞍山
人流要素行政壁垒	高	无锡-湖州、宁波-嘉兴、绍兴-台州、镇江-泰州
资金要素行政壁垒	低	上海-苏州
资金要素行政壁垒	高	南京-常州、南京-泰州、无锡-苏州、常州-镇江、常州-泰州、苏州-泰州、宁波-嘉兴、绍兴-嘉兴、绍兴-台州、扬州-镇江、镇江-泰州、南京-马鞍山、合肥-马鞍山

Fig.6 Coupling and coordinating pattern of resource institutional distance and factor flow direction

Tab.6 The city-pairs of various administrative intervention intensity of people flow and capital elements

行政干预类型	强度	城市组
人流要素行政干预	低	南京-扬州、南京-镇江、无锡-泰州、宁波-舟山、宁波-台州、金华-衢州、合肥-马鞍山
人流要素行政干预	高	常州-泰州、绍兴-嘉兴、扬州-镇江、扬州-泰州、镇江-泰州、南通-盐城、绍兴-金华
资金要素行政干预	低	南京-扬州、无锡-苏州、宁波-舟山、宁波-台州、绍兴-台州
资金要素行政干预	高	南京-常州、南京-镇江、南京-泰州、常州-镇江、苏州-泰州、杭州-嘉兴、杭州-绍兴、湖州-嘉兴、宁波-绍兴、扬州-镇江、镇江-泰州、合肥-马鞍山

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