The effect of technological relatedness and land finance on regional industrial evolution

doi:10.3969/j.issn.1004-9479.2022.05.2021112

Abstract

Abstract:

Regional industrial evolution is realized through the entry and exit of industries, which is a kind of creative destruction. The new industry creates a new development path for the region. The evolution of regional industries is driven by both the internal innovation of the industry and the external regional institutional environment. Regional endogenous force are manifested in technological relatedness, which dominates the new paths creation of regional industries; and exogenous forces, such as institutions and policies, will change the new path creation of regional industries. This article used industrial evolution to represent regional development and explored the impact of local land finance on industrial evolution. Based on the China city land transfer revenue data and the industrial enterprise databases, this article described the temporal and spatial differentiation characteristics of land finance and industrial evolution across the country over the years. Further used the Logit model to demonstrate the impact of land finance on industrial evolution on the city-4-digit industry scale. The research found that: ①Technological relatedness promotes the emergence of new industrial paths in the region. ②Land finance generally inhibits the creation of new paths on regional industries. ③Urban land finance dependence generally intensifies the path dependence of local industry evolution. ④There are regional differences in the impact of land finance on industrial evolution: in Eastern China, land supply restriction prevents the region from giving full play to its potential, and land finance can promote the endogenous development power of the region, which manifested as the path dependence of regional development. In Middle China, the industrial evolution was path-breaking during the research period, and the expansion effect of land finance promoted the regional development and its path breakthrough. In Western China, new paths creation is path-dependent, land finance has exceeded the potential of industrial development and restrained regional development. In Northeast China, paths creation is path-dependent, and land supply growth brought by land finance promotes regional development.

Key words: industry evolution, land finance, land transfer revenue, regional development, path dependence

摘要：

区域产业演化是新产业进入、旧产业退出的过程，新产业为区域创造新发展路径。受本地技术关联驱动，区域产业演化表现出路径依赖，而外生的制度因素可以改变新路径的方向。基于中国城市土地出让收入数据及工业企业数据库，分析历年土地财政和产业演化的时空分异特征，并利用Logit条件回归模型在城市-产业尺度实证检验技术关联与土地财政对区域产业演化的影响。研究发现：①技术关联促进了中国区域产业新路径产生。②土地财政总体上阻碍了中国区域产业新路径的产生。③城市的土地财政依赖总体上加剧了产业演化的路径依赖，阻碍了我国产业突破既有发展路径和实现转型升级。④土地财政对产业演化的影响存在区域差异：在东部地区，土地供给增长显著促进区域产业发展；土地财政促进了区域内生产业发展，强化了技术关联对产业发展新路径的积极效应。在中部，土地财政的扩张效应促进了区域发展及其路径突破，区域产业演化受产业转移影响，不受本地技术关联驱动。在西部，土地财政抑制了区域发展，本地技术关联的影响不显著。在东北，土地财政带来的土地供给增长有助于区域产业发展，产业演化存在路径依赖。

关键词: 产业演化, 土地财政, 土地出让收入, 区域发展, 路径依赖

Qi ZHAO, Shengjun ZHU. The effect of technological relatedness and land finance on regional industrial evolution[J]. World Regional Studies, 2022, 31(5): 953-966.

赵琪, 朱晟君. 技术关联与土地财政对区域产业演化的影响[J]. 世界地理研究, 2022, 31(5): 953-966.

Figures/Tables 9

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变量	指标	计量方式
nsop	市场化	非国有制企业产值占总产值的比重
fdip	全球化	FDI占GDP的比重
pgdp	经济发展水平	人均GDP
wage	劳动力素质	平均工资
inno	本地创新能力	复旦大学《中国城市和产业创新力报告》
labo	劳动力数量	城市单位从业人口与私营及个体从业人口总和
luse	土地利用效率	单位建成区面积产出的二、三产业总产值
urba	土地供给存量	城市建成区面积

变量	指标	计量方式
nsop	市场化	非国有制企业产值占总产值的比重
fdip	全球化	FDI占GDP的比重
pgdp	经济发展水平	人均GDP
wage	劳动力素质	平均工资
inno	本地创新能力	复旦大学《中国城市和产业创新力报告》
labo	劳动力数量	城市单位从业人口与私营及个体从业人口总和
luse	土地利用效率	单位建成区面积产出的二、三产业总产值
urba	土地供给存量	城市建成区面积

时期	样本量	平均值	中位数	标准差.	最小值	最大值
2006—2018	2 240	38.37972	27.43009	41.19316	0.00036	438.6201
2006—2010	654	39.3032	26.49436	43.83243	0.000647	438.6201
2011—2015	995	34.39605	27.88539	30.9323	0.013287	222.1311

时期	样本量	平均值	中位数	标准差.	最小值	最大值
2006—2018	2 240	38.37972	27.43009	41.19316	0.00036	438.6201
2006—2010	654	39.3032	26.49436	43.83243	0.000647	438.6201
2011—2015	995	34.39605	27.88539	30.9323	0.013287	222.1311

变量	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
landfin	-0.195^***			-0.216^***	-0.685^***	-0.222^***		-0.255^***	-0.667^***
	(0.0519)			(0.0523)	(0.162)	(0.0619)		(0.0624)	(0.195)
density		5.618^***		6.692^***	5.968^***		5.617^***	6.560^***	5.889^***
		(0.280)		(0.336)	(0.410)		(0.351)	(0.413)	(0.510)
landsup			10.85^***			11.47^***	9.519^***	9.809^***	9.665^***
			(2.259)			(2.386)	(2.250)	(2.384)	(2.383)
landfin×density					1.727^***				1.497^**
					(0.563)				(0.669)
nsop	-0.933^***	-1.484^***	-0.868^***	-1.949^***	-1.934^***	-1.337^***	-1.753^***	-2.504^***	-2.479^***
	(0.281)	(0.230)	(0.271)	(0.289)	(0.289)	(0.325)	(0.281)	(0.338)	(0.338)
fdip	0.946	2.791^*	3.148^*	0.0844	0.296	1.159	3.083^*	0.295	0.477
	(1.823)	(1.503)	(1.798)	(1.823)	(1.826)	(2.098)	(1.799)	(2.096)	(2.100)
pgdp	0.106^*	-0.0124	0.0355	0.0841	0.0868	0.122^*	0.0237	0.107	0.111
	(0.0597)	(0.0449)	(0.0563)	(0.0601)	(0.0602)	(0.0713)	(0.0566)	(0.0717)	(0.0717)
wage	0.359^***	0.552^***	0.321^***	0.426^***	0.450^***	0.216^**	0.401^***	0.286^***	0.304^***
	(0.0906)	(0.0677)	(0.0824)	(0.0914)	(0.0917)	(0.109)	(0.0830)	(0.110)	(0.110)
labo	0.697	-0.454	-1.100	0.652	0.377	0.232	-1.057	0.544	0.316
	(0.934)	(0.844)	(0.987)	(0.940)	(0.944)	(1.073)	(0.992)	(1.079)	(1.084)
inno	-0.0136	0.0101	0.0412	-0.000254	-0.00310	0.0328	0.0486^*	0.0398	0.0380
	(0.0260)	(0.0259)	(0.0285)	(0.0266)	(0.0266)	(0.0292)	(0.0289)	(0.0297)	(0.0298)
luse	-0.741	-0.802	-0.357	-0.0336	-0.350	-0.568	-0.280	0.157	-0.0953
	(1.318)	(1.031)	(1.209)	(1.331)	(1.338)	(1.472)	(1.215)	(1.483)	(1.490)
urba	0.742	1.170	1.786^*	1.350	1.350	1.567	1.973^*	2.003^*	2.012^*
	(0.992)	(0.892)	(1.050)	(0.989)	(0.987)	(1.149)	(1.042)	(1.142)	(1.140)
i.city	included	included	included	included	included	included	included	included	included
_cons	-2.107^***	-3.285^***	-1.934^***	-3.408^***	-3.219^***	-1.611^***	-2.955^***	-2.791^***	-2.630^***
	(0.350)	(0.296)	(0.348)	(0.360)	(0.365)	(0.410)	(0.356)	(0.420)	(0.426)
N	40327	54674	36451	40327	40327	28332	36451	28332	28332