京津冀地区制造业空间格局演化及其驱动因素

doi:10.18306/dlkxjz.2021.05.001

地理科学进展 ›› 2021, Vol. 40 ›› Issue (5): 721-735.doi: 10.18306/dlkxjz.2021.05.001

• 研究论文 • 下一篇

京津冀地区制造业空间格局演化及其驱动因素

蒋海兵¹(), 李业锦²^,^*()

1.盐城师范学院城市与规划学院,江苏盐城 224002
2.首都师范大学资源环境与旅游学院,北京 100048

收稿日期:2020-06-19 修回日期:2020-12-14 出版日期:2021-05-28 发布日期:2021-07-28
通讯作者: *李业锦(1977— ),男,海南澄迈人,博士,副教授,中国地理学会会员,研究方向为宜居城市、产业经济与规划等。E-mail:plansky@qq.com
作者简介:蒋海兵(1978— ),男,江苏建湖人,博士,副教授,中国地理学会会员,研究方向为城市和区域发展、产业布局等。E-mail:haibingjiang1@163.com
基金资助:
江苏省社会科学基金项目(18GLB014);江苏高校“青蓝工程”资助项目;盐城师范学院“高端人才支持计划”项目;国家自然科学基金项目(41001105)

Change of spatial structure of manufacturing industry in the Beijing-Tianjin-Hebei region and its driving factors

JIANG Haibing¹(), LI Yejin²^,^*()

1. School of Urban and Planning, Yancheng Teachers University, Yancheng 224002, Jiangsu, China
2. College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China

Received:2020-06-19 Revised:2020-12-14 Online:2021-05-28 Published:2021-07-28
Supported by:
Social Science Foundation of Jiangsu Province, No. 18GLB014(18GLB014);"Qinglan Project" of Jiangsu Universities;"High-end Talents Support Plan" Project of Yancheng Teachers University;National Natural Science Foundation of China(41001105)

摘要/Abstract

摘要：

京津冀地区产业转移升级、协同发展和先进制造业深度融合发展战略对制造业产业集群的空间布局提出更高要求。论文基于2000—2013年京津冀地区规模以上工业企业微观数据,运用核密度分析法和面板数据回归模型等方法,探究京津冀地区制造业空间格局演化特征及其驱动因素。结果表明：① 京津冀地区全部制造业总体格局相对稳定,高值区集聚于京津唐地区。资本密集型产业区域联动发展势头明显;技术密集型产业则日趋集中于少数区县,且与周边区县空间自相关程度整体弱化;劳动密集型产业区县邻近扩张与疏散转移发展交替出现。区域联动发展促进各地制造业均衡增长,缩小了区域制造业发展差距。② 京津冀地区制造业呈现出明显专业化地域分工趋势。劳动密集型产业日益向中心城市城区外围及中南部县区集中扩散;资本密集型产业集聚于环渤海西岸产业带,京津冀外围地区产业产值大幅度增加;技术密集型产业扎堆于京津高科技产业带。③ 3类制造业的关键驱动因素有所差异。劳动力密集型产业受投资和交通可达性影响;资本密集型产业对本地市场规模和投资依赖性强,受交通可达性影响弱;技术密集型产业主要受制于交通可达性与工资水平。3类制造业均明显受到地方财政支出作用影响。研究可为城市群先进制造业产业空间优化提供参考依据。

关键词: 制造业, 核密度分析, 面板回归模型, 驱动因素, 京津冀地区

Abstract:

The development strategy of industrial transfer and upgrading, coordinated development, and in-depth integration of advanced manufacturing in the Beijing-Tianjin-Hebei region put forward higher requirements for the spatial layout of manufacturing industrial clusters. Research on the change of manufacturing industry spatial pattern can provide a reference for the optimization of urban agglomerations' advanced manufacturing industries. Based on the micro-level data of industrial enterprises above designated size in the Beijing-Tianjin-Hebei region from 2000 to 2013, this study used kernal density analysis and panel data regression models to explore the characteristics and driving factors of the change of the manufacturing industry spatial pattern in the region. The results of this empirical research show that: 1) The overall spatial pattern of all manufacturing industries in the Beijing-Tianjin-Hebei region is relatively stable, and high-value areas are concentrated in the Beijing-Tianjin-Tangshan area. The regional linked development of capital-intensive industries is gaining momentum; technology-intensive industries are increasingly concentrated in a few districts and counties, and the degree of spatial autocorrelation with surrounding districts and counties has weakened as a whole; spatial expansion into nearby districts and counties and spatial transfer of labor-intensive industries appeared alternately; and the regional linked development promotes the balanced growth of manufacturing industries in various regions and narrows the development gap. 2) The manufacturing industry in the Beijing-Tianjin-Hebei region shows a clear trend of specialization and regional division of labor, and labor-intensive industries are increasingly spreading to the periphery of the central cities and the counties in the central and southern areas of the region. Capital-intensive industries are concentrated in the industrial belt on the west coast of the Bohai Sea, the industrial output value of the peripheral areas of the region has increased significantly, and technology-intensive industries are gathered in the Beijing-Tianjin high-tech industrial belt. 3) The key driving factors of the three types of manufacturing industries are different. Labor-intensive industries are affected by investment and transportation accessibility. Capital-intensive industries are highly dependent on local market size and investment, and are insensitive to transportation accessibility. Technology-intensive industries are mainly constrained by transportation accessibility and wage levels. The three types of manufacturing industries are obviously affected by local fiscal expenditures.

Key words: manufacturing industry, kernal density analysis, panel data regression model, driving factors, Beijing-Tianjin-Hebei region

蒋海兵, 李业锦. 京津冀地区制造业空间格局演化及其驱动因素[J]. 地理科学进展, 2021, 40(5): 721-735.

JIANG Haibing, LI Yejin. Change of spatial structure of manufacturing industry in the Beijing-Tianjin-Hebei region and its driving factors[J]. PROGRESS IN GEOGRAPHY, 2021, 40(5): 721-735.

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参考文献 25

[1]	Krugman P. First nature, second nature, and metropolitan location[J]. Journal of Regional Science, 1993,33(2):129-144. doi: 10.1111/jors.1993.33.issue-2
[2]	冯云廷. 城市经济学 [M]. 5版. 大连: 东北财经大学出版社, 2018.
	[Feng Yunting. Urban economics. 5th Edition. Dalian, China: Dongbei University of Finance and Economics Press, 2018. ]
[3]	贺灿飞, 胡绪千. 1978 年改革开放以来中国工业地理格局演变[J]. 地理学报, 2019,74(10):1962-1979. doi: 10.11821/dlxb201910002
	[He Canfei, Hu Xuqian. Evolution of Chinese industrial geography since reform and opening-up. Acta Geographica Sinica, 2019,74(10):1962-1979. ]
[4]	贺灿飞, 谢秀珍, 潘峰华. 中国制造业省区分布及其影响因素[J]. 地理研究, 2008,27(3):623-635.
	[He Canfei, Xie Xiuzhen, Pan Fenghua. Locational studies of Chinese manufacturing industries. Geographical Research, 2008,27(3):623-635. ]
[5]	刘红光, 王云平, 季璐. 中国区域间产业转移特征、机理与模式研究[J]. 经济地理, 2014,34(1):102-107.
	[Liu Hongguang, Wang Yunping, Ji Lu. Characteristics, mechanism and pattern of inter-regional industry transfers in China. Economic Geography, 2014,34(1):102-107. ]
[6]	石敏俊, 杨晶, 龙文, 等. 中国制造业分布的地理变迁与驱动因素[J]. 地理研究, 2013,32(9):1708-1720. doi: 10.11821/dlyj201309013
	[Shi Minjun, Yang Jing, Long Wen, et al. Changes in geographical distribution of Chinese manufacturing sectors and its driving forces. Geographical Research, 2013,32(9):1708-1720. ]
[7]	金煜, 陈钊, 陆铭. 中国的地区工业集聚: 经济地理、新经济地理与经济政策[J]. 经济研究, 2006,41(4):79-89.
	[Jin Yu, Chen Zhao, Lu Ming. Industry agglomeration in China: Economic geography, new economic geography and policy. Economic Research Journal, 2006,41(4):79-89. ]
[8]	张晓平, 孙磊. 北京市制造业空间格局演化及影响因子分析[J]. 地理学报, 2012,67(10):1308-1316.
	[Zhang Xiaoping, Sun Lei. Manufacture restructuring and main determinants in Beijing metropolitan area. Acta Geographica Sinica, 2012,67(10):1308-1316. ]
[9]	刘霄泉, 孙铁山, 李国平. 基于局部空间统计的产业集群空间分析: 以北京市制造业集群为例[J]. 地理科学, 2012,32(5):530-535. doi: 10.13249/j.cnki.sgs.2012.05.530
	[Liu Xiaoquan, Sun Tieshan, Li Guoping. Spatial analysis of industry clusters based on local spatial statistics: A case study of Beijing's manufacturing industry clusters. Scientia Geographica Sinica, 2012,32(5):530-535. ]
[10]	陈松林, 陈进栋, 韦素琼. 福建省综合交通可达性格局及其与制造业空间分布的关系分析[J]. 地理科学, 2012,32(7):807-815. doi: 10.13249/j.cnki.sgs.2012.07.807
	[Chen Songlin, Chen Jindong, Wei Suqiong. The integrated transportation accessibility in Fujian Province and its correlation with the spatial distribution of manufacturing. Scientia Geographica Sinica, 2012,32(7):807-815. ]
[11]	沈静, 向澄, 柳意云. 广东省污染密集型产业转移机制: 基于2000—2009年面板数据模型的实证[J]. 地理研究, 2012,31(2):357-368.
	[Shen Jing, Xiang Cheng, Liu Yiyun. The mechanism of pollution-intensive industry relocation in Guangdong Province, 2000-2009. Geographical Research, 2012,31(2):357-368. ]
[12]	仇方道, 蒋涛, 张纯敏, 等. 江苏省污染密集型产业空间转移及影响因素[J]. 地理科学, 2013,33(7):789-796. doi: 10.13249/j.cnki.sgs.2013.07.789
	[Qiu Fangdao, Jiang Tao, Zhang Chunmin, et al. Spatial relocation and mechanism of pollution-intensive industries in Jiangsu Province. Scientia Geographica Sinica, 2013,33(7):789-796. ]
[13]	张杰, 唐根年. 浙江省制造业空间分异格局及其影响因素[J]. 地理科学, 2018,38(7):1107-1117. doi: 10.13249/j.cnki.sgs.2018.07.012
	[Zhang Jie, Tang Gennian. Spatial differentiation pattern of manufacturing industry in Zhejiang and its influencing factors. Scientia Geographica Sinica, 2018,38(7):1107-1117. ]
[14]	王俊松. 长三角制造业空间格局演化及影响因素[J]. 地理研究, 2014,33(12):2312-2324. doi: 10.11821/dlyj201412009
	[Wang Junsong. Evolution of spatial pattern and influencing factors of manufacturing industries in Yangtze River Delta region. Geographical Research, 2014,33(12):2312-2324. ]
[15]	李燕, 贺灿飞. 1998—2009年珠江三角洲制造业空间转移特征及其机制[J]. 地理科学进展, 2013,32(5):777-787. doi: 10.11820/dlkxjz.2013.05.009
	[Li Yan, He Canfei. Characteristics and mechanism of manufacturing industry shift in the Pearl River Delta during 1998-2009. Progress in Geography, 2013,32(5):777-787. ]
[16]	周锐波, 李晓雯. 广东省制造业空间格局演化及其影响因素研究[J]. 人文地理, 2017,32(2):95-102.
	[Zhou Ruibo, Li Xiaowen. Evolution of spatial pattern and influencing factors of manufacturing industries in Guangdong Province. Human Geography, 2017,32(2):95-102. ]
[17]	刘汉初, 樊杰, 张海朋, 等. 珠三角城市群制造业集疏与产业空间格局变动[J]. 地理科学进展, 2020,39(2):195-206. doi: 10.18306/dlkxjz.2020.02.002
	[Liu Hanchu, Fan Jie, Zhang Haipeng, et al. Dynamics of manufacturing industry and change of its spatial pattern in the Pearl River Delta urban agglomeration. Progress in Geography, 2020,39(2):195-206. ]
[18]	李国平, 张杰斐. 京津冀制造业空间格局变化特征及其影响因素[J]. 南开学报(哲学社会科学版), 2015(1):90-96.
	[Li Guoping, Zhang Jiefei. The features of the changes in the geographical pattern of manufacturing sector in Jing-Jin-Ji Region and the influencing factors of these changes. Nankai Journal (Philosophy, Literature and Social Science Edition), 2015(1):90-96. ]
[19]	张杰斐, 席强敏, 孙铁山, 等. 京津冀区域制造业分工与转移[J]. 人文地理, 2016,31(4):95-101, 160.
	[Zhang Jiefei, Xi Qiangmin, Sun Tieshan, et al. Industrial division and transfer of manufacture in Beijing-Tianjin-Hebei region. Human Geography, 2016,31(4):95-101, 160. ]
[20]	鲁金萍, 刘玉, 杨振武, 等. 京津冀区域制造业产业转移研究[J]. 科技管理研究, 2015(11):86-89, 94.
	[Lu Jinping, Liu Yu, Yang Zhenwu, et al. Study on manufacturing industry transfer in Jing-Jin-Ji region. Science and Technology Management Research, 2015(11):86-89, 94. ]
[21]	席强敏, 季鹏. 京津冀高技术制造业空间结构演变的经济绩效[J]. 经济地理, 2018,38(11):112-122.
	[Xi Qiangmin, Ji Peng. Economic performance of spatial structure evolution of high technology manufacturing in Beijing-Tianjin-Hebei. Economic Geography, 2018,38(11):112-122. ]
[22]	孙久文, 姚鹏. 京津冀产业空间转移、地区专业化与协同发展: 基于新经济地理学的分析框架[J]. 南开学报(哲学社会科学版), 2015(1):81-89.
	[Sun Jiuwen, Yao Peng. Industrial relocation in Jing-Jin-Ji region, regional specialization and coordinated development: An analysis based on the framework of new economic geography. Nankai Journal (Philosophy, Literature and Social Science Edition), 2015(1):81-89. ]
[23]	尹海伟, 罗震东, 耿磊. 城市与区域规划空间分析应用 [M]. 南京: 东南大学出版社, 2015.
	[Yin Haiwei, Luo Zhendong, Geng Lei. The spatial analysis methods in urban and regional planning. Nanjing, China: Southeast University Press, 2015. ]
[24]	张文忠. 产业发展和规划的理论与实践 [M]. 北京: 科学出版社, 2009.
	[Zhang Wenzhong. Theory and practice of industrial development and planning. Beijing, China: Science Press, 2009.]
[25]	赵济, 陈传康. 中国地理[M]. 北京: 高等教育出版社, 1999.
	[Zhao Ji, Chen Chuankang. Geography of China. Beijing, China: Higher Education Press, 1999. ]

行业类型	包含行业及其代码
劳动密集型产业	13. 农副食品加工业,14. 食品制造业,15. 酒、饮料和精制茶制造业,16. 烟草制品业,17. 纺织业,18. 纺织服装、服饰业,19. 皮革、毛皮、羽毛及其制品和制鞋业,20. 木材加工和木、竹、藤、草制品业,21. 家具制造业,22. 造纸和纸制品业, 23. 印刷和记录媒介复制业,24. 文教、工美、体育和娱乐用品制造业,41. 其他制造业,42. 废弃资源综合利用业
资本密集型产业	25. 石油、煤炭及其他燃料加工业,26. 化学原料和化学制品制造业,28. 化学纤维制造业,29. 橡胶和塑料制品业,30. 非金属矿物制品业,31. 黑色金属冶炼和压延加工业,32. 有色金属冶炼和压延加工业,33. 金属制品业
技术密集型产业	27. 医药制造业,34. 通用设备制造业,35. 专用设备制造业,36. 汽车制造业,37. 铁路、船舶、航空航天和其他运输设备制造业,38. 电气机械和器材制造业,39. 计算机、通信和其他电子设备制造业,40. 仪器仪表制造业

行业	大型企业
汽车制造业	现代汽车公司、长城河北公司、一汽丰田、北京奔弛、长城天津公司、福田、现代摩比斯、福田戴姆勒、中信戴卡、北方凌云、北京汽车等
电子信息产业	三星通信、诺基亚通信、索爱普天、三星视界、联想(北京)、小米通信、三星电子、京东方显示、钜宝电子、伟创力电子、三星高新电机、鸿富锦精密电子、富士康精密电子(廊坊)、三星LED、三星电机、同方股份等
钢铁产业	河北津西、唐山钢铁、河北敬业、天津天铁、天津钢铁、唐山瑞丰、宣化钢铁、首钢京唐钢铁、邯郸钢铁、沧州中铁装备、唐山国丰、承德钢铁、首钢迁安钢铁等
化工产业	中沙(天津)、大沽化工、唐山三友、天澜新能源、天津碱厂、燕山石化、旭阳煤石化、PPG涂料(天津)、天津渤天化工、冀衡、沧州大化等
食品加工制造业	天狮生物、康师傅方便面、嘉里粮油、汇福粮油、今麦郎食品、红玫瑰食品、金海粮油、顺鑫农业、顶益食品、九三集团、兴柏生物、邦基正大等
医药制造业	华北制药、石药集团、拜耳医药、诺和诺德、天士力集团、诺华制药、天士力制药、以岭药业、神威药业、赛诺菲(北京)制药、天津天药、北京同仁堂等
纺织业	宏润面料、恩达纺织、卢华服装、洪源纺织、天纺投资、常山纺织、恒纺纺织、三利毛纺、宁纺集团、恒进纺织、正大纺织、永亮纺织等、大华纺织等

年份	制造业总产值	劳动密集型	资本密集型	技术密集型
2000	57.37	69.23	45.62	62.82
2005	54.22	37.26	42.19	78.27
2013	47.67	41.96	32.87	68.81

变量	ln(Indu_it)		ln(Labor_it)		ln(Capi_it)		ln(Tech_it)
变量	系数	z值	系数	z值	系数	z值	系数	z值
ln(Pop_it)	-0.170^**	-2.27	-0.169	-1.41	-0.122	-0.96	0.034	0.29
ln(GDP_it)	0.229^***	6.71	0.038	0.72	0.061	1.11	-0.062	-1.25
ln(Invest_it)	0.325^***	11.00	0.362^***	7.82	0.390^***	7.96	0.337^***	7.63
ln(Fiscal_it)	0.479^***	9.61	0.413^***	5.3	0.437^***	5.3	0.539^***	7.23
ln(Salary_it)	0.217^***	3.02	0.142	1.25	-0.018	-0.15	0.456^***	4.15
ln(Consume_it)	0.132^***	2.96	0.051	0.73	0.289^***	3.93	0.060	0.91
ln(Acc_it)	-0.777^***	-4.66	-0.936^***	-3.04	-0.563^*	-1.69	-3.005^***	-9.03
常数	14.982^***	13.46	15.319 ^***	7.93	14.224^***	6.84	22.637^***	11.23
模型设定	随机模型		随机模型		随机模型		随机模型
R²	0.75		0.37		0.43		0.57
观测数	2117		1987		1991		1903

变量	ln(PCindu_it)		ln(PClabor_it)		ln(PCcapi_it)		ln(PCtech_it)
变量	系数	z值	系数	z值	系数	z值	系数	z值
ln(GDP_it)	0.214^***	6.32	0.029	0.55	0.048	0.87	-0.061	-1.22
ln(Invest_it)	0.320^***	10.88	0.360^***	7.78	0.385^***	7.89	0.338^***	7.66
ln(Fiscal_it)	0.468^***	9.46	0.399^***	5.16	0.431^***	5.28	0.541^***	7.33
ln(Salary_it)	0.273^***	3.98	0.185^*	1.69	0.025	0.21	0.448^***	4.20
ln(Consume_it)	0.097^**	2.29	0.024	0.36	0.265^***	3.75	0.066	1.02
ln(Acc_it)	-0.751^***	-4.43	-0.895^***	-2.93	-0.549	-1.61	-3.013^***	-9.12
常数	9.196^***	9.14	9.538^***	5.44	8.779^***	4.53	18.210	9.80
模型设定	随机模型		随机模型		随机模型		随机模型
R²	0.75		0.38		0.43		0.57
观测数	2117		1987		1991		1903

京津冀地区制造业空间格局演化及其驱动因素

Change of spatial structure of manufacturing industry in the Beijing-Tianjin-Hebei region and its driving factors

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