京津冀城市群制造业结构变迁与空间集聚影响因素分析

doi:10.13249/j.cnki.sgs.2020.11.017

Abstract

Abstract:

The manufacturing industry plays an increasingly important role in supporting the national economy. Meanwhile, as a major historical decision of China, the Beijing-Tianjing-Hebei coordinated development strategy has entered into a new stage. Therefore, it is of great impetus and solid foundation in promoting the region to build a world-class competitive Urban Agglomeration by exploring the answers to the following two questions: the first is what are the characteristics of the spatial distribution and agglomeration trend of manufacturing industry in this region? The other is what are the factors that cause the variation of the latter? Essentially, the transferring and diffusion process of manufacturing industry under the spatial layout involves multiple dimensions. Therefore, based on the revised geographic aggregation index (EG), spatial econometric methods such as spatial lag model (SLM) and spatial error model (SEM) are constructed systematically to analyze the characteristics of spatial variation trend and influencing factors of manufacturing industry in Beijing-Tianjin-Hebei Urban Agglomeration. In addition to the deduction that the spatial distribution of different types of manufacturing industry has different characteristics, through rigorous calculation and analysis, the research also obtains the following conclusions: 1) Compared with Hebei Province, the characteristics of transfer and diffusion of technology intensive manufacturing industry in Beijing and Tianjin are more obvious; 2) Capital factors have a significant promoting effect on manufacturing agglomeration in Beijing-Tianjin-Hebei Urban Agglomeration, while the impact of knowledge intensity on manufacturing agglomeration in the region is not significant, and unlike the former two, the influence of labor factor intensity is negative; 3) The level of financial interest rates has a prominent negative correlation with manufacturing agglomeration, on the contrary, government intervention and macro tax burden have a positive promotion on manufacturing agglomeration; 4) The improvement of transportation infrastructure and the expansion of market scale can effectively stimulate the agglomeration of manufacturing industry in Beijing-Tianjin-Hebei region, however, the effect of foreign direct investment (FDI) have a negative correlation with the agglomeration of manufacturing industry in Beijing-Tianjin-Hebei Urban Agglomeration. At the end of this paper, the conclusions of spatial lag model (SLM) and spatial error model (SEM) can be used to put forward some comprehensive suggestions and measures for formulating reasonable spatial layout and long-term development strategy of manufacturing industry in Beijing-Tianjin-Hebei Urban Agglomeration.

Key words: Beijing-Tianjin-Hebei Urban Agglomeration, manufacturing industry structure, spatial agglomeration, influence factors

CLC Number:

F061.5

Zhou Wei, Zhao Yan, Ning Xuan. Manufacturing Industry Structure Changes and Spatial Agglomeration Influence Factors in Beijing-Tianjin-Hebei Urban Agglomeration[J].SCIENTIA GEOGRAPHICA SINICA, 2020, 40(11): 1921-1929.

Figures/Tables 5

	基本模型	空间面板滞后模型（SLM）				空间面板误差模型（SEM）
变量	FE	nonF	sF	tF	stF	nonF	sF	tF	stF
注：表4中、和**分别表示在10%、5%的和1%的检验水平上显著；括号内数值为t值;FE为固定效应；nonF：非固定效应；sF:空间固定效应；tF:时间固定效应；stF:时空固定效应；ρ:空间回归系数；λ:空间误差系数；R-squared：回归平方和占总离差平方和比重；LM-Lag：拉格朗日乘数滞后；R-LM（Lag）：稳健的拉格朗日乘数滞后检验；LM-Error：格朗日乘数误差检验；Log-L：对数似然函数；AR（1）-P：1阶自回归P值；AR（2）-P：2阶自回归P值；Hansen-P：Hansen检验P值。
_cons	1.727*** （8.81）
Cap	0.131*** （4.57）	0.130*** （6.71）	0.136*** （7.07）	0.115*** （5.78）	0.127*** （6.51）	0.185*** （8.32）	0.191*** （8.79）	0.167*** （7.56）	0.186*** （8.58）
Know	?0.048 （?0.64）	?0.055 （?1.01）	?0.072 （?1.33）	?0.058 （?1.08）	?0.071 （?1.32）	?0.003 （?0.06）	?0.033 （?0.61）	?0.006 （?0.12）	?0.032 （?0.55）
Lab	?0.163*** （?6.89）	?0.01*** （?1.91）	?0.03*** （?2.65）	?0.04*** （?2.91）	?0.04*** （?2.81）	0.020** （2.33）	?0.028** （?2.20）	?0.033** （?2.43）	?0.031** （?2.37）
Fin	?0.203*** （?9.06）	?0.182*** （?10.53）	?0.169*** （?10.03）	?0.248*** （?13.46）	?0.231*** （?12.74）	?0.297*** （?14.77）	?0.301*** （?15.11）	?0.327*** （?16.09）	?0.312*** （?15.60）
Gov	0.109*** （7.19）	0.073*** （7.21）	0.074*** （6.97）	0.040*** （3.51）	0.051*** （4.49）	0.076*** （6.32）	0.066*** （5.18）	0.045*** （3.53）	0.059*** （4.63）
Tax	0.866*** （8.21）	0.333*** （4.86）	0.322*** （4.62）	0.344*** （4.92）	0.298*** （4.27）	0.278*** （3.67）	0.305*** （4.05）	0.343*** （4.53）	0.308*** （4.10）
Tra	0.033*** （6.99）	0.034*** （10.94）	0.031*** （9.16）	0.035*** （10.13）	0.034*** （9.93）	0.056*** （15.00）	0.046*** （11.34）	0.048*** （11.82）	0.047*** （11.54）
Mar	0.015* （1.71）	0.0002 （0.04）	0.004 （0.78）	0.008 （1.49）	0.008 （1.44）	?0.001 （?0.13）	0.010 （1.53）	0.011* （1.65）	0.012* （1.80）
Fdi	?0.076** （?2.57）	?0.048** （?2.26）	?0.046** （?2.20）	?0.026 （?1.21）	?0.027 （?1.29）	?0.039* （?1.72）	?0.035 （?1.59）	?0.029 （?1.29）	?0.030 （?1.39）
ρ		0.676*** （34.78）	0.685*** （36.07）	0.611*** （27.52）	0.627*** （29.26）
λ						0.753*** （39.63）	0.777*** （44.02）	0.704*** （32.55）	0.732*** （36.34）
R-squared	0.309	0.578	0.628	0.592	0.640	0.256	0.334	0.388	0.444
LM-Lag		204.45***	203.60***	138.51***	148.25***	1800.13***	753.26***	559.25***	590.96***
R-LM（Lag）		143.26***	122.46***	36.50***	37.92***	706.28***	93.47***	9.058***	9.33***
LM-Error		109.26***	114.30***	103.17***	110.96***	1174.50***	122.51***	790.89***	855.24***
R-LM（Error）		48.07***	33.16***	1.166	0.63	80.66***	582.72***	240.70***	273.62***
Log-L		1034.3	1125.4	1079.6	1168.0	1113.1	1221.9	1141.7	1238.2
AR（1）-P	0.000
AR（2）-P	0.706
Hansen-P	0

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类型	2007年	2015年
注：γ为产业集聚指数。
低集聚水平（γ<0.02）	无	有色金属冶炼及压延加工业
中等集聚水平（0.02≤γ<0.05）	文教体育用品制造业；有色金属冶炼及加工业	食品制造；文教体育用品制造；交通运输设备制造业
高集聚水平 ^{（γ≥0.05）}	农副食品；食品；饮料；烟草；纺织业；纺织服装；皮革；木材加工；家具；造纸；印刷业；橡胶和塑料；其他；石油加工、炼焦及核燃料；非金属矿物；黑色金属冶炼；金属制品；通用设备；专用设备；仪器仪表；办公用机械；化学原料；医药；化学纤维；交通运输；电气机械；通信设备	农副食品；饮料；烟草；纺织业；纺织服装；皮革制品；木材加工；家具；造纸及纸制品；印刷业；橡胶和塑料；工艺品及其他；石油加工；炼焦及核燃料；非金属矿物；黑色金属冶炼；金属；其他；通用设备；专用设备；仪器仪表；办公用机械；化学原料；医药；化学纤维

产业部门	行业名称	2007年	2015年
劳动力密集型制造业	农副食品加工业	0.4566	0.5323
	食品制造业	0.3182	0.0651
	饮料制造业	0.3972	0.6560
	烟草制品业	0.5136	0.6757
	纺织业	1.0514	1.5796
	纺织服装、鞋、帽制造业	0.2876	0.2057
	皮革、毛皮、羽毛（绒）及其制品业	1.1448	1.6422
	木材加工及木、竹、藤、棕、草制品业	0.9662	1.5039
	家具制造业	0.3988	0.5950
	造纸及纸制品业	0.5041	0.5429
	印刷业和记录媒介的复制	0.7585	0.6829
	文教体育用品制造业	0.0292	0.0486
	橡胶和塑料制品业	0.3037	0.5888
	工艺品及其他制造业	0.5428	0.1766
资本密集型制造业	石油加工、炼焦及核燃料加工业	0.2711	0.2703
	非金属矿物制品业	0.6671	0.9319
	黑色金属冶炼及压延加工业	0.4771	0.6421
	有色金属冶炼及压延加工业	0.0669	0.0181
	金属制品业	0.2835	0.5122
	通用设备制造业	0.1760	0.2141
	专用设备制造业	0.3567	0.2419
	仪器仪表及文化、办公用机械制造业	0.5956	0.9549
技术密集型制造业	化学原料及化学制品制造业	0.3225	0.4838
	医药制造业	0.2239	0.4779
	化学纤维制造业	0.7904	0.9741
	交通运输设备制造业	0.2019	0.0322
	电气机械及器材制造业	0.1606	0.4165
	通信设备、计算机及其他电子设备制造	0.4712	0.3041

变量名		符号	变量解释	预期影响
注：“+”表示正向影响；“?”表示负向影响；“？”表示不确定。
因变量	区位商	Y_i	$ \dfrac{ i{\text{区域制造业总产值} }/{i} {\text{区域} }{\rm{GDP} } }{ {\text{全国制造业总产值} }/{\text{全国} }{\rm{GDP} } } $
解释变量	资本密集度	Cap	固定资产净产值/GDP	+
	知识密集度	Know	各区县普通中学专任教师人数/在岗职工总人数	+
	劳动密集度	Lab	在岗职工平均工资水平（万元）	？
	金融利率	Fin	年末居民储蓄存款余额/当年GDP	?
	政府干预度	Gov	GDP/财政支出	+
	宏观税负	Tax	财政收入/GDP	+
控制变量	交通基础设施	Tra	各区县（市）公路里程（km）	+
	市场规模	Mar	地区生产总值（亿元）	+
	外商投资规模	Fdi	外商投资企业产值（规模以上企业）/规模以上工业总产值	+

Manufacturing Industry Structure Changes and Spatial Agglomeration Influence Factors in Beijing-Tianjin-Hebei Urban Agglomeration

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