中国城市日企的同业与同源效应——以京、沪、广、深为例

doi:10.18306/dlkxjz.2020.11.006

摘要/Abstract

摘要：

日本外商直接投资(Foreign Direct Investment, FDI)企业在中国北京、上海和广深等典型城市高度集聚,现有研究一方面将FDI均质化处理,缺乏精细的产业划分,另一方面缺少国家内部的同源集聚分析,同时对典型城市集聚的异同性关注不够。为弥补研究不足,论文在集聚的研究基础上,重点关注日企集中分布的典型城市,对比其同业集聚效应和同源集聚效应。选取1984—2017年日本在北京、上海和广深的FDI企业级数据,利用多项Logistic回归分析方法,以广深为参照系,建立分别包括7个方程在内的同业集聚效应模型和同源集聚效应模型,同步考虑企业所属行业和价值链环节、进入模式与时间等企业异质性控制变量,分析京、沪、广深两效应的异同。研究结果表明：日企在中国典型城市的同业效应和同源效应异同性明显。具体表现在：第一,上海同业效应和异业效应最为显著,且结果稳健,广深同业效应略强于北京,但结果稳健性较差;第二,上海同源和异源效应结果稳健且显著,企业的追随效应较强,北京和广深差异较小;第三,企业属性变量的引入,有效提升了模型的解释力度。上海的日企进入时间较早,各地企业规模整体差别不大。上海日企进入模式以独资为主,北京和广深以合资为主,但独资化趋势明显;北京行业结构中服务业占比较高,广深制造业独大;广深和上海产业链环节中侧重生产制造和进出口贸易环节,北京商务服务和研发设计布局较多。

关键词: FDI, 集聚, 同源效应, 同业效应, 企业异质性

Abstract:

The distribution of Japanese foreign direct investment (FDI) companies in China is extremely uneven and these companies are highly concentrated in the Beijing, Shanghai, and Guangzhou-Shenzhen regions. Traditional FDI research has always focused on how urban attributes and conditions affect the location choice of companies. But the role of spatial agglomeration should be equally concerned. Existing research on agglomeration has shortcomings, such as homogenizing FDI and lack of detailed classification of industries, which lead to significant differences in the results of the studies. Whether companies will follow the investment location choice of other companies with the same source country has not received enough attention. At the same time, there is insufficient attention to the similarities and differences of typical urban agglomerations. To address these issues, based on the research of agglomeration and by focusing on typical cities where Japanese companies are concentrated, this study compared and analyzed the same industry agglomeration effect and the same source agglomeration effect. Using the FDI enterprise data of Japan in Beijing, Shanghai, and Guangzhou-Shenzhen in 1984 to 2017 and the multivariate logistic regression analysis method, with Guangzhou-Shenzhen as the reference region, we established the same industry agglomeration effect model and the same source agglomeration effect model, which includes seven equations each. Enterprise heterogeneity control variables such as industry and value chain links, entry mode, and entry time were added to the model to compare and analyze similarities and differences between Beijing, Shanghai, and Guangzhou-Shenzhen. The results show that the similarities and differences of the same industrial agglomeration effect and the agglomeration effects of the same source are obvious for Japanese companies in typical cities in China. Specifically: 1) Shanghai's same industrial agglomeration and cross-industry agglomeration are the most significant, and the results are stable. Guangzhou-Shenzhen's same industrial agglomeration is slightly stronger than Beijing, but the results are less robust. 2) The results of Shanghai's same source agglomeration are stable and significant and the agglomeration effect of enterprises is strong. The difference between Beijing and Guangzhou-Shenzhen is small. 3) The introduction of enterprise attribute variables has effectively improved the explanatory power of the model. The entry time of Japanese companies in Shanghai is earlier, and the overall size of enterprises across the country is not much different. The entry mode of Japanese enterprises in Shanghai is mainly sole proprietorship. In Beijing and Guangzhou-Shenzhen these companies are mainly joint ventures, but the increasing trend of sole proprietorship is obvious. The proportion of companies in the service industry is relatively high in Beijing, and the number of manufacturing companies is the largest in Guangzhou-Shenzhen. The Japanese companies in Guangzhou-Shenzhen and Shanghai focus on manufacturing or import and export trade in the industrial chain, and the number of companies specializing in business services and research and development is the highest in Beijing.

Key words: foreign direct investment (FDI), agglomeration, the same industry effect, the same source effect, company heterogeneity

刘玉潇, 王茂军. 中国城市日企的同业与同源效应——以京、沪、广、深为例[J]. 地理科学进展, 2020, 39(11): 1845-1859.

LIU Yuxiao, WANG Maojun. The same industry effect and the same source effect of Japanese companies in China: Take Beijing, Shanghai, Guangzhou and Shenzhen as examples[J]. PROGRESS IN GEOGRAPHY, 2020, 39(11): 1845-1859.

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指标		方程1	方程2	方程3	方程4	方程5	方程6	方程7
N		342	342	193	342	342	342	186
伪R²	Cox和Snell	0.183	0.226	0.178	0.218	0.288	0.278	0.670
	Nagelkerke	0.209	0.257	0.203	0.248	0.328	0.316	0.761
	McFadden	0.096	0.121	0.093	0.117	0.161	0.154	0.522
似然比显著性水平		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
分类百分比校正/%		49.40	47.70	47.20	51.80	56.70	54.00	78.50

变量	方程1		方程2		方程3		方程4		方程5		方程6		方程7
变量	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海
进入时间			0.104^**(0.025)	0.002^*(0.093)									0.143(0.391)	-1.373^***(<0.001)
企业规模					<0.001(0.173)	<0.001(0.286)							<0.001(0.794)	-0.001(0.177)
合资							-1.475^**(0.001)	-1.314^**(0.002)					-1.263^*(0.051)	-1.182(0.158)
生产制造									-2.519^***(<0.001)	-1.090^**(0.010)			-1.066(0.253)	2.857 (0.145)
商务服务									0.033(1.034)	0.035(0.941)			0.031(0.968)	3.290^*(0.062)
进出口贸易									-1.162^** (0.036)	-0.472(0.310)			-0.362(0.623)	3.719^**(0.035)
研发设计									-0.182(0.777)	-1.113^*(0.098)			-0.131(0.888)	3.978^*(0.065)
服务业											2.277^*** (<0.001)	0.742^**(0.012)	2.087^**(0.006)	-0.649(0.480)
同业集聚	0.008(0.700)	0.057^**(0.001)	-0.005(0.817)	0.056^**(0.001)	-0.005(0.879)	-0.028(0.270)	0.014(0.524)	0.062^*** (<0.001)	0.003(0.907)	-0.060^**(0.001)	0.006(0.804)	0.055^**(0.010)	-0.045(0.425)	0.282^**(0.003)
异业集聚	-0.006(0.218)	0.014^**(0.001)	-0.002^**(0.022)	0.014^**(0.001)	-0.008(0.269)	0.016^**(0.006)	-0.008(0.113)	0.012^**(0.004)	-0.014^**(<0.001)	-0.014^***(<0.001)	-0.016^**(0.007)	0.010^**(0.012)	-0.046(0.233)	0.210^*** (<0.001)
百分比校正/%	19.3	75.8	19.3	77.0	29.8	74.5	14.5	72.0	45.8	67.7	48.2	64.6	60.0	93.0

指标		方程1	方程2	方程3	方程4	方程5	方程6	方程7
N		342	340	187	342	342	342	186
伪R²	Cox和Snell	0.189	0.383	0.205	0.220	0.288	0.283	0.678
	Nagelkerke	0.215	0.436	0.233	0.251	0.328	0.322	0.771
	McFadden	0.099	0.229	0.108	0.118	0.161	0.158	0.535
似然比显著性水平		<0.001	<0.001	<0.001	<0.001	<0.001	<0.001	<0.001
分类百分比校正/%		47.10	66.20	47.10	51.20	56.10	54.70	78.00

变量	方程1		方程2		方程3		方程4		方程5		方程6		方程7
变量	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海	北京	上海
进入时间			0.185^**(0.006)	-0.487^***(<0.001)									0.093(0.579)	-1.392^** (<0.001)
企业规模					<0.001(0.204)	<0.001(0.401)							<0.001(0.996)	-0.001(0.199)
合资							-1.432^***(0.001)	-1.220^**(0.004)					-1.360^**(0.042)	-1.065(0.210)
生产制造									-2.505^***(<0.001)	-1.098 (<0.001)			-1.105(0.225)	2.978(0.130)
商务服务									0.038(0.939)	-0.180(0.175)			0.198(0.802)	3.374^*(0.054)
进出口贸易									-1.115^** (0.036)	-0.630(0.175)			0.032(0.996)	3.691^**(0.033)
研发设计									-0.135(0.832)	-0.858(0.183)			-0.234(0.800)	4.164^*(0.052)
服务业											2.298^*** (<0.001)	0.693^** (0.017)	2.140^**(0.005)	-0.531(0.564)
同源集聚	-0.014(0.168)	0.030^***(<0.001)	0.017(0.258)	0.102^*** (<0.001)	-0.031(0.003)	-0.029^**(0.003)	-0.014(0.155)	0.030^*** (<0.001)	-0.023(0.030)	-0.026^***(<0.001)	-0.026^**(0.017)	0.026^*** (<0.001)	-0.072^*(0.068)	0.237^*** (<0.001)
异源集聚	-0.002(0.769)	0.014^**(0.001)	0.032(0.022)	0.089^*** (<0.001)	-0.003(0.594)	0.013^**(0.021)	-0.003(0.623)	0.014^**(0.003)	-0.008(0.140)	-0.011^**(0.015)	-0.009^*(0.096)	0.012^**(0.012)	-0.026(0.475)	0.220^*** (<0.001)
百分比校正/%	21.7	75.2	19.3	86.3	32.6	74.4	15.7	71.4	45.8	67.7	48.2	66.5	64.4	93.0

地区	2001年前		2002—2012年		2013年后		合计
地区	合资数量/家	比重/%	合资数量/家	比重/%	合资数量/家	比重/%	合资企业/家	比重/%
北京	70	63.63	119	60.71	20	42.55	209	59.21
上海	282	53.80	527	39.80	115	47.13	924	44.17
广深	77	81.00	178	64.96	32	69.56	267	64.34