珠三角新晋跨境制造业企业地理集聚与区位选择

doi:10.18306/dlkxjz.2019.10.013

地理科学进展 ›› 2019, Vol. 38 ›› Issue (10): 1583-1595.doi: 10.18306/dlkxjz.2019.10.013

珠三角新晋跨境制造业企业地理集聚与区位选择

叶玉瑶¹,吴康敏^1,^2,³,张虹鸥¹,吴旗韬¹,陈伟莲¹

^1. 广州地理研究所,广州 510070
^2. 中国科学院广州地球化学研究所,广州 510640
^3. 中国科学院大学,北京 100049

收稿日期:2019-06-10 修回日期:2019-08-07 出版日期:2019-10-28 发布日期:2019-11-01
作者简介:叶玉瑶(1980— ),女,四川乐山人,博士,研究员,研究方向为城市群与区域发展战略。E-mail: yeyuyao@gdas.ac.cn
基金资助:
国家自然科学基金项目(No. 41671130);国家自然科学基金项目(No. 41671128);广东省科学院实施创新驱动发展能力建设专项(No. 2016GDASRC-0101);广州市科技计划项目(No. 201707010427)

Geographical agglomeration and location factors of the new-born cross-border manufactural firms in the Pearl River Delta

YE Yuyao¹,WU Kangmin^1,^2,³,ZHANG Hongou¹,WU Qitao¹,CHEN Weilian¹

^1. Guangzhou Institute of Geography, Guangzhou 510070, China
^2. Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
^3. University of Chinese Academy of Sciences,Beijing 100049, China

Received:2019-06-10 Revised:2019-08-07 Online:2019-10-28 Published:2019-11-01
Supported by:
National Natural Science Foundation of China(No. 41671130);National Natural Science Foundation of China(No. 41671128);GDAS' Project of Science and Technology Development(No. 2016GDASRC-0101);The Technology Plan of Guangzhou(No. 201707010427)

摘要/Abstract

摘要：

珠三角的跨境资本因其文化多元性、地缘特殊性而受到国际经济地理学家的广泛关注,“多元资本主义”等多种理论框架被提出以解释其特殊性。然而,由于数据、方法的限制,相关研究多停留于理论及定性探讨层面,基于微观企业样点的研究较为欠缺,特别是纳入企业异质性等新经济因素的定量模型研究更为缺乏。论文基于微观企业样点数据,综合考虑传统一般经济因素与制度、集聚、创新、企业异质性等新经济因素,采用核密度分析方法以及空间回归分析,研究了2005—2009、2009—2013年2个时段的珠三角新晋跨境制造业企业(new-born cross-border manufacturing firms, NCMF)的空间分布格局与差异,并重点关注金融危机前后(2005—2009年)这一特殊的经济转型时期,珠三角NCMF区位选择的影响机制。结果表明：①珠三角NCMF的空间集聚程度较以往有所降低,2005—2009年与2009—2013年2个时段的NCMF在结构与分布特征上呈现出较大的差异,热点区位在2005年后开始由珠三角东岸地区向西岸拓展,2009年后则再次呈现以东岸为主的集聚特征;②金融危机前后,珠三角的发展动力发生了根本性的变化,以往吸引跨境制造业企业的劳动力成本优势与开发区政策优势逐步弱化,而集聚因素、创新因素以及企业异质性成为影响跨境制造业企业空间集聚与区位选择的关键影响因素;③处于动力转换期的珠三角,需要通过构建完善的制度环境、建立创新网络、增强要素集聚、根据企业偏好制定多元化引资政策来重新获得发展的新优势。论文旨在从企业微观层面揭示经济区域内部的外商直接投资区位,同时也为理解转型时期中国以珠三角为代表的外向型经济区域的动力转换与空间重构提供实证参考。

关键词: NCMF, 劳动力成本, 创新, 制度, 企业异质性

Abstract:

The cross-border capital of the Pearl River Delta has received extensive attention from international economic geographers because of its cultural diversity and geopolitical specificity. The theoretical model of "hybrid capitalism" was proposed base on this. However, due to the limitations of data and methods, relevant research mostly stays at the level of theoretical and qualitative exploration. The research based on firm-level samples is deficient, especially quantitative models that incorporate the new economic factors such as firm heterogeneity. Based on the sample data of enterprises, this study synthetically considered the traditional economic factors and new economic factors such as institution, agglomeration, innovation, and firm heterogeneity. In order to explain the mechanism of foreign direct investment (FDI) location choice from the firm level, we also combined a spatial analysis method and spatial regression model. Kernel density spatial analysis and spatial lag modeling based on firm samples were conducted to uncover the geographical agglomeration characteristics and location factors of the new-born cross-border manufacturing firms (NCMF) in the Pearl River Delta (PRD) during 2005-2009 and 2009-2013. To explore the location choice mechanism of FDI in the transitional period, we also focused on the impact mechanism of location choice of NCMF in the PRD before and after the global financial crisis (2005-2009). The main results are as follow: 1) The spatial agglomeration of the NCMF in the PRD is lower than before. The NCMF in the two periods of 2005-2009 and 2009-2013 showed great differences in structure and distribution characteristics. The hotspot of firm distribution began to expand from the east coast of the PRD to the west side after 2005, and after 2009, firm agglomeration in the east coast was again obvious. 2) After the global financial crisis, the development momentum of the PRD has undergone fundamental changes. The advantages of low labor cost and preferential policies of development zones that attracted cross-border manufacturing firms have gradually weakened, while agglomeration factors, innovation factors, and firm heterogeneity have become the key factors that affect the spatial agglomeration and location choice of NCMF. 3) In the period of a dynamic transformation, the Pearl River Delta needs to regain its new advantages of development by building a sound institutional environment, establishing innovation networks, enhancing factor agglomeration, and formulating diversified investment policies according to firm preferences. This study examined the location choice of FDI within the economic region using the firm-level data, and may provide an empirical reference for understanding the dynamic transformation and spatial reconstruction of the export-oriented economic region represented by the Pearl River Delta in China during the transition period.

Key words: NCMF, labor cost, innovation, institution, firm heterogeneity

叶玉瑶,吴康敏,张虹鸥,吴旗韬,陈伟莲. 珠三角新晋跨境制造业企业地理集聚与区位选择[J]. 地理科学进展, 2019, 38(10): 1583-1595.

YE Yuyao,WU Kangmin,ZHANG Hongou,WU Qitao,CHEN Weilian. Geographical agglomeration and location factors of the new-born cross-border manufactural firms in the Pearl River Delta[J]. PROGRESS IN GEOGRAPHY, 2019, 38(10): 1583-1595.

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参考文献 72

[1]	贺灿飞, 梁进社, 张华 . 2005. 北京市外资制造企业的区位分析[J]. 地理学报, 60(1):122-130.
	[ He C F, Liang J S, Zhang H . 2005. Locational study of foreign enterprises in Beijing based on an ordered probity model. Acta Geographica Sinica, 60(1):122-130. ]
[2]	黄志基, 贺灿飞, 杨帆 , 等. 2015. 中国环境规制、地理区位与企业生产率增长[J]. 地理学报, 70(10):1581-1591.
	[ Huang Z J, He C F, Yang F , et al. 2015. Environmental regulation, geographic location and growth of firms' productivity in China. Acta Geographica Sinica, 70(10):1581-1591. ]
[3]	李佳洺, 张文忠, 李业锦 , 等. 2016. 基于微观企业数据的产业空间集聚特征分析: 以杭州市区为例[J]. 地理研究, 35(1):95-107.
	[ Li J M, Zhang W Z, Li Y J , et al. 2016. The characteristics of industrail agglomeration based on micro-geographic data. Geographical Research, 35(1):95-107. ]
[4]	李小建, 李国平, 曾刚 . 2006. 经济地理学 [M]. 北京: 高等教育出版社.
	[ Li X J, Li G P, Zeng G. 2006. Economic geograph. Beijing, China: Higher Education Press. ]
[5]	李小建, 苗长虹 . 2004. 西方经济地理学新进展及其启示[J]. 地理学报, 59(S1):153-161.
	[ Li X J, Miao C H . 2004. Recent developments in western economic geographies and theoretical thinking for China's counterpart. Acta Geographica Sinica, 59(S1):153-161. ]
[6]	李郇, 符文颖, 刘宏锋 . 2009. 经济全球化背景下的产业空间重构[J]. 热带地理, 29(5):454-459.
	[ Li X, Fu W Y, Liu H F . 2009. Industrial space reconstructing in the context of globalization. Tropical Geography, 29(5):454-459. ]
[7]	刘颖, 郭琪, 贺灿飞 . 2016. 城市区位条件与企业区位动态研究[J]. 地理研究, 35(7):1301-1313.
	[ Liu Y, Guo Q, He C F . 2016. Urban characteristics and firm's location selection. Geographical Research, 35(7):1301-1313. ]
[8]	苗长虹, 魏也华, 吕拉昌 . 2011. 新经济地理学 [M]. 北京: 科学出版社.
	[ Miao C H, Wei Y H, Lv L C. 2011. New economic geography. Beijing, China: Science Press. ]
[9]	潘峰华, 刘作丽, 夏亚博 , 等. 2013. 中国上市企业总部的区位分布和集聚特征[J]. 地理研究, 32(9):1721-1736.
	[ Pan F H, Liu Z L, Xia Y B , et al. 2013. Location and agglomeration of headquarters of public listed firms within China's urban system. Geographical Research, 32(9):1721-1736. ]
[10]	王洋, 杨忍, 李强 , 等. 2016. 广州市银行业的空间布局特征与模式[J]. 地理科学, 36(5):742-750. doi: 10.13249/j.cnki.sgs.2016.05.012
	[ Wang Y, Yang R, Li Q , et al. 2016. The spatial layout features and patterns of banking industry in Guangzhou City, China. Scientia Geographica Sinica, 36(5):742-750. ] doi: 10.13249/j.cnki.sgs.2016.05.012
[11]	韦荟, 吕斌, 孙莉 . 2010. 经济危机对东莞电子信息制造业空间集聚形态的影响研究: 基于两次经济危机的比较视角[J]. 城市发展研究, ( 7):113-118.
	[ Wei H, Lv B, Sun L . 2010. The impact of economic crisis on the spatial concentration of electronic information industry in Dongguan: Based on the comparison of the two economic crises. Urban Studies, ( 7):113-118. ]
[12]	吴康敏, 张虹鸥, 王洋 , 等. 2016. 广州市多类型商业中心识别与空间模式[J]. 地理科学进展, 35(8):963-974.
	[ Wu K M, Zhang H O, Wang Y , et al. 2016. Identify of the multiple types of commercial center in Guangzhou and its spatial pattern. Progress in Geography, 35(8):963-974. ]
[13]	袁丰, 魏也华, 陈雯 , 等. 2012. 无锡城市制造业企业区位调整与苏南模式重组[J]. 地理科学, 32(4):401-408.
	[ Yuan F, Wei Y H, Chen W , et al. 2012. Manufacturing firms location adjustment and the restructuring of the Sunan Model in Wuxi City. Scientia Geographica Sinica, 32(4):401-408. ]
[14]	赵冬昶, 苗燕民 . 2009. 后金融危机时代珠三角地区产业结构升级研究[J]. 价格理论与实践, ( 10):74-75.
	[ Zhao D C, Miao Y M . 2009. Industrial structure upgrading in the Pearl River Delta region in the post financial crisis era. Price: Theory & Practice, ( 10):74-75. ]
[15]	赵浚竹, 孙铁山, 李国平 . 2014. 中国汽车制造业集聚与企业区位选择[J]. 地理学报, 69(6):850-862.
	[ Zhao J Z, Sun T S, Li G P . 2014. Agglomeration and firm location choice of China's automobile manufacturing industry. Acta Geographica Sinica, 69(6):850-862. ]
[16]	Alcácer J . 2006. Location choices across the value chain: How activity and capability influence collocation[J]. Management Science, 52(10):1457-1471.
[17]	Aw B Y, Lee Y . 2008. Firm heterogeneity and location choice of Taiwanese multinationals[J]. Journal of International Economics, 75(2):403-415.
[18]	Baldwin R E, Okubo T . 2005. Heterogeneous firms, agglomeration and economic geography: Spatial selection and sorting[J]. Journal of Economic Geography, 6(3):323-346.
[19]	Belderbos R, Carree M . 2002. The location of Japanese investments in China: Agglomeration effects, keiretsu, and firm heterogeneity[J]. Journal of the Japanese & International Economies, 16(2):194-211.
[20]	Beugelsdijk S, Mudambi R . 2013. MNEs as border-crossing multi-location enterprises: The role of discontinuities in geographic space[J]. Journal of International Business Studies, 44(5):413-426.
[21]	Blanc-Brude F, Cookson G, Piesse J , et al. 2014. The FDI location decision: Distance and the effects of spatial dependence[J]. International Business Review, 23(4):797-810.
[22]	Bo B N, Asmussen C G, Weatherall C D . 2017. The location choice of foreign direct investments: Empirical evidence and methodological challenges[J]. Journal of World Business, 52(1):62-82.
[23]	Cheng L K, Kwan Y K . 2000. What are the determinants of the location of foreign direct investment? The Chinese experience[J]. Journal of International Economics, 51(2):379-400.
[24]	Chu H J, Liau C J, Lin C H , et al. 2012. Integration of fuzzy cluster analysis and kernel density estimation for tracking typhoon trajectories in the Taiwan region[J]. Expert Systems with Applications, 39(10):9451-9457.
[25]	Coates D . 2005. Varieties of capitalism, varieties of approaches[M]. New York, USA: Palgrave Macmillan.
[26]	Daude C, Stein E . 2010. The quality of institutions and foreign direct investment[J]. Economics & Politics, 19(3):317-344.
[27]	Dicken P . 2005. Tangled webs: Transnational production networks and regional integration [R]. SPACES Working Paper 2005-04. Marburg, Germany: University of Marburg.
[28]	Dieter E, Kim L . 2001. Global production networks, knowledge diffusion, and local capability formation[J]. Research Policy, 31(8):1417-1429.
[29]	Du J, Lu Y, Tao Z . 2008. Economic institutions and FDI location choice: Evidence from US multinationals in China[J]. Journal of Comparative Economics, 36(3):412-429.
[30]	Duanmu J L . 2012. Firm heterogeneity and location choice of Chinese Multinational Enterprises (MNEs)[J]. Journal of World Business, 47(1):64-72.
[31]	Duranton G, Puga D . 2003. Micro-foundations of urban agglomeration economies[M] // Henderson J V, Thisse J-F. Handbook of Regional and Urban Economics. Elsevier:2063-2117.
[32]	Ehrlich M V, Seidel T . 2013. More similar firms: More similar regions? On the role of firm heterogeneity for agglomeration[J]. Regional Science & Urban Economics, 43(3):539-548.
[33]	Fujita M, Thisse J F . 2009. New economic geography: An appraisal on the occasion of Paul Krugman's 2008 Nobel Prize in economic sciences[J]. Regional Science & Urban Economics, 39(2):109-119.
[34]	Goerzen A, Asmussen C G, Bo B N . 2013. Global cities and multinational enterprise location strategy[J]. Journal of International Business Studies, 44(5):427-450.
[35]	Hao H, Wei Y D . 2014. Intra-metropolitan location of foreign direct investment in Wuhan, China: Institution, urban structure, and accessibility[J]. Applied Geography, 47:78-88.
[36]	Hao H, Wei Y D . 2016. Spatial inequality of foreign direct investment in China: Institutional change, agglomeration economies, and market access[J]. Applied Geography, 69:99-111.
[37]	He C F . 2002. Information costs, agglomeration economies and the location of foreign direct investment in China[J]. Regional Studies, 36(9):1029-1036.
[38]	He C F . 2003. Location of foreign manufacturers in China: Agglomeration economies and country of origin effects[J]. Papers in Regional Science, 82(3):351-372.
[39]	Henderson J V . 2003. Marshall's scale economies[J]. Journal of Urban Economics, 53(1):1-28.
[40]	Henderson J, Dicken P Hess, Coe N , et al. 2002. Global production networks and the analysis of economic development[J]. Review of International Political Economy, 9(3):436-464.
[41]	Henderson, Coe N, Hess M , et al. 2005. Globalising regional development: A global production networks perspective[J]. Transactions of the Institute of British Geographers 29: 464-484.
[42]	Hernandez E . 2014. Finding a home away from home: Effects of immigrants on firms' foreign location choice and performance[J]. Administrative Science Quarterly, 59(1):73-108.
[43]	Hong J . 2014. Firm heterogeneity and location choices: Evidence from foreign manufacturing investments in China[J]. Urban Studies, 46(10):2143-2157.
[44]	Hoover E M . 1963. The location of economic activity[M]. New York, USA: McGraw-Hill.
[45]	Jin U K, Aguilera R V . 2016. Foreign location choice: Review and Extensions[J]. International Journal of Management Reviews, 18(2):133-159.
[46]	Kostova T R K, Dacin M T . 2008. Institutional theory in the study of multinational corporations: A critique and new directions[J]. Academy of Management Review, 33(4):994-1006.
[47]	Krugman P, Venables A J . 1996. Integration, specialization, and adjustment[J]. European Economic Review, 40(3):959-967.
[48]	Lane D, Myant M . 2007. Varieties of capitalism in post-communist countries[M]. New York, USA: Palgrave Macmillan.
[49]	Laulajainen R S H A . 1995. Competitive strategies[M]. Netherlands: Springer.
[50]	Losch A. 1954. Economics of location [M]. New Haven, USA: Yale University Press.
[51]	Martin R . 1999. The new 'geographical turn' in economics: Some critical reflections[J]. Cambridge Journal of Economics, 23(1):65-91.
[52]	Martin R, Sunley P . 2006. Path dependence and regional economic evolution[J]. Papers in Evolutionary Economic Geography, 6(4):395-437.
[53]	Meyer K E . 2010. Foreign investment strategies and sub-national institutions in emerging markets: Evidence from Vietnam[J]. Journal of Management Studies, 42(1):63-93.
[54]	Myles J, Shave F F . 2015. Agglomeration economies, firm heterogeneity, and foreign direct investment in the United States[J]. Strategic Management Journal, 21(12):1175-1193.
[55]	Ohlin B . 1952. Interregional and international trade[M]. Cambridge, USA: Harvard University Press
[56]	Okubo T, Picard P M, Thisse J F . 2010. The spatial selection of heterogeneous firms[J]. Journal of International Economics, 82(2):230-237.
[57]	Ottaviano G I P . 2011. "New" new economic geography: Firm heterogeneity and agglomeration economies[J]. Journal of Economic Geography, 11(2):231-240.
[58]	Rasciute S, Pentecost E, Ferrett B . 2014. Firm heterogeneity in modelling foreign direct investment location decisions[J]. Applied Economics, 46(12):1350-1360.
[59]	Rosenthal S S, Strange W C . 2003. Geography, industrial organization, and agglomeration[J]. The Review of Economics and Statistics, 85(2):377-393.
[60]	Scott W R . 2001. Institutions and organizations[M]. Thousand Oaks, USA: Sage Publications.
[61]	Wang J, Zhang X, Yeh A G O . 2016. Spatial proximity and location dynamics of knowledge-intensive business service in the Pearl River Delta, China[J]. Habitat International, 53:390-402.
[62]	Wang Y, Wang S J, Li G D , et al. 2017. Identifying the determinants of housing prices in China using spatial regression and the geographical detector technique[J]. Applied Geography, 79:26-36.
[63]	Weber A. 1960. Theory of the location of industries [M]. Chicago, USA: University of Chicago Press.
[64]	Whitley R. 1999. Divergent capitalisms: The social structuring and change of business systems [M]. Oxford, UK: Oxford University Press.
[65]	Wu K M, Wang Y, Ye Y Y , et al. 2019. Relationship between the built environment and the location choice of high-tech firms: Evidence from the Pearl River Delta[J]. Sustainability, 11, 3689. doi: 10.3390/su11133689.
[66]	Yang C . 2006. Overseas Chinese investments in transition: The case of Dongguan[J]. Eurasian Geography and Economics, 47(5):604-621.
[67]	Yang C . 2007. Divergent hybrid capitalisms in China: Hong Kong and Taiwanese electronics clusters in Dongguan[J]. Economic Geography, 83(4):395-420.
[68]	Yang C . 2012. Restructuring the export-oriented industrialization in the Pearl River Delta, China: Institutional evolution and emerging tension[J]. Applied Geography, 32:143-157.
[69]	Ye Y Y, Wu K M, Xie Y C , et al. 2019. How firm heterogeneity affects foreign direct investment location choice: Micro-evidence from new foreign manufacturing firms in the Pearl River Delta[J]. Applied Geography, 106:11-21.
[70]	Yeung W C . 2004. Chinese capitalism in a global era: Towards hybrid capitalism[M]. London, UK: Routledge.
[71]	Yeung W C, Liu W. Dicken P. . 2006. Transnational corporations and network effects of a local manufacturing cluster in mobile telecommunications equipment in China[J]. World Development, 34(3):520-540.
[72]	Zhou C S, Chen J, Wang S J . 2018. Examining the effects of socioeconomic development on fine particulate matter (PM_2.5) in China's cities using spatial regression and the geographical detector technique[J]. Science of the Total Environment, 619-620:436-445.

项目	企业数/个	产值规模 /万元	企业平均从业人数/人	劳动生产率 /(万元/人)	集聚程度R
2005年既有跨境制造业企业	12841	19967.94	481	508.50	0.294
2005—2009年NCMF	3558	15121.26	327	530.25	0.350
2009—2013年NCMF	1554	238460.83	500.51	1112.98	0.3676

分类	影响因素	指标测算	数据来源	备注
一般经济因素	劳动力成本	测算劳动生产率,即单位劳动力产出的GDP,一般而言,劳动生产率越高,代表劳动力成本越低	工业企业数据库	连续变量纳入回归模型
	本地市场需求	地市社会消费品零售总额	统计年鉴
	基础设施水平	等级以上路网密度(格网尺度为10 km×10 km)	交通路网矢量数据
新经济因素	集聚因素	2005年已有跨境制造业企业核密度值(500 m×500 m)	工业企业数据库
	创新因素	2005年已有高新技术企业核密度值(500 m×500 m)	工业企业数据库
	企业异质性	企业规模差异,用企业工业总产值表示	工业企业数据库
		外资来源地差异,港澳资本VS非港澳外资	工业企业数据库	非连续变量设置对照组
		投资方式差异,外商独资VS合资、合作	工业企业数据库
		产业结构水平差异,劳动密集型VS资本密集型VS技术密集型	工业企业数据库
	制度因素	政策区划差异,企业样点位于省级开发区内VS位于省级开发区外	省级以上开发区边界数据

变量	系数	Std.	z	P
W	0.9173^***	0.0050	182.934	<0.0001
常数项	-0.0030^***	0.0011	-2.8012	0.0051
劳动生产率	1.31E-07	1.22E-07	1.0793	0.2805
本地市场需求	-1.33E-10^***	4.13E-11	-3.2145	0.0013
基础设施水平	0.0080^***	0.0015	5.3131	<0.0001
集聚因素	0.0178^***	0.0013	14.1087	<0.0001
创新因素	0.0058^***	0.0020	2.8397	0.0045
企业规模	-1.61E-10	2.54E-10	-0.6324	0.5271
	R²: 0.9916; AIC: -19971.90

变量	港澳台资本				非港澳台外资
变量	系数	Std.	z	P	系数	Std.	z	P
W	0.8601^***	0.0079	108.6790	<0.0001	0.7746^***	0.0127	61.0412	<0.0001
常数项	-0.0001	0.0017	-0.0838	0.9332	0.0174^***	0.0029	5.9675	<0.0001
劳动生产率	-1.99E-08	2.15E-07	-0.0926	0.9262	1.45E-07	2.53E-07	0.5734	0.5664
本地市场需求	-1.86E-10^***	6.65E-11	-2.7978	0.0052	-1.65E-10^*	9.64E-11	-1.7085	0.0876
基础设施水平	0.0087^***	0.0023	3.8543	0.0001	-0.0048	0.0038	-1.2509	0.2110
集聚因素	0.0299^***	0.0020	15.1362	<0.0001	0.0455^***	0.0030	15.1564	<0.0001
创新因素	0.0086^***	0.0032	2.6965	0.0070	0.0096^*	0.0049	1.9440	0.0519
企业规模	7.05E-10	6.05E-10	1.1654	0.2438	-9.37E-10^*	5.25E-10	-1.7858	0.0741
	R²: 0.9886; AIC: -11731.00				R²: 0.9786; AIC: -6097.26

变量	独资				合资、合作
变量	系数	Std.	z	P	系数	Std.	z	P
W	0.8933^***	0.0062	143.7600	<0.0001	0.3278^***	0.0182	18.0008	<0.0001
常数项	0.0004	0.0013	0.2719	0.7857	0.0359^***	0.0067	5.3521	<0.0001
劳动生产率	-5.38E-08	2.71E-07	-0.1989	0.8423	2.42E-07	3.63E-07	0.6660	0.5054
本地市场需求	-1.02E-10^**	5.15E-11	-1.9734	0.0485	-1.57E-09^***	2.33E-10	-6.7469	<0.0001
基础设施水平	0.0049^***	0.0018	2.6856	0.0072	0.0058	0.0094	0.6106	0.5414
集聚因素	0.0230^***	0.0015	14.8809	<0.0001	0.1711^***	0.0059	29.0275	<0.0001
创新因素	0.0058^**	0.0025	2.3392	0.0193	-0.0348^**	0.0139	-2.5002	0.0124
企业规模	-2.58E-10	3.37E-10	-0.7658	0.4438	-7.65E-11	2.59E-09	-0.0295	0.9765
	R²: 0.9904; AIC: -16063.90				R²: 0.9112; AIC: -2219.80

珠三角新晋跨境制造业企业地理集聚与区位选择

Geographical agglomeration and location factors of the new-born cross-border manufactural firms in the Pearl River Delta

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变量	技术密集				劳动密集				资本密集
变量	系数	Std.	z	P	系数	Std.	z	P	系数	Std.	z	P
W	0.4860^***	0.0232	20.9611	<0.0001	0.5853^***	0.0181	32.312	<0.0001	0.8677^***	0.0077	112.5980	<0.0001
常数项	0.0731^***	0.0077	9.5037	<0.0001	0.0264^***	0.0040	6.6161	<0.0001	0.0036^**	0.0017	2.1329	0.0329
劳动生产率	-1.29E-06	1.69E-06	-0.7632	0.4454	-4.33E-06	2.75E-06	-1.5733	0.1157	1.17E-07	1.43E-07	0.8153	0.4149
本地市场需求	3.17E-10	3.37E-10	0.9385	0.3480	-9.48E-10^***	1.56E-10	-6.0782	<0.0001	-1.19E-10^**	5.90E-11	-2.0171	0.0437
基础设施水平	-0.0593^***	0.0100	-5.9168	<0.0001	0.0032	0.0054	0.5894	0.5556	0.0030	0.0023	1.3010	0.1933
集聚因素	0.1298^***	0.0079	16.4987	<0.0001	0.0802^***	0.0043	18.6195	<0.0001	0.0277^***	0.0019	14.9117	<0.0001
创新因素	-0.0838^***	0.0172	-4.8688	<0.0001	0.0423^***	0.0076	5.5580	<0.0001	0.0083^***	0.0029	2.8332	0.0046
企业规模	4.47E-10	9.10E-10	0.4915	0.6231	3.36E-09	6.07E-09	0.5534	0.5800	2.53E-10	6.20E-10	0.4080	0.6833
	R²: 0.9451; AIC: -1873.70				R²: 0.9650; AIC: -4281.33				R²: 0.9903; AIC: -10693.00

变量	开发区内				开发区外
变量	系数	Std.	z	P	系数	Std.	z	P
W	0.8245^***	0.0198	41.7005	<0.0001	0.9118^***	0.0054	169.7390	<0.0001
常数项	0.011^***	0.0032	3.4877	0.0005	-0.0040^***	0.0012	-3.2735	0.0011
劳动生产率	-3.16E-07	4.46E-07	-0.7091	0.4783	1.64E-07	1.32E-07	1.2464	0.2126
本地市场需求	-1.81E-10^*	1.10E-10	-1.6536	0.0982	-1.82E-10^***	4.87E-11	-3.7486	0.0002
基础设施水平	0.0034	0.0054	0.6224	0.5337	0.0095^***	0.0017	5.7034	<0.0001
集聚因素	0.0440^***	0.0063	6.9284	<0.0001	0.0186^***	0.0013	13.9385	<0.0001
创新因素	-0.0300^***	0.0107	-2.7951	0.0052	0.0084^***	0.0022	3.8316	0.0001
企业规模	-5.30E-10	4.30E-10	-1.2345	0.2170	-1.02E-10	3.59E-10	-0.2832	0.7770
	R²: 0.9645; AIC: -2539.12				R²: 0.9917; AIC: -17120.30