北京对外投资与吸引投资的时空特征及影响因素的比较研究

doi:10.18306/dlkxjz.2023.03.003

摘要/Abstract

摘要：

随着北京总部经济的蓬勃发展和非首都核心功能疏解的持续推进，北京与国内其他城市的资本流动得到了越来越多的关注。论文利用2000—2019年北京与全国地级及以上城市对外投资和吸引投资数据，揭示北京对外投资和吸引投资的时空特征，并利用地理加权回归(GWR)模型分析投资影响因素的空间分异特征。研究发现： ① 北京对外投资与吸引投资规模均呈现出先增加再减少的趋势，且对外投资一直大于吸引投资，北京是资本净输出区；北京对外投资和吸引投资均以服务业为主，对外投资的制造业总额和比重均大于吸引投资。② 北京对外投资与吸引投资空间范围不断扩大，对外投资的空间分布范围更广，分层现象更加明显；北京对外投资目的地以东部沿海城市和省会城市为主，近期更注重对中西部城市和北京周边城市的投资；北京吸引投资来源地较为稳定，主要是省会城市、东部沿海城市和北京周边城市。对外投资与吸引投资的重点区域非常类似。③ 北京对外投资与吸引投资的空间集中程度高但呈现下降趋势，吸引投资空间集中程度更高；近期北京对外投资分布呈现空间正相关分布，吸引投资呈现随机分布；对外投资形成了京津冀、长三角、山东半岛三大高—高集聚区；吸引投资形成了长三角、珠三角两大高—高集聚区。④ 对外投资与吸引投资均受到经济发展规模差异、产业结构水平差异的影响，影响效果存在明显的空间异质性；对外投资还会受到交通通达性和劳动力成本差异的影响，吸引投资还会受到经济开放程度差异的影响。论文完善了对外投资目的地与吸引投资来源地的对比研究，丰富了投资地理研究。

关键词: 企业投资, 对外投资, 吸引投资, 地理加权回归, 北京

Abstract:

With the vigorous development of Beijing's headquarters economy and continuous promotion of the relief of noncapital core functions, capital flows between Beijing and other cities in China have received increasingly attention. Using the data of Beijing's outward investment and inward investment at prefecture-level and above cities from 2000 to 2019, this study examined the temporal and spatial characteristics of Beijing's outward investment and inward investment, and analyzed the spatial differentiation characteristics of investment influencing factors using a geographically weighted regression (GWR) model. The research found that: 1) Beijing's outward investment and inward investment first increased and then decreased, outward investment had always been greater than inward investment, and Beijing was a net capital export area. Beijing's outward investment and inward investment were mainly in the service sector, and the total amount and proportion of manufacturing in outward investment were greater than that of inward investment. 2) The spatial scope of Beijing's outward investment and inward investment continued to expand, the spatial distribution of destinations of outward investment was wider than inward investment, and the stratification phenomenon was more obvious. Beijing's outward investment was mainly in eastern coastal cities and provincial capital cities. Recently, more attention had been paid to the investment in central and western cities and cities around Beijing. The origin city of inward investment was stable, mainly provincial capital cities, eastern coastal cities, and cities around Beijing. The key cities of outward investment and inward investment were similar. 3) Beijing had a high degree of spatial concentration of outward investment and inward investment but showed a downward trend, and the degree of spatial concentration of inward investment was even higher. Recently, Beijing's outward investment had shown a positive spatial association, and inward investment had shown a random distribution. The high-high agglomeration areas of outward investment were the Beijing-Tianjin-Hebei, Yangtze River Delta, and Shandong Peninsula regions, and the high-high agglomeration areas of inward investment were the Yangtze River Delta and Pearl River Delta regions. 4) Beijing's outward investment and inward investment were both affected by differences in economic development scale and industrial structure, but there was an obvious spatial heterogeneity in the effects of influence. Outward investment was also affected by differences in transportation accessibility and labor costs, and inward investment was also affected by differences in economic openness. The research has improved the comparative study of outward investment destinations and inward investment sources, and enriched the study of investment geography.

Key words: enterprise investment, outward investment, inward investment, geographically weighted regression, Beijing

王子安, 卢明华. 北京对外投资与吸引投资的时空特征及影响因素的比较研究[J]. 地理科学进展, 2023, 42(3): 438-451.

WANG Zi'an, LU Minghua. A comparative study on the temporal and spatial characteristics and influencing factors of Beijing’s outward investment and inward investment[J]. PROGRESS IN GEOGRAPHY, 2023, 42(3): 438-451.

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参考文献 47

[1]	魏后凯. 现代区域经济学[M]. 北京: 经济管理出版社, 2006.
	[Wei Houkai. Modern regional economies. Beijing, China: Economy & Management Publishing House, 2006.]
[2]	Bagchi-Sen S, Wheeler J O. A spatial and temporal model of foreign direct investment in the United States[J]. Economic Geography, 1989, 65(2): 113-129. doi: 10.2307/143776
[3]	Hoang H H, Goujon M. Determinants of intra-region and extra-region foreign direct investment inflow in ASEAN: A spatial econometric analysis[J]. Applied Spatial Analysis and Policy, 2019, 12(4): 965-982. doi: 10.1007/s12061-018-9280-8
[4]	Procher V. Agglomeration effects and the location of FDI: Evidence from French first-time movers[J]. The Annals of Regional Science, 2011, 46(2): 295-312. doi: 10.1007/s00168-009-0349-9
[5]	Hill S, Munday M. The UK regional distribution of foreign direct investment: Analysis and determinants[J]. Regional Studies, 1992, 26(6): 535-544. doi: 10.1080/00343409212331347181
[6]	Thomas D E, Grosse R. Country-of-origin determinants of foreign direct investment in an emerging market: The case of Mexico[J]. Journal of International Management, 2001, 7(1): 59-79. doi: 10.1016/S1075-4253(00)00040-5
[7]	Grosse R, Trevino L J. Foreign direct investment in the United States: An analysis by country of origin[J]. Journal of International Business Studies, 1996, 27(1): 139-155. doi: 10.1057/palgrave.jibs.8490129
[8]	李国平, 杨开忠. 外商对华直接投资的产业与空间转移特征及其机制研究[J]. 地理科学, 2000, 20(2): 102-109.
	[Li Guoping, Yang Kaizhong. A study on the mechanism and character of the industrial and spatial transference of FDI in China. Scientia Geographica Sinica, 2000, 20(2):102-109.] doi: 10.13249/j.cnki.sgs.2000.02.102
[9]	廖小东, 丰凤. 近10年外商在华直接投资的空间分异及成因分析[J]. 经济地理, 2012, 32(12): 112-116.
	[Liao Xiaodong, Feng Feng. Study on spatial differentiation and its causes of FDI in China in recent 10 years. Economic Geography, 2012, 32(12): 112-116.]
[10]	曾国军. 外商直接投资在华区位选择的影响因素研究[J]. 学术研究, 2005(11): 38-42, 147.
	[Zeng Guojun. Determinants of location choice of FDI to China's mainland. Academic Research Journal, 2005(11): 38-42, 147.]
[11]	Defever F. Functional fragmentation and the location of multinational firms in the enlarged Europe[J]. Regional Science and Urban Economics, 2006, 36(5): 658-677. doi: 10.1016/j.regsciurbeco.2006.06.007
[12]	Enright M J. The location of activities of manufacturing multinationals in the Asia-Pacific[J]. Journal of International Business Studies, 2009, 40(5): 818-839. doi: 10.1057/jibs.2009.2
[13]	贺灿飞, 肖晓俊. 跨国公司功能区位实证研究[J]. 地理学报, 2011, 66(12): 1669-1681.
	[He Canfei, Xiao Xiaojun. Geography of multinational corporations in China: An empirical study of fortune global 500 multinational corporations in electronics and medical and chemical industries. Acta Geographica Sinica, 2011, 66(12): 1669-1681.] doi: 10.11821/xb201112008
[14]	Schiller D, Burger M J, Karreman B. The functional and sectoral division of labour between Hong Kong and the Pearl River Delta: From complementarities in production to competition in producer services?[J]. Environment and Planning A: Economy and Space, 2015, 47(1): 188-208. doi: 10.1068/a140128p
[15]	Li S Y, Fabuš M. Study on the spatial distribution of China's outward foreign direct investment in EU and its influencing factors[J]. Entrepreneurship and Sustainability Issues, 2019, 6(3): 1280-1296.
[16]	Fu Y, Supriyadi A, Wang T. China's outward FDI in Indonesia: Spatial patterns and determinants[J]. Sustainability, 2018, 10(12): 4632. doi:10.3390/su10124632. doi: 10.3390/su10124632
[17]	Meyer S P. Canada's multinationals: A study in outward foreign direct investment[D]. London, Canada: The University of Western Ontario, 1995.
[18]	汪胜兰, 蒋小荣, 杨永春. 中国境外投资企业功能区位的空间格局及其演化[J]. 地域研究与开发, 2020, 39(5): 1-7.
	[Wang Shenglan, Jiang Xiaorong, Yang Yong-chun. Spatial pattern and evolution of the functional location of China's foreign investment enterprises. Areal Research and Development, 2020, 39(5): 1-7.]
[19]	余官胜, 林俐. 企业海外集群与新晋企业对外直接投资区位选择: 基于浙江省微观企业数据[J]. 地理研究, 2015, 34(2): 364-372. doi: 10.11821/dlyj201502015
	[Yu Guansheng, Lin Li. Enterprises overseas cluster and foreign direct investment location choice of new entrants: An empirical research based on micro enterprises data in Zhejiang Province. Geographical Research, 2015, 34(2): 364-372.] doi: 10.11821/dlyj201502015
[20]	王茂军, 徐永平. 中国在美洲OFDI的基本特征与决定因素[J]. 地理学报, 2017, 72(8): 1373-1391. doi: 10.11821/dlxb201708004
	[Wang Maojun, Xu Yongping. China's OFDI in America: Basic features and determinants. Acta Geographica Sinica, 2017, 72(8): 1373-1391.] doi: 10.11821/dlxb201708004
[21]	刘晓宁. 企业对外直接投资区位选择: 东道国因素与企业异质性因素的共同考察[J]. 经济经纬, 2018, 35(3): 59-66.
	[Liu Xiaoning. Location choice of outward foreign direct investment: A study on host country factors and enterprise heterogeneity factors. Economic Survey, 2018, 35(3): 59-66.]
[22]	郑蕾, 刘志高. 中国对“一带一路”沿线直接投资空间格局[J]. 地理科学进展, 2015, 34(5): 563-570. doi: 10.11820/dlkxjz.2015.05.004
	[Zheng Lei, Liu Zhigao. Spatial pattern of Chinese outward direct investment in the Belt and Road Initiative area. Progress in Geography, 2015, 34(5): 563-570.] doi: 10.11820/dlkxjz.2015.05.004
[23]	公丕萍, 宋周莺, 刘卫东. 中国与“一带一路”沿线国家贸易的商品格局[J]. 地理科学进展, 2015, 34(5): 571-580. doi: 10.11820/dlkxjz.2015.05.005
	[Gong Peiping, Song Zhouying, Liu Weidong. Commodity structure of trade between China and countries in the Belt and Road Initiative area. Progress in Geography, 2015, 34(5): 571-580.] doi: 10.11820/dlkxjz.2015.05.005
[24]	张亚斌. “一带一路”投资便利化与中国对外直接投资选择: 基于跨国面板数据及投资引力模型的实证研究[J]. 国际贸易问题, 2016(9): 165-176.
	[Zhang Yabin. The investment facilitation of "one belt one road" and choices of China's foreign direct investment: Empirical analysis based on cross-panel data and investment gravity model. Journal of International Trade, 2016(9): 165-176.]
[25]	王帅, 席强敏, 李国平. 北京制造业企业对河北投资的空间特征与影响因素[J]. 经济地理, 2015, 35(4): 90-98.
	[Wang Shuai, Xi Qiangmin, Li Guoping. The geographical characteristics & influencing factors of Beijing manufacture enterprises investment on Hebei. Economic Geography, 2015, 35(4): 90-98.]
[26]	卢明华, 周悦颜, 刘汉初, 等. 北京企业对河北直接投资的时空动态特征及影响因素[J]. 地理科学进展, 2020, 39(3): 389-401. doi: 10.18306/dlkxjz.2020.03.004
	[Lu Minghua, Zhou Yueyan, Liu Hanchu, et al. Spatiotemporal dynamics and influencing factors of direct investment in Hebei Province by Beijing's enterprises. Progress in Geography, 2020, 39(3): 389-401.] doi: 10.18306/dlkxjz.2020.03.004
[27]	桑瑞聪, 刘志彪. 中国产业转移趋势特征和影响因素研究: 基于上市公司微观数据的分析[J]. 财贸研究, 2014, 25(6): 53-60.
	[Sang Ruicong, Liu Zhibiao. The study of the trend and the influential factors of industry transference in China: Analysis on listed companies. Finance and Trade Research, 2014, 25(6): 53-60.]
[28]	宋渊洋, 黄礼伟. 为什么中国企业难以国内跨地区经营?[J]. 管理世界, 2014, 30(12): 115-133.
	[Song Yuanyang, Huang Liwei. Why is it difficult for China enterprises to operate across regions in China? Management World, 2014, 30(12): 115-133.]
[29]	胡国建, 陈传明, 陈丽娟, 等. 企业跨区域投资格局及其影响因素: 以福建上市企业为例[J]. 经济地理, 2018, 38(9): 138-146.
	[Hu Guojian, Chen Chuanming, Chen Lijuan, et al. Study on the cross-regional investment pattern of enterprises and its influencing factors: Taking listed enterprises in Fujian as an example. Economic Geography, 2018, 38(9): 138-146.] doi: 10.2307/142274
[30]	张永波, 张峰. 基于企业投资数据的京津冀科技创新空间网络研究[J]. 城市规划学刊, 2017(S2): 72-78.
	[Zhang Yongbo, Zhang Feng. A research on the spatial technological innovation network of Beijing-Tianjin-Hebei region based on the enterprise investment data. Urban Planning Forum, 2017(S2): 72-78.]
[31]	谢专, 张佳梁, 张晓波. 京津冀的产业结构现状、变迁与空间资本流动: 来自工商注册数据的证据[J]. 人口与发展, 2015, 21(5): 24-33.
	[Xie Zhuan, Zhang Jialiang, Zhang Xiaobo. The structure of production and capital flows in Beijing-Tianjin-Hebei: Evidence from firm registry database. Population and Development, 2015, 21(5): 24-33.]
[32]	许欣. 北京企业对河北直接投资区位选择及影响因素研究[D]. 北京: 首都师范大学, 2017.
	[Xu Xin. Location selection and influencing factors of direct investment in Hebei by Beijing enterprises. Beijing, China: Capital Normal University, 2017.]
[33]	陆大道. 京津冀城市群功能定位及协同发展[J]. 地理科学进展, 2015, 34(3): 265-270. doi: 10.11820/dlkxjz.2015.03.001
	[Lu Dadao. Function orientation and coordinating development of subregions within the Jing-Jin-Ji urban agglomeration. Progress in Geography, 2015, 34(3): 265-270.] doi: 10.11820/dlkxjz.2015.03.001
[34]	叶琪. 我国区域产业转移的态势与承接的竞争格局[J]. 新疆财经, 2013(6): 38-45.
	[Ye Qi. The transfer trend and undertaking competitive situation of China's regional industry. Finance & Economics of Xinjiang, 2013(6): 38-45.]
[35]	沈惊宏, 孟德友, 陆玉麒. 皖江城市带承接长三角产业转移的空间差异分析[J]. 经济地理, 2012, 32(3): 43-49.
	[Shen Jinghong, Meng Deyou, Lu Yuqi. The analysis of spatial difference of Wanjiang demonstration zone undertaking the Yangtze River Delta's industry transfer. Economic Geography, 2012, 32(3): 43-49.]
[36]	张建伟, 苗长虹, 肖文杰. 河南省承接产业转移区域差异及影响因素[J]. 经济地理, 2018, 38(3): 106-112.
	[Zhang Jianwei, Miao Changhong, Xiao Wenjie. Regional differences and influence factor of Henan's undertaking industrial transfer. Economic Geography, 2018, 38(3):106-112.]
[37]	张建伟, 赵建吉, 肖文杰, 等. 豫皖湘赣承接产业转移的空间计量经济分析[J]. 地理科学, 2019, 39(1): 140-146. doi: 10.13249/j.cnki.sgs.2019.01.016
	[Zhang Jianwei, Zhao Jianji, Xiao Wenjie, et al. Spatial econometric analysis of undertaking industrial transfer in Henan-Anhui-Hunan-Jiangxi region. Scientia Geographica Sinica, 2019, 39(1): 140-146.] doi: 10.13249/j.cnki.sgs.2019.01.016
[38]	Santos Françoso M, Breul M, Hiratuka C. The spatial organization of oil and gas investments in South America: An analysis based on communities[J]. Nova Economia, 2019, 29(3): 795-815. doi: 10.1590/0103-6351/4756
[39]	蔡高明, 李志斌, 王东宇, 等. 中原城市群产业投资网络结构特征分析[J]. 城市发展研究, 2017, 24(12): 16-21, 91.
	[Cai Gaoming, Li Zhibin, Wang Dongyu, et al. A study on characteristics of the investment network of central plains city group. Urban Development Studies, 2017, 24(12): 16-21, 91.]
[40]	王伟, 张常明, 王梦茹. 中国三大城市群产业投资网络演化研究[J]. 城市发展研究, 2018, 25(11): 118-124, 2, 161.
	[Wang Wei, Zhang Changming, Wang Mengru. Research on the evolution of industrial investment network of China's three major urban agglomerations. Urban Development Studies, 2018, 25(11): 118-124, 2, 161.]
[41]	李聪, 卢明华, 张金哲, 等. 京津冀城市群产业投资网络演变及影响因素研究[J]. 人文地理, 2022, 37(5): 162-170.
	[Li Cong, Lu Minghua, Zhang Jinzhe, et al. Evolution and influencing factors of industrial investment network in Beijing-Tianjin-Hebei urban agglomeration. Human Geography, 2022, 37(5): 162-170.]
[42]	高技. Excel下基尼系数的计算研究[J]. 浙江统计, 2008(6): 41-43.
	[Gao Ji. Study on the calculation of Gini coefficient. Zhejiang Statistics, 2008(6): 41-43.]
[43]	宗会明, 季欣. 1999—2018年重庆市主城区住宅用地空间演变特征及驱动因素研究[J]. 地理科学, 2021, 41(7): 1256-1265. doi: 10.13249/j.cnki.sgs.2021.07.016
	[Zong Huiming, Ji Xin. Spatial characteristics and driving factors of expansion of residential land use in Chongqing urban area from 1999 to 2018. Scientia Geographica Sinica, 2021, 41(7): 1256-1265.] doi: 10.13249/j.cnki.sgs.2021.07.016
[44]	王少剑, 高爽, 陈静. 基于GWR模型的中国城市雾霾污染影响因素的空间异质性研究[J]. 地理研究, 2020, 39(3): 651-668. doi: 10.11821/dlyj020181389
	[Wang Shaojian, Gao Shuang, Chen Jing. Spatial heterogeneity of driving factors of urban haze pollution in China based on GWR model. Geographical Research, 2020, 39(3): 651-668.] doi: 10.11821/dlyj020181389
[45]	周悦颜. 基于企业网络的京津冀地区城市联系特征及影响因素[D]. 北京: 首都师范大学, 2020.
	[Zhou Yueyan. Characteristics and influencing factors of urban connection in Beijing-Tianjin-Hebei region based on enterprise network. Beijing, China: Capital Normal University, 2020.]
[46]	王成. 山东省城市网络特征及其演化过程探析[D]. 北京: 首都师范大学, 2015.
	[Wang Cheng. Analysis of the features and evolution of the urban network in Shandong Province. Beijing, China: Capital Normal University, 2015.]
[47]	吴加伟, 陈雯, 袁丰, 等. 中国企业本土并购双方的地理格局及其空间关联研究[J]. 地理科学, 2019, 39(9): 1434-1445. doi: 10.13249/j.cnki.sgs.2019.09.009
	[Wu Jiawei, Chen Wen, Yuan Feng, et al. The geographical distribution and evolution mechanism of domestic merger and acquisition in China. Scientia Geographica Sinica, 2019, 39(9): 1434-1445.] doi: 10.13249/j.cnki.sgs.2019.09.009

影响因素	指标选取	定义
经济发展规模差异	GDP	各城市地区生产总值与北京地区生产总值的差值(万元)
经济开放程度差异	实际使用外资额	各城市实际使用外资额与北京实际使用外资额差值(万美元)
产业结构水平差异	第三产业与第二产业比值	各城市第三产业增加值与第二产业增加值的比值和北京第三产业增加值与第二产业增加值的比值的差值
交通通达性	铁路时间距离	距离北京的最短铁路行驶时间(h)
创新能力差异	专利授权量	各城市的有效专利授权量与北京有效专利授权量的差值(件)
政策环境差异	国家级经济技术开发区数量	各城市拥有的国家级经济技术开发区的数量与北京拥有的国家级经济技术开发区数量的差值(个)
劳动力成本差异	在岗职工年平均工资	各城市在岗职工年平均工资与北京在岗职工年平均工资的差值(万元)
劳动力素质差异	本专科在校生数量	各城市本专科在校生数量与北京本专科在校生数量的差值(人)

变量	对外投资	吸引投资
经济发展规模差异	-0.691^***	-0.989^***
	(-3.214)	(-5.364)
经济开放程度差异	-0.059	-0.313^**
	(-0.313)	(-1.992)
产业结构水平差异	-0.120^**	0.084^***
	(-2.909)	(-3.294)
交通通达性	-0.249^**	-0.058
	(-3.981)	(-0.978)
创新能力差异	0.165	0.220
	(1.057)	(1.418)
政策环境差异	-0.056	0.025
	(-0.606)	(0.384)
劳动力成本差异	-0.169^***	-0.063
	(-2.916)	(-1.048)
劳动力素质差异	-0.112	0.219
	(-1.046)	(0.367)
常数项	0.001	0.024
	(0.025)	(0.827)
R²	0.606	0.764

解释变量	最大值	最小值	系数绝对平均值	正值占比/%	负值占比/%
经济发展规模差异	-0.40	-3.25	0.8500	0	100.00
产业结构水平差异	0.12	-0.51	0.1352	7.17	92.83
交通通达性	0.29	-2.00	0.4600	4.78	95.22
劳动力成本差异	0.12	-0.48	0.1351	9.22	90.78

解释变量	最大值	最小值	系数绝对平均值	正值占比/%	负值占比/%
经济发展规模差异	-0.18	-1.12	0.72	0	100.00
经济开放程度差异	0.05	-0.51	0.21	18.77	81.23
产业结构水平差异	0	-0.35	0.08	0.36	99.64