地理科学进展 ›› 2020, Vol. 39 ›› Issue (4): 553-566.doi: 10.18306/dlkxjz.2020.04.003
收稿日期:
2019-04-17
修回日期:
2019-06-10
出版日期:
2020-04-28
发布日期:
2020-06-28
通讯作者:
李仙德
作者简介:
徐宁(1994— ),男,河北邢台人,硕士生,主要从事城市地理与城市经济研究。E-mail: 1299153597@qq.com
基金资助:
Received:
2019-04-17
Revised:
2019-06-10
Online:
2020-04-28
Published:
2020-06-28
Contact:
LI Xiande
Supported by:
摘要:
全球城市是世界投资网络的管理和控制中心。加强对外投资网络建设有助于上海落实2035年建成“卓越的全球城市”的发展战略目标。论文挖掘A股上市公司年报合并财务报表等信息,基于城市尺度建立上海上市公司对外投资数据库(2005、2010、2017年),利用位序-规模分析、社会网络分析、负二项回归分析等方法,研究上海上市公司对外投资网络演变及其影响因素。研究发现:① 上海上市公司对外投资网络集中于西欧、北美、东南亚、东亚等地,2005—2017年,“一带一路”沿线区域吸引的上海上市公司子公司增加了155家。② 上海上市公司对外投资网络呈现出先向国外中心城市等级扩散,再向其周边城市邻近扩散的态势。③ 上海对外投资的上市公司主要来自制造业、金融业、交通运输仓储和邮政业等,其中制造业投资网络覆盖的国外城市最多。2005—2017年,上海制造业领域的上市公司对外投资网络涉及的国外城市数量增长了102个。④ 社会邻近性、城市在世界城市网络中的等级、离岸金融中心以及方便旗国、海港对上海上市公司对外投资网络的演变具有正向的影响。
徐宁, 李仙德. 上海上市公司对外投资网络演变及其影响因素研究[J]. 地理科学进展, 2020, 39(4): 553-566.
XU Ning, LI Xiande. Evolution of Shanghai listed companies’ outward investment network and its determinants[J]. PROGRESS IN GEOGRAPHY, 2020, 39(4): 553-566.
表2
2005、2010和2017年上海上市公司在各地区投资情况"
区域 | 2005年 | 2010年 | 2017年 | |||
---|---|---|---|---|---|---|
子公司数量/家 | 比例/% | 子公司数量/家 | 比例/% | 子公司数量/家 | 比例/% | |
西欧 | 9 | 24.32 | 42 | 26.25 | 286 | 38.29 |
北美 | 9 | 24.32 | 17 | 1.63 | 121 | 16.20 |
东南亚* | 7 | 18.92 | 20 | 12.50 | 98 | 13.12 |
东亚 | 6 | 16.22 | 12 | 7.50 | 53 | 7.10 |
南美 | 1 | 2.70 | 9 | 5.63 | 40 | 5.35 |
大洋洲 | 3 | 8.11 | 7 | 4.38 | 36 | 4.82 |
西非 | 0 | 0 | 50 | 31.25 | 35 | 4.69 |
东欧* | 0 | 0 | 1 | 0.63 | 32 | 4.28 |
西亚* | 1 | 2.70 | 1 | 0.63 | 17 | 2.28 |
南亚* | 0 | 0 | 1 | 0.63 | 16 | 2.14 |
其他 | 1 | 2.70 | 0 | 0 | 13 | 1.74 |
合计 | 37 | 100.00 | 160 | 100.00 | 747 | 100.00 |
表4
上海发生对外投资行为的上市公司行业结构演变"
行业 | 2005年 | 2010年 | 2017年 | |||
---|---|---|---|---|---|---|
数量/家 | 比例/% | 数量/家 | 比例/% | 数量/家 | 比例/% | |
制造业 | 9 | 50.00 | 22 | 44.90 | 68 | 49.28 |
信息传输、软件和信息技术服务业 | 2 | 11.11 | 5 | 10.20 | 19 | 13.77 |
金融业 | 1 | 5.56 | 2 | 4.08 | 9 | 6.52 |
交通运输、仓储和邮政业 | 0 | 0 | 3 | 6.12 | 9 | 6.52 |
批发和零售业 | 1 | 5.56 | 7 | 14.29 | 8 | 5.80 |
房地产业 | 2 | 11.11 | 2 | 4.08 | 4 | 2.90 |
建筑业 | 1 | 5.56 | 3 | 6.12 | 4 | 2.90 |
综合 | 1 | 5.56 | 2 | 4.08 | 3 | 2.17 |
其他 | 1 | 5.56 | 3 | 6.12 | 14 | 10.14 |
合计 | 18 | 100.00 | 49 | 100.00 | 138 | 100.00 |
表5
解释变量指标选取及说明"
维度 | 变量 | 说明 | 预期回归系数 | 数据来源 |
---|---|---|---|---|
地理邻近性 | 地理距离(DIST) | 上海到子公司所在城市的距离(取自然对数) | - | 百度地图 |
政治邻近性 | 友好城市(SIST) | 是否友好城市 | + | 上海市政府官网 |
社会邻近性 | 汉字文化圈(CULT) | 是否属于汉字文化圈 | + | 根据胡兆量[ |
控制变量: 城市属性 | 首都(CAPI) | 是否首都 | + | 百度地图 |
海港(SEAP) | 是否海港城市 | + | 搜航网 | |
机场(AIRP) | 是否有机场 | + | 天巡网 | |
避税城市(TAX) | 是否避税港型离岸金融中心或方便旗国城市 | + | OECD/国际航运 公会(ICS) | |
Alpha级城市(ALP) | 是否Alpha级城市 | + | GaWC网站 |
表6
负二项回归结果"
自变量 | 全行业 | 制造业 | 交通业 | 金融业 | ||||
---|---|---|---|---|---|---|---|---|
2005年 | 2010年 | 2017年 | 2005年 | 2010年 | 2017年 | 2017年 | 2017年 | |
DIST | -0.268 | 0.243 | 0.211 | -0.330 | 0.053 | 0.372** | 0.478 | 1.390*** |
SIST | -0.148 | -0.042 | 0.150 | -0.143 | -0.251 | -0.049 | -0.280 | -0.093 |
CULT | 0.406 | 1.317** | 0.921*** | 0.618 | 0.645 | 1.256*** | 1.732*** | 2.055** |
CAPI | -0.035 | 0.063 | -0.173 | -0.003 | 0.010 | -0.258 | 0.189 | -0.047 |
SEAP | 0.060 | 0.309 | 0.443*** | 0.034 | -0.084 | 0.438** | 0.495 | 0.191 |
AIRP | 0.233 | 0.160 | 0.226 | -0.040 | -0.466 | |||
TAX | 1.599** | 2.123*** | 2.491*** | 0.026 | -0.196 | 1.220*** | 2.093*** | 2.037** |
ALP | 0.857 | 0.555 | 1.472*** | -0.064 | 0.478 | 0.748*** | 0.624 | 0.931*** |
常数 | 2.515 | -2.395 | -1.768 | 3.096 | -0.452 | -3.195 | -4.269 | -12.746 |
Pseudo R2 | 0.288 | 0.224 | 0.197 | 0.107 | 0.077 | 0.111 | 0.209 | 0.174 |
N | 18 | 48 | 197 | 17 | 35 | 119 | 38 | 25 |
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