地理学报 ›› 2022, Vol. 77 ›› Issue (6): 1446-1460.doi: 10.11821/dlxb202206010
吴思栩1,2,3,4(), 孙斌栋1,2,3,4(
), 张婷麟1,2,3,4
收稿日期:
2021-03-03
修回日期:
2022-01-06
出版日期:
2022-06-25
发布日期:
2022-08-19
通讯作者:
孙斌栋(1970-), 男, 河北阜平人, 博士, 教授, 博士生导师, 研究方向为城市地理与经济地理。E-mail: bdsun@re.ecnu.edu.cn作者简介:
吴思栩(1996-), 女, 湖北黄冈人, 博士生, 研究方向为数字经济与城市发展。E-mail: wusixuecnu@163.com
基金资助:
WU Sixu1,2,3,4(), SUN Bindong1,2,3,4(
), ZHANG Tinglin1,2,3,4
Received:
2021-03-03
Revised:
2022-01-06
Published:
2022-06-25
Online:
2022-08-19
Supported by:
摘要:
本文旨在揭示互联网影响城市内部就业分布的净效应及其动态变化。首先,将互联网分散力与集聚力的相对变化纳入互联网动态影响的分析框架并提出相应理论假说;其次,利用中国2004年、2008年、2013年3次经济普查中289个地级市的2247万个企业的微观数据,以“邮区”为基本空间单元构建了城市内部就业集聚指数;最后,构造工具变量以缓解内生性问题。结果显示,平均而言,互联网能显著促进城市内部的就业集聚,但随互联网渗透率的提高,其促进作用呈现“边际递减”趋势,而城市就业的空间多中心性不断提升,即就业向远离城市主中心的次中心集聚;对于高发展水平的城市,互联网渗透率的提高促进了就业先短暂分散,而后“边际递增”式集聚。本文研究发现对于预判未来城市中经济活动的空间分布和指导空间规划具有重要意义。
吴思栩, 孙斌栋, 张婷麟. 互联网对中国城市内部就业分布的动态影响[J]. 地理学报, 2022, 77(6): 1446-1460.
WU Sixu, SUN Bindong, ZHANG Tinglin. The dynamic impact of the Internet on intra-urban employment distribution in Chinese cities[J]. Acta Geographica Sinica, 2022, 77(6): 1446-1460.
表1
主要变量统计描述
变量 | 含义 | 观测值 | 均值 | 标准差 | 最小值 | 最大值 |
---|---|---|---|---|---|---|
邮区面积 | 邮区面积(km2) | 91668 | 154.231 | 152.881 | 0.740 | 1431.892 |
德尔塔指数 | 城市内部就业集聚程度 | 842 | 0.668 | 0.104 | 0.332 | 0.971 |
基尼指数 | 城市内部就业集聚程度 | 839 | 0.801 | 0.094 | 0.337 | 0.996 |
渗透率 | 每百人互联网宽带接入用户数 | 826 | 9.198 | 10.172 | 0.089 | 92.067 |
道路面积 | 年末人均铺装道路面积(m2) | 832 | 10.139 | 16. 617 | 0.790 | 442.950 |
人口规模 | 常住人口数量(104人) | 834 | 426.087 | 295.882 | 0.006 | 3358.010 |
人口密度 | 常住人口数量/行政区域面积(104人/km2) | 833 | 0.043 | 0.038 | 0.001 | 0.445 |
人均实际GDP | 城市人均实际GDP(元) | 766 | 23914.5 | 23892.7 | 674.034 | 294592 |
制造业比重 | 本地制造业人数/本地总从业人数(%) | 842 | 25.221 | 13.746 | 1.476 | 81.296 |
职工工资 | 城镇职工平均工资(元) | 768 | 21344 | 10350 | 1208 | 68530 |
政府干预程度 | 政府非公共财政支出/全国均值(%) | 834 | 0.999 | 0.829 | 0.076 | 17.983 |
生产性服务业占比 | 城市生产性服务业从业人数/全国生产性服务业从业人数(%) | 835 | 0.352 | 0.866 | 0.011 | 12.877 |
人力资本 | 平均受教育年限(年) | 834 | 8.857 | 0.822 | 7.135 | 12.734 |
城市创新水平 | 城市创新能力指数 | 842 | 4.813 | 27.579 | 0 | 543.080 |
初始年份固定电话 | 2000年每百人固定电话数(部/百人) | 842 | 12.466 | 6.420 | 2.915 | 48.110 |
表2
互联网渗透率对城市内部就业集聚的非线性影响:OLS结果
变量 | 德尔塔指数 | 基尼指数 | |||
---|---|---|---|---|---|
(1) | (2) | (3) | (4) | ||
渗透率(ln) | 0.023* | 0.044** | 0.012 | 0.026** | |
(0.012) | (0.017) | (0.009) | (0.011) | ||
渗透率二次项(ln) | -0.012*** | -0.007*** | |||
(0.004) | (0.003) | ||||
道路面积(ln) | 0.008 | 0.002 | 0.005 | 0.002 | |
(0.018) | (0.019) | (0.014) | (0.014) | ||
人口规模(ln) | -0.247*** | -0.303*** | -0.150*** | -0.184*** | |
(0.071) | (0.080) | (0.057) | (0.064) | ||
人口密度(ln) | -0.057*** | -0.062*** | -0.043*** | -0.047*** | |
(0.019) | (0.020) | (0.015) | (0.016) | ||
人均实际GDP(ln) | -0.222*** | -0.242*** | -0.152*** | -0.164*** | |
(0.060) | (0.063) | (0.046) | (0.047) | ||
制造业比重(ln) | 0.052*** | 0.045** | 0.045** | 0.040** | |
(0.019) | (0.019) | (0.019) | (0.018) | ||
职工工资(ln) | -0.035 | -0.052 | -0.010 | -0.021 | |
(0.050) | (0.050) | (0.035) | (0.036) | ||
政府干预程度(ln) | -0.003 | -0.013 | -0.010 | -0.016 | |
(0.018) | (0.018) | (0.018) | (0.018) | ||
观测值 | 759 | 759 | 756 | 756 | |
R2 | 0.211 | 0.227 | 0.181 | 0.191 |
表3
互联网渗透率对城市内部就业集聚的非线性影响:工具变量结果
变量 | 德尔塔指数 | 基尼指数 | 多中心指数 | |||||
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | |||
A:2SLS | ||||||||
渗透率(ln) | 0.217*** | 0.445*** | 0.143*** | 0.292*** | 0.808** | 0.677** | ||
(0.067) | (0.071) | (0.050) | (0.060) | (0.318) | (0.284) | |||
渗透率二次项(ln) | -0.041*** | -0.027*** | 0.024 | |||||
(0.008) | (0.007) | (0.028) | ||||||
B:第一阶段回归 | ||||||||
初始年份固定电话( | 3.721*** | 3.721*** | 3.721*** | 3.721*** | 3.721*** | 3.721*** | ||
(0.121) | (0.121) | (0.121) | (0.121) | (0.121) | (0.121) | |||
扩散速度(α) | 0.181*** | 0.181*** | 0.181*** | 0.181*** | 0.181*** | 0.181*** | ||
(0.007) | (0.007) | (0.007) | (0.007) | (0.007) | (0.007) | |||
R2 | 0.773 | 0.773 | 0.773 | 0.773 | 0.773 | 0.773 | ||
F值 | 2514 | 2514 | 2514 | 2514 | 2514 | 2514 | ||
观测值 | 747 | 747 | 744 | 744 | 740 | 740 | ||
R2 | 0.208 | 0.253 | 0.180 | 0.213 | 0.114 | 0.115 |
表4
城市发展水平对互联网渗透率非线性影响的调节效应:工具变量结果
变量 | 德尔塔指数 | 基尼指数 | |||||||
---|---|---|---|---|---|---|---|---|---|
经济发展水平 | 生产性服务业 | 人力资本 | 创新水平 | 经济发展水平 | 生产性服务业 | 人力资本 | 创新水平 | ||
渗透率(ln) | 1.449*** | 0.280** | 1.515* | 0.315*** | 0.844*** | 0.185** | 1.033* | 0.231** | |
(0.360) | (0.116) | (0.841) | (0.112) | (0.276) | (0.091) | (0.614) | (0.092) | ||
渗透率二次项(ln) | -0.325*** | -0.011 | -0.142 | -0.032* | -0.196*** | -0.008 | -0.121 | -0.029** | |
(0.086) | (0.019) | (0.197) | (0.018) | (0.060) | (0.014) | (0.149) | (0.014) | ||
渗透率(ln)×调节变量(ln) | -0.110** | -0.085** | -0.546 | -0.056** | -0.062*** | -0.053* | -0.370 | -0.031* | |
(0.044) | (0.043) | (0.401) | (0.025) | (0.013) | (0.031) | (0.296) | (0.018) | ||
渗透率二次项(ln)×调节变量(ln) | 0.029*** | 0.018** | 0.058 | 0.013*** | 0.012*** | 0.014** | 0.050 | 0.008** | |
(0.009) | (0.009) | (0.091) | (0.004) | (0.002) | (0.006) | (0.069) | (0.003) | ||
调节变量(ln) | -0.132 | 0.118* | 0.751 | 0.066* | -0.049 | 0.061 | 0.397 | 0.034 | |
(0.097) | (0.062) | (0.514) | (0.036) | (0.049) | (0.048) | (0.394) | (0.027) | ||
观测值 | 747 | 744 | 747 | 744 | 746 | 744 | 747 | 743 | |
R2 | 0.280 | 0.239 | 0.279 | 0.230 | 0.269 | 0.233 | 0.267 | 0.223 |
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