智慧城市建设是否促进了新型城镇化与市场一体化：鱼和熊掌不可兼得？

doi:10.13284/j.cnki.rddl.003664

Abstract

Abstract:

Smart city construction will have a profound impact on urban development and regional pattern, and it is necessary to explore its impact on new urbanization and regional market integration, so as to provide empirical evidence for accelerating the construction of smart cities. Based on the panel data of 238 prefecture-level cities from 2005 to 2019, this study considers the establishment of the national smart city pilot as a quasi-natural experiment and includes it in the analysis of the factors influencing market integration. The multi-period difference method was used to empirically investigate the influence of smart city pilot construction on market integration at the prefecture-level city level. The conclusions are as follows. According to the calculation results, the degree of inter-city market segmentation in the whole sample period from 2005 to 2019 showed a trend of shock decline, except that the degree of inter-city market segmentation increased in 2008 and 2009. The benchmark regression results show that although smart city pilot construction can promote economic urbanization, social urbanization, and environmental urbanization of the pilot cities, it is not conducive to market integration among cities. The conclusion that smart city construction will intensify market segmentation remains valid even after a series of robustness tests. The influence of smart city construction on inter-city market integration varies according to city level, city size, and city location, which is mainly manifested in the fact that it significantly inhibits the market integration of low-level cities, small and medium-sized cities, and inland cities, and significantly promotes the market integration of big cities and coastal cities. The influence mechanism shows that narrowing the information infrastructure gap not only helps in playing the role of smart city construction in promoting the development of new urbanization but also promotes market integration among cities. Narrowing the gap in public expenditure is conducive to the promotion of smart city construction for social urbanization and alleviates market segmentation among cities. Promoting the development of secondary industries can enhance environmental urbanization and ease market segmentation. Therefore, in the context of building a national unified large market, the pilot construction of smart cities should pay full attention to the negative effects of the "digital divide" between regions, encourage some localities with conditions to strengthen the construction of smart cities independently, and prevent the "digital divide" between regions from widening. This study further enriches the research on the factors influencing market integration at the city level and simultaneously provides some references for urban digital transformation and the development of new urbanization.

Key words: smart city construction, new urbanization, market integration, double difference method, China

CLC Number:

F127

Hui Zhang, Hanyue Zhang, Renjun Li. Does Smart City Construction Promote New Urbanization and Market Integration: Can We Have Both?[J].Tropical Geography, 2023, 43(4): 681-694.

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References 0

	Baye M R, Morgan J, and Scholten P. 2004. Price Dispersion in the Small and in the Large: Evidence from an Internet Price Comparison Site. The Journal of Industrial Economics, 52(4): 463-496.
	Bonfadelli H. 2002. The Internet and Knowledge Gaps: A Theoretical and Empirical Investigation. European Journal of Communication, 17(1): 65-84.
	陈朴，林垚，刘凯. 2021. 全国统一大市场建设、资源配置效率与中国经济增长. 经济研究，56（6）：40-57.
	Chen Pu, Lin Yao, and Liu Kai. 2021. The Construction of a Unified National Market, Efficiency of Resource Allocation and Economic Growth in China. Economic Research Journal, 56(6): 40-57.
	Corrocher N. 2002. Ordanini A. Measuring the Digital Divide: A Framework for the Analysis of Cross-Country Differences. Journal of Information Technology, 17(1): 9-19.
	戴一鑫，卢泓宇. 2022. 高技术产业集聚对长江经济带新型城镇化的影响——基于空间溢出效应的视角. 软科学，[2022-07-14].http://kns.cnki.net/kcms/detail/51.1268.g3.20220713.1356.012.html，1-23. [Dai Yixin, and Lu Hongyu. 2022. The Impact of High-Tech Industrial Agglomeration on the New Urbanization of the Yangtze River Economic Belt-Perspective Based on Spatial Spillover Effects. Soft Science, [2022-07-14].http://kns.cnki.net/kcms/detail/51.1268.g3.20220713.1356.012.html, 1-23. ]
	范欣，宋冬林，赵新宇. 2017. 基础设施建设打破了国内市场分割吗?. 经济研究，52（2）：20-34.
	Fan Xin, Song Donglin, and Zhao Xinyu. 2017. Does Infrastructure Construction Break up Domestic Market Segmentation?. Economic Research Journal, 52(2): 20-34.
	付平，刘德学. 2019. 智慧城市技术创新效应研究—基于中国282个地级城市面板数据的实证分析. 经济问题探索，（9）：72-81.
	Fu Ping, and Liu Dexue. Research on the Effect of Technological Innovation in Smart Cities: An Empirical Analysis Based on the Panel Data of 282 Prefecture -Level Cities in China. Inquiry into Economic Issues, (9): 72-81 .
	辜胜阻，杨建武，刘江日. 2013. 当前我国智慧城市建设中的问题与对策. 中国软科学，（1）：6-12.
	Gu Shengzu, Yang Jianwu, and Liu Jiangri. 2013. Problems in the Development of Smart City in China and Their Solution. China Soft Science, (1): 6-12.
	Gorodnichenko Y, Sheremirov V, and Talavera O. 2018. Price Setting in Online Markets: Does IT Click?. Journal of the European Economic Association, 16(6): 1764-1811.
	桂琦寒，陈敏，陆铭，陈钊. 2006. 中国国内商品市场趋于分割还是整合：基于相对价格法的分析. 世界经济，（2）：20-30.
	Gui Qihan, Chen Min, Lu Ming, and Chen Zhao. 2006. China's Domestic Commodity Market Tends to be Divided or Integrated: Analysis Based on Relative Price Method. The Journal of World Economy, (2): 20-30.
	胡丽娜，薛阳，孙倩. 2022. 财政分权对新型城镇化的影响及作用机制研究——有调节的中介和门槛效应检验. 经济体制改革，（5）：144-150.
	Hu Lina, Xue Yang, and Sun Qian. 2022. Research on the Influence Mechanism of Fiscal Decentralization on New Urbanization-Moderated Mediation and Threshold Testing. Reform of Economic System, (5): 144-150.
	蒋选，王林杉. 2021. 智慧城市政策的产业结构升级效应研究——基于多期DID的经验考察. 中国科技论坛，（12）：31-40.
	Jiang Xuan, and Wang Linshan. 2021. The Upgrading Effect of Industrial Structure of Smart City Policy: An Empirical Study Based on Time-Varying DID. Forum on Science and Technology in China, (12): 31-40 .
	吕冰洋，贺颖. 2020. 迈向统一市场：基于城市数据对中国商品市场分割的测算与分析. 经济理论与经济管理，（4）：13-25.
	Lu Bingyang, and He Ying. 2020. On the Trend of Regional Market Integration: Measurement and Analysis of Chinese Commodity Market Segmentation Based on City Data. Economic Theory and Business Management, (4): 13-25.
	李杰伟，吴思栩. 2020. 互联网、人口规模与中国经济增长：来自城市的视角. 当代财经，（1）：3-16.
	Li Jiewei, and Wu Sixiang. 2020. Internet, Population Scale and China's Economic Growth: From the City Perspective. Contemporary Finance & Economics, (1): 3-16.
	Niebel T. 2018. ICT and Economic Growth: Comparing Developing, Emerging and Developed Countries. World Development, 104: 197-211.
	Poncet S. 2003. Measuring Chinese Domestic and International Integration. China Economic Review, 14(1): 1-21.
	邱泽奇，张樹沁，刘世定，张英康. 2016. 从数字鸿沟到红利差异——互联网资本的视角. 中国社会科学，（10）：93-115.
	Qiu Zeqi, Zhang Shuqin, Liu Shicheng, and Zhang Yingkang. 2016. From the Digital Divide to Dividend Difference: From the Perspective of Internet Capital. Social Sciences in China, (10): 93-115.
	孙震，刘健平，刘涛雄. 2021. 跨平台竞争与平台市场分割——基于中国线上市场价格离散的证据. 中国工业经济，（6）：118-136.
	Sun Zhen, Liu Jianping and Liu Taoxiong. 2021. Cross-Platform Competition and Market Segmentation in China's Online Market: Evidence Based on Platform and Price Dispersion. China Industrial Economics, (6): 118-136.
	石大千，李格，刘建江. 2020，信息化冲击、交易成本与企业TFP——基于国家智慧城市建设的自然实验. 财贸经济，41（3）：117-130.
	Shi Daqian, Li Ge, and Liu Jianjiang. 2020. Information Impact, Transaction Cost and Enterprise TFP: Natural Experiments Based on Chinese Smart City Construction. Finance & Trade Economics, 41 (3): 117-130.
	孙博文，尹俊. 2021. 交通投资何以实现高质量的市场一体化?——基于地理性与制度性市场分割的视角. 宏观质量研究，9（1）：113-128.
	Sun Bowen, and Yin Jun. 2021. How can Transportation Investment Achieve High Quality Market Integration? A Perspective Based on Geographical and Institutional Market Segmentation. Journal of Macro-Quality Research, 9(1): 113-128.
	Stigler G J. 1961. The Economics of Information. Journal of Political Economy, 69(3): 213-225.
	唐斯斯，张延强，单志广，王威，张雅琪. 2020. 我国新型智慧城市发展现状、形势与政策建议. 电子政务，（4）：70-80.
	Tang Sisi, Zhang Yanqiang, Shan Zhiguang, Wang Wei and Zhang Yaqi. 2020 . The Status Quo, Situation and Policy Suggestions of the Development of New-Type Smart Cities in China. E-Government, (4): 70-80.
	van Dijk J A G M. 2006. Digital Divide Research, Achievements and Shortcomings. Poetics, 34(4): 221-235.
	许宪春，张美慧. 2020 . 中国数字经济规模测算研究——基于国际比较的视角. 中国工业经济，（5）：23-41. [Xu Xianchun, and Zhang Meihui. 2020. Research on the Scale Measurement of China's Digital Economy: Based on the Perspective of International Comparison. China Industrial Economics, (5): 23-41.
	谢莉娟，张昊. 2015. 国内市场运行效率的互联网驱动——计量模型与案例调研的双重验证. 经济理论与经济管理，（9）：40-55.
	Xie Lijuan, and Zhang Hao. 2015 . The Internet Drive in Domestic Market Operating Efficiency: Analysis Based on Econometric Model and Case Study. Economic Theory and Business Management, (9): 40-55.
	谢莉娟，严玉珊，张昊. 2018. 互联网与国内区域市场整合：促进还是阻碍?——基于空间计量的实证检验. 产业经济评论，17（4）：19-45.
	Xie Lijuan, Yan Yushan, and Zhang Hao. 2018. Internet and the Integration of Domestic Regional Markets: Promotion or Hindrance?: An Empirical Test Based on Spatial Econometrics. Review of Industrial Economics, 17(4): 19-45.
	谢非，袁露航，傅炜. 2021. 长三角区域何以实现高质量市场一体化？——基于对外开放、产业结构升级、金融发展视角. 改革，（6）：112-124.
	Xie Fei, Yuan Luhang, and Fu Wei. 2021. How can Yangtze River Delta Realize High-Quality Market Integration?: From the View of Opening Up, Upgrading of Industrial Structure and Financial Development. Reform, (6): 112-124.
	阳敏，毛军. 2017. 财税竞争与中国市场一体化发展的空间关联分析. 经济地理，37（9）：57-61.
	Yang Min, and Mao Jun. 2017. Spatial Correlation Analysis of Fiscal and Taxation Competition and Chinese Market Integration Development. Economic Geography, 37(9): 57-61.
	杨瑞，张然，许航. 2022. 数字经济能否促进新型城镇化的发展?—来自284个城市的经验证据. 城市发展研究，29（6）：102-109.
	Yang Rui, Zhang Ran, and Xu Hang. 2022. Can Digital Economy Promote the New Urbanization: Based on the Empirical Test of 284 Cities in China. Urban Development Studies, 29(6): 102-109.
	Young A. 2000. The Razor's Edge: Distortions and Incremental Reform in the People's Republic of China. The Quarterly Journal of Economics, 115(4): 1091-1135.
	于斌斌，陈露. 2019. 新型城镇化能化解产能过剩吗?. 数量经济技术经济研究，36（1）：22-41.
	Yu Binbin, and Lu Chen. 2019. Can New-Type Urbanization Resolve Excess Production Capacity?. Journal of Quantitative & Technological Economics, 36(1): 22-41.
	袁航，朱承亮. 2020. 智慧城市是否加速了城市创新?. 中国软科学，（12）：75-83.
	Yuan Hang, and Zhu Chengliang. 2020. Do Smart Cities Accelerate Urban Innovation?. China Soft Science, (12): 75-83.
	张治栋，赵必武. 2021. 智慧城市建设对城市经济高质量发展的影响——基于双重差分法的实证分析. 软科学，35（11）：65-70，129.
	Zhang Zhidong, and Zhao Biwu. 2021. The Impact of Smart City Construction on the High-Quality Development of Urban Economy: Empirical Analysis Based on Double Difference Method. Soft Science, 35 (11): 65-70, 129.
	曾亿武，孙文策，李丽莉，傅昌銮. 2022 . 数字鸿沟新坐标：智慧城市建设对城乡收入差距的影响. 中国农村观察，（3）：165-182.
	Zeng Yiwu, Sun Wence, Li Lili, and Fu Changluan. 2022. A New Coordinate of Digital Divide: The Impact of Smart City Construction on Urban-Rural Income Gap. China Rural Survey, (3): 165-182.
	朱海龙，张志雄. 2021. 中国智慧化建设区域差异研究. 经济地理，41（8）：54-61，80.
	Zhu Hailong, and Zhang Zhixiong. 2021. Regional Differences of China's Intelligent Construction. Economic Geography, 41(8): 54-61, 80 .
	赵涛，张智，梁上坤. 2020. 数字经济、创业活跃度与高质量发展——来自中国城市的经验证据. 管理世界，36（10）：65-76.
	Zhao Tao, Zhang Zhi, and Liang Shangkun. 2020. Digital Economy, Entrepreneurship and High-Quality Economic Development: Empirical Evidence from Urban China. Journal of Management World, 36(10): 65-76.

变量符号	变量名称	样本数/个	平均值	标准差	最小值	最大值
seg	市场分割	3 570	0.034 9	0.029 6	0.007 69	0.458
smct	智慧城市	3 570	0.145	0.352	0	1
pop-urban	人口城镇化	3 570	0.495	0.17	0.099 5	1
eco-urban	经济城镇化	3 570	3.339	0.882	0.676	6.319
sco-urban	社会城镇化	3 570	9.605	0.888 2	6.461	11.99
env-urban	环境城镇化	3 570	0.019 4	0.066 6	0.000 084	2.928
open	对外开放	3 570	0.226	0.521	0.000 2	10.07
inform	信息基础	3 570	6.602	0.808	4.249	10.35
fin	金融发展	3 570	2.158	1.079	0.731	21.30
dense	经济密度	3 570	0.258	0.618	0.000 76	13.48
soe	国有化	3 570	0.474	0.196	0.015 9	1.000
gov	政府干预	3 570	0.657	0.654	0.041 2	10.94
indus	工业化水平	3 570	1.331	0.636	0.105	7.416
edu	教育水平	3 570	1.654	2.012	0.006 96	15.63
inter	通信网络	3 570	0.159	0.136	0.000 056	1.00

变量	pop_urban	eco_urban	sco_urban	env_urban	seg
smct	0.008 01（0.673 9）	0.031 41^*（0.017 4）	0.113 30^***（0.041 1）	-0.013 16^***（0.004 8）	0.003 96^***（0.00 15）
soe	-1.083 27（2.226 2）	0.0105 3（0.061 1）	0.006 37（0.127 5）	0.029 21（0.025 8）	0.002 77（0.005 3）
gov	77.944 69（128.690 1）	3.811 18（2.620 3）	-3.235 27（4.989 7）	-1.166 17^*（0.634 1）	-0.012 00（0.203 4）
indus	0.1044 8（0.310 1）	0.097 61^***（0.009 9）	0.113 59^***（0.022 1）	0.010 24^*（0.005 5）	0.001 56（0.001 0）
inform	0.461 54（0.455 7）	0.022 45^**（0.011 4）	0.0764 7^***（0.023 7）	0.001 11（0.001 9）	-0.002 80^***（0.000 9）
fin	-0.456 01（0.280 4）	-0.050 61^***（0.015 1）	-0.115 35^**（0.048 0）	-0.000 55（0.000 6）	-0.001 05^*（0.000 6）
dense	-0.687 35（0.915 1）	-0.103 08^***（0.022 5）	-0.108 26^*（0.056 6）	0.008 41^*（0.004 8）	0.001 47（0.001 9）
open	0.893 07（0.852 1）	-0.017 31（0.021 7）	0.061 82（0.052 0）	0.005 24（0.003 6）	-0.001 21（0.000 9）
edu	0.747 68^*（0.387 9）	0.003 80（0.008 5）	0.008 13（0.015 5）	0.001 97（0.002 7）	-0.001 35（0.001 5）
inter	-1.072 84（1.583 5）	-0.026 91（0.041 1）	0.003 38（0.104 0）	-0.005 31（0.005 2）	0.009 65^*（0.004 9）
城市固定效应	YES	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES	YES
观测值	3 570	3 570	3 570	3 570	3 570
R²	0.592	0.928	0.834	0.072	0.431

变量	eco-urban	sco-urban	env-urban	seg
d_4	0.004 41（0.011 2）	0.015 05（0.022 0）	0.008 19（0.011 7）	0.000 90（0.002 6）
d_3	0.006 64（0.013 5）	0.0148 8（0.030 0）	0.035 02（0.031 3）	0.002 11（0.002 4）
d_2	0.006 92（0.013 6）	0.027 06（0.024 9）	0.021 62（0.020 3）	0.001 89（0.002 0）
d_1	0.011 71（0.013 7）	0.033 95（0.024 5）	0.001 68（0.002 6）	-0.000 27（0.001 8）
d1	0.033 48^*（0.017 5）	0.104 50^***（0.032 6）	-0.001 83（0.001 7）	0.004 02^**（0.002 0）
d2	0.052 83^**（0.021 9）	0.140 27^***（0.046 6）	-0.005 60^***（0.002 1）	0.003 90^*（0.002 2）
d3	0.045 34^*（0.023 8）	0.119 25^**（0.055 6）	-0.007 34^***（0.002 5）	0.006 43^**（0.003 1）
d4	0.049 02^*（0.027 7）	0.096 68（0.065 3）	-0.009 26^**（0.003 6）	0.003 10（0.002 1）
控制变量	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES
观测值	3 570	3 570	3 570	3 570
R²	0.915	0.835	0.079	0.430

变量	强度DID回归	缩短样本年份	剔除特殊城市	省-年固定效应
smct	—	0.003 01^*（0.001 74）	0.004 11^**（0.002 06）	0.003 39^**（0.001 50）
Dige×smct	0.002 15^**（0.000 84）	—	—	—
控制变量	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES
省-年固定效应	NO	NO	NO	YES
观测值	2 115	2 618	3 120	3 570
R²	0.144	0.449	0.325	0.550

变量	干扰性政策	金融危机	改变处理组		工具变量
smct	0.003 79^**（0.001 48）	0.003 96^**（0.001 52）	0.004 15^**（0.001 8）	0.004 16^**（0.002 1）	0.028 79^*（0.014 9）
电商示范城市	控制	—	—	—	—
创新型城市	控制	—	—	—	—
宽带中国试点	控制	—	—	—	—
crisis	—	0.012 4^***（0.002 38）	—	—	—
控制变量	YES	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES	YES
观测值	3 570	3 570	3 570	2 760	3 570
R²	0.433	0.431	0.431	0.341	0.230

Does Smart City Construction Promote New Urbanization and Market Integration: Can We Have Both?

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变量	城市等级		城市规模		城市区位
变量	高	低	大	中小	沿海	内陆
smct	-0.001 60（0.003 6）	0.004 50^*（0.002 2）	-0.004 43^*（0.002 5）	0.007 30^***（0.002 7）	-0.005 65^*（0.003 3）	0.005 79^***（0.002 1）
控制变量	YES	YES	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES	YES	YES
观测值	690	2 880	1 095	2 475	660	2 910
R²	0.471	0.357	0.323	0.349	0.324	0.335
id	46	192	73	165	44	194

变量	eco-urban	sco-urban	env-urban	seg
smct	0.033 2^**（0.016 5）	0.143^***（0.036 4）	-0.012 1^**（0.005 36）	0.003 27（0.001 99）
smct×infgap	-0.516^***（0.168 3）	-1.876^***（0.375）	0.122^*（0.063 7）	0.043 3^*（0.024 8）
infgap	0.335^***（0.118）	0.919^***（0.234）	0.007 27（0.027 0）	-0.038 9^**（0.017 6）
控制变量	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES
观测值	3 570	3 570	3 570	3 570
R²	0.935	0.857	0.082	0.328

变量	eco_urban	sco_urban	env_urban	seg
smct	0.021 8（0.016 0）	0.108^***（0.033 0）	-0.014 1^**（0.005 87）	0.004 05^**（0.001 9）
smct×fisgap	-0.001 58（0.002 99）	-0.022 5^***（0.006 82）	0.002 63^***（0.000 88）	0.000 92^***（0.000 31）
fisgap	0.0125^***（0.003 84）	0.043 7^***（0.010 1）	0.002 11^***（0.000 58）	0.000 197（0.000 27）
控制变量	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES
观测值	3 570	3 570	3 570	3 570
R²	0.936	0.865	0.086	0.328

变量	eco_urban	sco_urban	env_urban	seg
smct	0.018 9（0.016 1）	0.097 6^***（0.035 8）	-0.016 7^**（0.007 1）	0.0039 8^**（0.001 83）
smct×indus	-0.017 0（0.019 8）	0.033 7（0.045 5）	-0.018 13^*（0.010 1）	-0.005 75^**（0.002 72）
indus	0.090 0^***（0.011 1）	0.116^***（0.021 1）	0.018 1（0.013 1）	0.024 4^*（0.001 38）
控制变量	YES	YES	YES	YES
城市固定效应	YES	YES	YES	YES
年份固定效应	YES	YES	YES	YES
观测值	3 570	3 570	3 570	3 570
R²	0.935	0.854	0.084	0.328

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