An Empirical Analysis of the Synergistic Effect of Urban Pilot Policies in China

被引:2
|
作者
Wen, Jian [1 ]
Su, Shiwei [1 ]
机构
[1] Nanjing Forestry Univ, Coll Econ & Management, Nanjing 210037, Peoples R China
关键词
national innovative city pilot policy; low-carbon city pilot policy; smart city pilot policy; synergistic innovation; INNOVATION; SUBSIDIES;
D O I
10.3390/su15076313
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The strengthening of urban innovation capacity has emerged as the main force behind the promotion of the high-quality development in China because it is a significant carrier of regional innovation. This work uses the multi-time point difference approach to study the synergistic effect, mechanism, and heterogeneity among the pilot policies of national innovation city, low-carbon city and smart city based on the panel data of 282 cities from 2001 to 2016. The findings demonstrate that (1) The national innovative city pilot policies, low-carbon city pilot policies, and smart city pilot policies have a significant effect on the improvement of urban innovation and show a synergistic effect. (2) With the help of government investment in science and technology and the construction of an innovation platform, the pilot policies of smart cities and innovative cities show a superposition effect; in addition, through the upgrading of industrial structure, the green technology innovation, public participation, low-carbon urban pilot policy, and the innovative city present the supplementary effect. (3) From the perspective of heterogeneity, the superposition and supplementary effects of lower administrative level cities are better. The effect of policy synergy overlay is the largest in the eastern region, whereas the effect of policy synergy supplement is stronger in the eastern and western regions than in the central region. The robustness test supports the conclusion of this paper. This paper analyzes the collaborative innovation effect of urban pilot policies, which can provide ideas for the combination design of policy tools.
引用
收藏
页数:19
相关论文
共 50 条
  • [31] The effect of foreign direct investment on the urban wage in China: An empirical examination
    Ge, Ying
    URBAN STUDIES, 2006, 43 (09) : 1439 - 1450
  • [32] An empirical evaluation of China's monetary policies
    Fan, Longzhen
    Yu, Yihong
    Zhang, Chu
    JOURNAL OF MACROECONOMICS, 2011, 33 (02) : 358 - 371
  • [33] Empirical analysis of urban transport demand of young people and prospects of sustainable transport policies
    Venezia, E
    SUSTAINABLE DEVELOPMENT AND PLANNING II, VOLS 1 AND 2, 2005, 84 : 959 - 967
  • [34] The effect of low-carbon city pilot policy on public health: An empirical analysis of adult health in China
    Chen, Hongwen
    Dian, Jie
    Fan, Sihan
    Fang, Ying
    ECONOMIC ANALYSIS AND POLICY, 2025, 85 : 2043 - 2062
  • [35] The digital economy and entrepreneurial dynamics: An empirical analysis of urban regions in China
    Wang, Shucui
    Song, Yutong
    Du, Anna Min
    Liang, Jia
    RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE, 2024, 71
  • [36] Hedonic price analysis of urban housing: An empirical research on Hangzhou, China
    Wen H.-Z.
    Jia S.-H.
    Guo X.-Y.
    Journal of Zhejiang University-SCIENCE A, 2005, 6 (8): : 907 - 914
  • [37] An Empirical Analysis on the Influencing Factors of Urban Residents' Income Gap in China
    Wu, Yaqin
    Liu, Yang
    Guo, Qiaoli
    2011 INTERNATIONAL CONFERENCE ON APPLIED SOCIAL SCIENCE (ICASS 2011), VOL IV, 2011, : 350 - +
  • [38] Hedonic price analysis of urban housing:An empirical research on Hangzhou,China
    温海珍
    贾生华
    郭晓宇
    Journal of Zhejiang University Science A(Science in Engineering), 2005, (08) : 907 - 914
  • [39] Empirical Analysis income gap between urban and rural residents in China
    Yu, Ma
    2010 INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE AND SAFETY ENGINEERING (MSSE 2010), VOLS I AND II, 2010, : 1027 - 1030
  • [40] The effect of anti-money laundering policies: an empirical network analysis
    Peter Gerbrands
    Brigitte Unger
    Michael Getzner
    Joras Ferwerda
    EPJ Data Science, 11