Does haze pollution inhibit innovation efficiency in China? The mediating role of human capital and the moderating role of government attention

被引:0
作者
Wang, Qian [1 ]
Zhang, Songzi [2 ]
Ren, Shuming [2 ]
机构
[1] Dalian Maritime Univ, Sch Maritime Econ & Management, Dalian 116026, Peoples R China
[2] Dalian Univ Technol, Sch Econ & Management, Dalian 116024, Peoples R China
基金
中国国家自然科学基金;
关键词
Haze pollution; Innovation efficiency; Human capital; Government attention; Spatial Durbin Tobit model; Dynamic threshold model; AIR-POLLUTION; ENVIRONMENTAL-POLICY; PRODUCTIVITY; SYSTEMS; GROWTH;
D O I
10.1016/j.jclepro.2024.144261
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The problem of low innovation efficiency in developing countries has gained increasing attention, although there is little empirical evidence to examine this issue, especially from a haze pollution perspective. To fill this critical gap, this paper employs a series of empirical methods to investigate the impact of haze pollution on innovation efficiency and takes a panel dataset covering 30 provincial-level regions in China over 2010-2018 as a case study. Results show that: (1) An increase in haze pollution has an inhibitory effect on China's provincial innovation efficiency, whether for the overall, R&D, and commercialization efficiency. (2) Such a negative effect is exacerbated in provinces with low levels of urbanization and financial development, presenting a preference for poor territories. (3) Regarding spatial spillover effects, innovation efficiency in a given province is negatively correlated with haze pollution from neighboring provinces. (4) Regarding mediating factors, haze pollution reduces human capital and subsequently can inhibit innovation efficiency, i.e., the "human capital loss effect". (5) Regarding moderating factors, rather than a "cost following effect", government attention mitigates the inhibiting effect of haze pollution on innovation efficiency through an "innovation compensation effect". In general, policymakers should seek a win-win situation between innovation activities and environmental protection.
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页数:17
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共 65 条
  • [1] Transition to Clean Technology
    Acemoglu, Daron
    Akcigit, Ufuk
    Hanley, Douglas
    Kerr, William
    [J]. JOURNAL OF POLITICAL ECONOMY, 2016, 124 (01) : 52 - 104
  • [2] The Environment and Directed Technical Change
    Acemoglu, Daron
    Aghion, Philippe
    Bursztyn, Leonardo
    Hemous, David
    [J]. AMERICAN ECONOMIC REVIEW, 2012, 102 (01) : 131 - 166
  • [3] A MODEL OF GROWTH THROUGH CREATIVE DESTRUCTION
    AGHION, P
    HOWITT, P
    [J]. ECONOMETRICA, 1992, 60 (02) : 323 - 351
  • [4] How does air pollution affect urban innovation capability? Evidence from 281 cities in China
    Ai, Hongshan
    Wang, Mengyuan
    Zhang, Yue-Jun
    Zhu, Tian-Tian
    [J]. STRUCTURAL CHANGE AND ECONOMIC DYNAMICS, 2022, 61 : 166 - 178
  • [5] How does government attention matter in air pollution control? Evidence from government annual reports
    Bao, Rui
    Liu, Tianle
    [J]. RESOURCES CONSERVATION AND RECYCLING, 2022, 185
  • [6] THE MODERATOR MEDIATOR VARIABLE DISTINCTION IN SOCIAL PSYCHOLOGICAL-RESEARCH - CONCEPTUAL, STRATEGIC, AND STATISTICAL CONSIDERATIONS
    BARON, RM
    KENNY, DA
    [J]. JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY, 1986, 51 (06) : 1173 - 1182
  • [7] Broner F., 2012, Sources of Comparative Advantage in Polluting Industries
  • [8] Instrumental variable estimation of a threshold model
    Caner, M
    Hansen, BE
    [J]. ECONOMETRIC THEORY, 2004, 20 (05) : 813 - 843
  • [9] The impact of technological innovation on air pollution: Firm-level evidence from China
    Chen, Fenglong
    Wang, Meichang
    Pu, Zhengning
    [J]. TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE, 2022, 177
  • [10] Natural resources, urbanization and regional innovation capabilities
    Chen, Jian
    Wang, Lingjun
    Li, Yuanyuan
    [J]. RESOURCES POLICY, 2020, 66 (66)