Literature DB >> 32092916

Government R&D Subsidies, Environmental Regulations, and Their Effect on Green Innovation Efficiency of Manufacturing Industry: Evidence from the Yangtze River Economic Belt of China.

Ming Yi1, Yiqian Wang1, Modan Yan2, Lina Fu3, Yao Zhang1.   

Abstract

The Yangtze River Economic Belt is the most important manufacturing economic belt in China. The level of manufacturing green innovation efficiency of the Yangtze River Economic Belt directly affects the overall competitiveness of China's manufacturing industry. With panel data from 11 provinces and cities along the Yangtze River Economic Belt in China for the period of 2008 to 2017, this paper applies the slacks-based measure (SBM)-data envelopment analysis (DEA) model and panel Tobit model to conduct an empirical study of the effects of government research and development subsidies and environmental regulations on the green innovation efficiency of the manufacturing industry of the Yangtze River Economic Belt. The results show that, firstly, government R&D subsidies and environmental regulations are both conducive to improving the green innovation efficiency of the manufacturing industry of the Yangtze River Economic Belt; secondly, because of the fact that the interaction terms between government R&D subsidies and environmental regulations failed to pass the significance test, the positive moderating effects of R&D subsidies on environmental regulations and green innovation efficiency of the manufacturing industry are not obvious; thirdly, in terms of control variables, strengthening agglomeration is the only factor that is positively correlated with green innovation efficiency improvement of the manufacturing industry. Enterprise scale and industrial structure have negative effects on green innovation efficiency improvement, and the openness of economy has no correlation with green innovation efficiency.

Entities:  

Keywords:  D subsidies; environmental regulations; government R& green innovation efficiency of manufacturing industry; panel Tobit model

Year:  2020        PMID: 32092916     DOI: 10.3390/ijerph17041330

Source DB:  PubMed          Journal:  Int J Environ Res Public Health        ISSN: 1660-4601            Impact factor:   3.390


  11 in total

1.  Research on coupling coordination and influencing factors between Urban low-carbon economy efficiency and digital finance-Evidence from 100 cities in China's Yangtze River economic belt.

Authors:  Fengge Yao; Liqing Xue; Jiayuan Liang
Journal:  PLoS One       Date:  2022-07-29       Impact factor: 3.752

2.  The spatial spillover effect of environmental regulation on the total factor productivity of pharmaceutical manufacturing industry in China.

Authors:  Qijie Wu; Yuexin Li; Yufei Wu; Fei Li; Shen Zhong
Journal:  Sci Rep       Date:  2022-07-08       Impact factor: 4.996

3.  Exploring an Efficient Evolutionary Game Model for the Government-Enterprise-Public during the Double Carbon Policy in China.

Authors:  Bilin Zou; Chunhua Ju; Fuguang Bao; Ye Lai; Chonghuan Xu; Yiwen Zhu
Journal:  Int J Environ Res Public Health       Date:  2022-04-11       Impact factor: 4.614

4.  Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt.

Authors:  Mengchao Yao; Jinjun Duan; Qingsong Wang
Journal:  Int J Environ Res Public Health       Date:  2022-05-24       Impact factor: 4.614

5.  Can Green Economy and Ecological Welfare Achieve Synergistic Development? The Perspective of the "Two Mountains" Theory.

Authors:  Lindong Ma; Yuanxiao Hong; Xihui Chen
Journal:  Int J Environ Res Public Health       Date:  2022-05-26       Impact factor: 4.614

6.  How Do Environmental Technology Standards Affect the Green Transformation? New Evidence from China.

Authors:  Xiufeng Zhang; Yan Li; Ke Shi; Yanchao Feng
Journal:  Int J Environ Res Public Health       Date:  2022-05-12       Impact factor: 4.614

7.  Spatial analysis, coupling coordination, and efficiency evaluation of green innovation: A case study of the Yangtze River Economic Belt.

Authors:  Ye Tian; Peng Huang; Xu Zhao
Journal:  PLoS One       Date:  2020-12-09       Impact factor: 3.240

8.  Do Managerial Ties Help or Hinder Corporate Green Innovation? The Moderating Roles of Contextual Factors.

Authors:  Yu Zhang; Yajuan Wang
Journal:  Int J Environ Res Public Health       Date:  2022-03-28       Impact factor: 3.390

9.  Spatial and temporal evolution of urban economic development efficiency in China's Yangtze River economic belt from the perspective of sustainable development.

Authors:  Fengge Yao; Liqing Xue; Jiayuan Liang
Journal:  PLoS One       Date:  2022-09-12       Impact factor: 3.752

10.  Evaluating Green Innovation Efficiency and Its Socioeconomic Factors Using a Slack-Based Measure with Environmental Undesirable Outputs.

Authors:  Hongxu Guo; Zihan Xie; Rong Wu
Journal:  Int J Environ Res Public Health       Date:  2021-12-07       Impact factor: 3.390

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