scholarly journals Threshold Effect of High-Tech Industrial Scale on Green Development—Evidence from Yangtze River Economic Belt

2019 ◽  
Vol 11 (5) ◽  
pp. 1432 ◽  
Author(s):  
Yanhong Liu ◽  
Xinjian Huang ◽  
Weiliang Chen

Based on the panel data of 11 regions in the Yangtze River Economic Belt from 1998 to 2016, we tested and analyzed the effects of high-tech industrial expansion on green development. For these regions in the Yangtze River Economic Belt, we wanted to investigate the potential linear relationship between the scale of high-tech industry and green development or the possible threshold effect. We wanted to determine if this relationship is different in various regions of the Yangtze River Economic Belt. According to the empirical test, we found that: (1) for the entire Yangtze River Economic Belt region, the influence of high-tech industrial scale on green development doubled the threshold effect, and a marginal efficiency diminishing effect existed with the further increase in scale; (2) due to the differences among the regions, the threshold effect was different in different regions, with a double threshold effect in the lower reaches, a single threshold effect in the middle reaches, and no threshold effect in the upper reaches; and (3) regarding the high-tech industrial scale, the downstream areas were too large to weaken its promoting effect on green development. In the middle reaches, the positive impact on green development was still increasing, and the high-tech industrial scale should be further expanded. However, in the upstream areas, high-tech industrial scales did not reach the threshold value and the relationship between the high-tech industrial scale and green development was linear. Therefore, local high-tech industries should be cultivated and developed.

2019 ◽  
Vol 11 (19) ◽  
pp. 5189 ◽  
Author(s):  
Weiliang Chen ◽  
Xinjian Huang ◽  
Yanhong Liu ◽  
Xin Luan ◽  
Yan Song

Development is the eternal theme of the times. However, the transformation of the development mode is imminent, and we should abandon the extensive economic development mode and turn to the efficient development of an intensive mode. The high-tech industry will be the decisive force in future industrial development. The agglomeration of the industry will help form economies of scale, thereby improving the effective allocation of resources and promoting productivity. The increase in green economy efficiency is a key factor in achieving green development and an important indicator of achieving the coordinated development of economic development and environmental protection. Therefore, in this study, we try to improve the efficiency of the green economy through industrial agglomeration to achieve green development. In order to solve this problem, we took the Yangtze River Economic Belt as the research object, used Super Slacks-based Measure (SBM) data envelopment analysis (DEA) and general algebraic modeling system (GAMS) to study the green economy efficiency, and then used the system generalized moment method (SGMM) to study the impact of high-tech industry agglomeration on green economy efficiency. According to the empirical test, we found that (1) the green economy efficiency of the Yangtze River Economic Belt shows a volatile upward trend, (2) the green economy efficiency of the Yangtze River Economic Belt differs with time and by region, (3) the agglomeration of the high-tech industry has a lagging effect on the improvement of green economy efficiency, and (4) the regression coefficients of economic development and foreign direct investment are positive and those of environmental regulation and urbanization are negative. Finally, in this paper, we provide corresponding policy recommendations to promote the agglomeration of high-tech industries, thereby improving the efficiency of the green economy.


Author(s):  
Senlin Hu ◽  
Gang Zeng ◽  
Xianzhong Cao ◽  
Huaxi Yuan ◽  
Bing Chen

The role of technological innovation (TI) in green development is controversial. Based on 2003–2017 panel data of 108 cities in the Yangtze River Economic Belt (YREB), this study constructed an index system to evaluate urban green development and analyzed the role of TI on urban green development with the help of a panel econometric model. The results show that: (1) From 2003 to 2017, the levels of TI and green development of cities in the YREB have gradually improved, but the core–periphery structure is obvious, and the levels of TI and green development in the lower reaches are significantly higher than those in the middle and upper reaches. (2) TI has a significant positive role in promoting green development, showing a U-shaped nonlinear relationship, and this relationship varies from region to region. (3) TI has a significant impact on green development with direct and indirect effects. In the economic and social dimensions, TI has a positive impact on green development, while in the ecological dimension, the direct effect and indirect effect have opposite relationships. (4) TI has a significant threshold effect on green development, and there are differences in threshold characteristics between the three dimensions. These findings provide a scientific basis for policymaking about innovation-driven regional green development, and it can enrich the related theories of environmental economic geography.


2020 ◽  
Vol 12 (2) ◽  
pp. 644
Author(s):  
Zhiying Zhang ◽  
Hua Cheng ◽  
Yabin Yu

The textile industry is a traditional pillar industry of the national economy in China. The strategic goal of Chinese innovation is to upgrade and transform traditional industries and make them develop in coordination with high-tech industries, so as to realize sustainable industrial development. At the core of industrial sustainable development, the innovation of the textile industry in China has become an important issue worthy of attention. Based on resource-based theory and signal transfer theory, the relationship between government funding, R&D models and the innovation performance of the Chinese textile industry is studied. The results show that government funding has a significant, direct promoting effect on the internal R&D and science-based cooperation of enterprises. Government funding indirectly promotes market-based cooperation through internal R&D. The promoting effect of internal R&D on innovation performance is greater than that of cooperative R&D. Internal R&D and cooperative R&D have more promoting effects on R&D reserve performance than those on market performance. Government funding indirectly promotes innovation performance through the mediation of internal R&D and science-based cooperation. The threshold effect of cooperative R&D indicates that only when the cooperative R&D intensity exceeds the threshold can government funding foster innovation performance more effectively. The conclusions can provide theoretical guidance for the formulation of innovation policy.


PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260985
Author(s):  
Haijuan Yan ◽  
Xiaofei Hu ◽  
Dawei Wu ◽  
Jianing Zhang

Green development is an effective way to achieve economic growth and social development in a harmonious, sustainable, and efficient manner. Although the Yangtze River Economic Belt (YREB) plays an important strategic role in China, our understanding of its spatiotemporal characteristics, as well as the multiple factors affecting its green development level (GDL), remains limited. This study used the entropy weight method (EWM) to analyze the temporal evolution and spatial differentiation characteristics of the GDL in the YREB from 2011 to 2019. Further, fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the influence path of GDL. The results showed that the GDL of the YREB increased from 2015 to 2019, but the overall level was still not high, with high GDL mainly concentrated in the lower reaches. The GDL model changed from being environmentally driven and government supported in 2011 to being environmentally and economically driven since 2014. The core conditions for high GDL changed from economic development level (EDL) to scientific technological innovation level (STIL) and environmental regulation (ER). The path for improving GDL is as follows: In regions with high EDL, effective ER, moderate openness level (OL), and high STIL are the basis, supplemented by a reasonable urbanization scale (US). In areas with low EDL, reasonable industrial structure (IS) and STIL are the core conditions for development; further, EDL should be improved and effective ER and OL implemented. Alternatively, without considering changes to EDL, improvement can be achieved through reasonable OL and US or effective ER. This study provides a new method for exploring the path of GDL and a reference for governments to effectively adjust green development policies.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xiaohong Liu ◽  
Ching-Ter Chang

Market integration is an important tool for China’s regionally coordinated economic development. At the same time, China is implementing an innovation-driven development strategy. Therefore, the way the market integration affects regional innovation is of great significance to analyze this problem. The panel data of 27 cities in the Yangtze River Delta region in China with the highest degree of economic integration from 2009 to 2018 are used to investigate the impact of market integration (MI) on regional innovation (RI). The main findings are as follows: the first-order lag term of RI is significantly positive, and RI has certain path dependence. In this regard, MI has a positive impact on RI and promotes RI. The estimated coefficient of MI is significantly positive and has a positive impact on RI and promotes RI. This provides a reference for promoting RI through MI. The contributions of the paper are threefold: (1) This paper examines the impact of MI on RI to provide policy implications for the coordinated development of innovation between regions. (2) The relative price method is adopted to measure the MI, which covers 16 kinds of commodities, covering a wider range than does the traditional method. (3) This paper uses the generalized method of moments (GMM) to test the effect of MI on RI for the first time.


2021 ◽  
Vol 8 ◽  
Author(s):  
Gen Li ◽  
Ying Zhou ◽  
Fan Liu ◽  
Tao Wang

To explore the evolution mechanism of manufacturing green development efficiency is of great significance to realize green transformation of manufacturing industry in the Yangtze River Economic Belt. This paper fully considers the resource inputs and undesirable outputs in the production process and applies WSR methodology to construct the index system of influencing factors. Based on the panel data of 11 provinces and cities in the Yangtze River Economic Belt from 1998 to 2017, the super-SBM model is used to calculate the manufacturing green development efficiency. Then, the regional differences of manufacturing green development efficiency in the Yangtze River Economic Belt are deeply analyzed. Finally, Tobit model is applied to analyze the influencing factors of the manufacturing green development efficiency. And it turns out, during the statistics period, manufacturing green development efficiency in the Yangtze River Economic Belt is “U” shaped distribution, the mean value of each province over the years is 0.812, which is at the medium development level; the manufacturing green development efficiency in the Yangtze River Economic Belt is on the rise, and the low scale efficiency is the main reason that restricts the manufacturing green development efficiency in the Yangtze River Economic Belt. All the influencing factors have different effects on the manufacturing green development efficiency in different regions. Therefore, this paper puts forward corresponding policy suggestions from the three dimensions of Wuli, Shili and Renli.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Cai Shukai ◽  
Wang Haochen ◽  
Zhou Xiaohong

This paper proposed a substantial gap to a large-scale population density and city size on regional innovation output. To measure the impact of population density and city size on regional innovation output, this study employs the threshold effect model with panel data of 230 prefectures and cities from 2007 to 2016. Based on the econometric analysis, the results exhibit a positive and significant relationship between population density, city size, and innovation output. This correlation suggests that when one factor increases, the other increases in the parallel direction and vice versa. Moreover, when the city size expands the threshold value of 2.934 percent, the innovation promotes and increases the effects of urban-scale expansion. On the other hand, for medium- and low-density cities, the increase of urban population density has a significant and positive impact on urban innovation output. However, for high-density cities, the increase of population density has no significant impact on innovation output.


Sign in / Sign up

Export Citation Format

Share Document