Can Innovation Agglomeration Reduce Carbon Emissions? Evidence from China

• Published in: International journal of environmental research and public health Vol. 18; no. 2; p. 382
• Main Authors: Zhang, Jianqing, Yu, Haichao, Zhang, Keke, Zhao, Liang, Fan, Fei
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 06.01.2021; MDPI
• Subjects: Carbon; Carbon - analysis; Carbon Dioxide - analysis; China; Clean technology; Climate change; Econometrics; Economic development; Economic growth; Emissions; Energy conservation; Energy consumption; Energy efficiency; Energy management; Environmental impact; Explicit knowledge; Manufacturing; Renewable resources; China; carbon emission; energy intensity; innovation agglomeration; dynamic spatial Durbin model
• ISSN: 1660-4601; 1661-7827; 1660-4601
• DOI: 10.3390/ijerph18020382

Innovation agglomeration plays a decisive role in improving the input–output scale and marginal output efficiency of factors. This paper takes carbon emissions as the unexpected output and energy consumption as the input factor into the traditional output density model. The dynamic spatial panel Durbin model is used to analyze the mechanism for innovation agglomeration and energy intensity to affect carbon emissions from 2004 to 2017 in thirty Chinese provinces. Then, we test the possible mediating effect of energy intensity between innovation agglomeration and carbon emissions. The major findings are as follows. (1) The carbon emission intensity has time-dependence and positive spatial spillover effect. That is, there is a close correlation between current and early carbon emissions, and there is also a high-degree correlation between regional and surrounding areas’ carbon emissions. (2) Carbon emissions keep a classical inverted U-shaped relation with innovation agglomeration, as well as with energy intensity. However, the impact of innovation agglomeration on carbon emissions in inland regions of China does not appear on the right side of the inverted U-shaped curve, while carbon emissions are subject to a positive nonlinear promoting effect from energy intensity. (3) When the logarithm of innovation agglomeration is more than 3.0309, it first shows the inhibition effect on energy intensity. With the logarithm of innovation agglomeration exceeding 5.0100, it will show the dual effect of emission reduction and energy conservation. (4) Energy intensity could work as the intermediary variable of innovation agglomeration’s influence on carbon emissions. Through its various positive externalities, innovation agglomeration can produce a direct impact on carbon emissions, and through energy intensity, it can also affect carbon emissions indirectly.