Abstract
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.
Highlights
Material wealth has been greatly increased amid the rapid expansion of urbanization and global industrialization, but the consumption of a large amount of energy in the extensive model of economic development has brought severe challenges to the ecological environment, such as the greenhouse effect and the rising of sea level increased with global climate change
Durbin model as follows: Where CO2 is the carbon emission intensity, i stands for province, and t stands for year; CO2(t−1) represents the carbon emission with one-phase lag, which is used to control and investigate the time lag effect of carbon emission intensity; Senit denotes energy intensity and Aginit refers to the degree of innovation agglomeration
It is necessary to research the problems in this paper by the spatial Durbin panel model, which cannot degenerate to spatial lag model or spatial error model
Summary
Material wealth has been greatly increased amid the rapid expansion of urbanization and global industrialization, but the consumption of a large amount of energy in the extensive model of economic development has brought severe challenges to the ecological environment, such as the greenhouse effect and the rising of sea level increased with global climate change Such serious ecological and environmental problems have attracted more and more attention from governments [1]. Technological innovation, as a significant factor contributing largely to the enhancement of energy efficiency, is an important way to realize low-carbon economy, emission reduction, and energy conservation [9,10]. The spatial dynamic econometric model is used to test the relationship among innovation agglomeration, energy intensity, and carbon emission, which can control both spatial and endogenous effect.
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