Threshold effect of technological innovation on carbon emission intensity based on multi-source heterogeneous data

Abstract

It is of much importance to clarify the impact of technological innovation on carbon emission intensity for the low-carbon transformation of China's economy. This study, based on the panel data of 30 Chinese provinces and municipalities from 2010 to 2020, measures and analyzes the carbon emission intensity and the level of technological innovation, establishing a spatial econometric model to study the spatial spillover effect and a panel threshold model to analyze the nonlinear influence of technological innovation level on carbon emission intensity. The findings are as follows: First, the overall carbon emission intensity in China shows a decreasing trend from 2010 to 2020, with the average dropping from 3.09 in 2010 to 1.98 in 2020; Second, the spatial autocorrelation results reveal that the level of technological innovation and carbon emission intensity in China are obviously aggregated in the global spatial distribution pattern. Third, the regression results of the spatial econometric model show that the direct effect of technological innovation on carbon emission intensity is significantly negative at the level of 1%, that is, the improvement of the technological innovation in a certain area has a significant inhibitory effect on carbon emission intensity. Fourth, based on the level of economic development, there is a significant three-threshold effect of the level of technological innovation on carbon emission intensity in China, and the influence of the level of technological innovation on carbon emission intensity varies in the direction of existence and coefficient values within different threshold intervals. As economic development reaches the third interval, the technological innovation level has the most significant inhibition on carbon emission intensity. These findings enriches the research of the nonlinear relationship between technological innovation and carbon emission intensity, clarifies the spatial spillover effect and threshold effect between among them, and provides inspiration for better promote the low-carbon transformation of economy.