External knowledge sourcing and green innovation growth with environmental and energy regulations: Evidence from manufacturing in China

Abstract

This paper adopts the slacks-based measure-directional distance function (SBM-DDF, 2009) method for deriving the "Green Innovation Growth" rates of 28 manufacturing industries in China. The results indicate that the overall level of green innovation growth in China's manufacturing is relatively low, with a declining trend. The tradeoffs among energy, environment and economy are rather sharp, and the "Porter Effect (1995)" (environmental regulation will promote green technology innovation) is not currently realized quickly in manufacturing. These evaluations imply an unsustainable development model in China, with significant differences among industries. By using a dynamic panel threshold model and employing an industry-level panel dataset for 2008-2014, we show that external knowledge sourcing has a significant negative impact on green innovation growth but with different constraints on R & D levels among industries. With the strengthening of R & D levels, gradually surpassing "critical mass", the negative role of external knowledge sourcing in driving this mechanism becomes smaller and smaller; it has a non-linear relationship with the "threshold effect". Consequently, we provide insights into the relationship among energy consumption, environmental pollution and technology innovation, and show how the heterogeneity of the R & D threshold affects differences in external knowledge sourcing and green innovation growth. These insights lead to a better understanding of the driving force, realizing path and policy design for green innovation growth.