Mechanism analysis of the influence of intelligent manufacturing on carbon emission intensity: evidence from cross country and industry

How to reduce carbon emission intensity is a common challenge facing in various countries, particularly in developing countries. We identify three literature gaps: theoretical framework of a novel perspective of intelligent manufacturing (IM) influencing carbon intensity, empirical tests by solving endogeneity with cross country and industry data to answer why IM influences carbon intensity, and mediation analysis to explain how IM influences carbon intensity. By applying the World Input-Output Database (WIOD) and environmental account database with panel data of 13 manufacturing sectors in 39 economies from 2000 to 2011, we reveal that IM has a significant reduction in carbon intensity after considering endogeneity and robust check. Our mechanism test demonstrates that energy consumption structure and position in global value chains (GVCs) are main channels. Heterogeneity analysis reveals that developing countries have larger carbon restraining influence by IM. The contributions of this study are: First, this study investigates restraining influence on carbon intensity from novel perspective of IM, which enriches theoretical analysis. Second, this study takes advantage of cross country and industry data to test and adopts Generalized Method of Moments (GMM) model to solve endogeneity, which answers why IM influences carbon intensity. Further, this paper performs heterogeneity analysis and explores the mediating effects played by improving energy consumption structure and enhancing position in global value chains (GVCs), which answers how IM influences carbon intensity.