Artificial Intelligence and Carbon Emissions: Mediating Role of Energy Efficiency, Factor Market Allocation and Industrial Structure
Liu Jun, Hengxu Shen, Junwei Chen, Xin Jiang, Abdul Waheed Siyal
Abstract
Artificial intelligence (AI) plays an important role in promoting energy transformation and achieving global green and low-carbon goals. Based on the panel data of 285 prefecture-level cities in China from 2011 to 2022, this paper empirically examines the impact of AI on carbon emission (CE) and its internal mechanism. It is found that the impact of AI on CE in general shows an “inverted U-shaped” relationship, which is first promoted and then suppressed, and this result still holds after a series of robustness tests. The mechanism test shows that AI affects CE in three main ways: improving energy efficiency, optimizing factor market allocation, and industrial structure. The heterogeneity results show that the “inverted U-shape” relationship of AI on CE is significant in resource cities insignificant in non-resource cities, significant in low-carbon pilot cities, and insignificant in non-low-carbon pilot cities, significant in areas with a high level of industrialization, and insignificant in areas with a low level of industrialization. This study provides valuable insights for the application of AI and the formulation of energy conservation and emission reduction policies.