TY - JOUR
T1 - Artificial intelligence and energy intensity in China's industrial sector
T2 - Effect and transmission channel
AU - Liu, Liang
AU - Yang, Kun
AU - Fujii, Hidemichi
AU - Liu, Jun
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China [Grant No. 71973068]; Humanities and Social Sciences Research Planning Foundation of China's Ministry of Education [Grant No. 19YJA790055]; the Grant-in-Aid for Scientific Research (C) (20K12283) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan; and Scientific Research Foundation of Graduate School of Southeast University, China [Grant No. YBPY1971].
Funding Information:
This work was supported by the National Natural Science Foundation of China [Grant No. 71973068 ]; Humanities and Social Sciences Research Planning Foundation of China’s Ministry of Education [Grant No. 19YJA790055 ]; the Grant-in-Aid for Scientific Research (C) ( 20K12283 ) of the Ministry of Education, Culture, Sports, Science and Technology (MEXT) of Japan ; and Scientific Research Foundation of Graduate School of Southeast University, China [Grant No. YBPY1971 ].
Publisher Copyright:
© 2021 Economic Society of Australia, Queensland
PY - 2021/6
Y1 - 2021/6
N2 - The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected. Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors.
AB - The continued development of artificial intelligence (AI) has changed production methods but may also pose challenges related to energy consumption; in addition, the effectiveness of AI differs across industries. Thus, to develop efficient policies, it is necessary to discuss the effect of AI adoption on energy intensity and to identify industries that are more significantly affected. Using data on industrial robots installed in 16 Chinese industrial subsectors from 2006 to 2016, this paper investigates both the effect of AI on energy intensity and the channel through which this effect is transmitted. The empirical results show, first, that boosting applications of AI can significantly reduce energy intensity by both increasing output value and reducing energy consumption, especially for energy intensities at high quantiles. Second, compared with the impacts in capital-intensive sectors (e.g., basic metals, pharmaceuticals, and cosmetics), the negative impacts of AI on energy intensity in labor-intensive sectors (e.g., textiles and paper) and technology-intensive sectors (e.g., industrial machinery and transportation equipment) are more pronounced. Finally, the impact of AI on energy intensity is primarily achieved through its facilitation of technological progress; this accounts for 78.3% of the total effect. To reduce energy intensity, the Chinese government should effectively promote the development of AI and its use in industry, especially in labor-intensive and technology-intensive sectors.
UR - http://www.scopus.com/inward/record.url?scp=85102634462&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85102634462&partnerID=8YFLogxK
U2 - 10.1016/j.eap.2021.03.002
DO - 10.1016/j.eap.2021.03.002
M3 - Article
AN - SCOPUS:85102634462
SN - 0313-5926
VL - 70
SP - 276
EP - 293
JO - Economic Analysis and Policy
JF - Economic Analysis and Policy
ER -
