Research on the Mechanism of Two-Way Interaction between Digital Economy and Household Energy Transition in China

Yi Zhang; Jiayue Chai; Shuting Miao; Jin Chen

doi:10.62051/ijgem.v3n2.06

Authors

Yi Zhang
Jiayue Chai
Shuting Miao
Jin Chen

DOI:

https://doi.org/10.62051/ijgem.v3n2.06

Keywords:

Digital economy, Green energy efficiency, High quality development, Threshold effect

Abstract

The article selects the inter-provincial panel data from 2015 to 2022, and examines the bidirectional impact of digital economy and China's household energy structure and utilization efficiency and its mechanism of action by using the double-fixed panel model, the mediation and threshold effect model, and the coupled coordination model. The results show that the digital economy has a significant positive impact on household energy structure and utilization efficiency; from the perspective of the impact mechanism, the digital economy can promote the improvement of household energy utilization efficiency and the optimization of structure through the mediating effect of technological innovation; the threshold effect finds that when the digitalization level exceeds 0.661, the digitalization is in the optimal state for driving household energy utilization efficiency in the provincial area; Secondly, this paper focuses on the two-way relationship between the two, and finds that the overall coupling situation is good, and the regional digitalization level and energy efficiency in the "inverted triangle" pattern show a high degree of coupling, and the coupling and coordination phenomenon, which was originally mainly concentrated in the eastern region, has begun to spread to the western region. The purpose of this paper is to promote the acceleration of the national energy transition by playing the positive role of digital economy in promoting the rationalization and advancement of the energy consumption structure, and then reverse the development of China's digital economy, injecting the dual kinetic energy of green and digital into the high-quality development of the economy as a whole.

Downloads

Download data is not yet available.

References

LIU Yaqin, SUN Wei, ZHU Zhishuang. Impact of carbon market on low-carbon transformation of energy structure and its role path [J]. China Environmental Science, 2022, 42(09):4369-4379.

Zou Xuan, Wang Pan. Industrial structure adjustment and energy consumption structure optimization [J]. Soft Science, 2019, 33(05):11-16.

ZHANG Qianqian, LI Baiji. Analysis of the effect of energy structure influencing factors and policy optimization based on path analysis method [J]. Enterprise Economy, 2017, 36(08):11-17.

FAN Decheng, WANG Shaohua, ZHANG Wei. Analysis of influencing factors of primary energy consumption structure under the target of low-carbon economy [J]. Resource Science, 2012, 34(04):696-703.

FAN Ying, YI Bowen. Laws, driving mechanisms and China's path of energy transition [J]. Management World, 2021, 37(08):95-105.

WANG Yong, WANG Ying. Feasibility and optimal path for China to achieve the dual-control target of carbon emission reduction - the perspective of energy structure optimization [J]. China Environmental Science, 2019, 39(10):4444-4455.

HU Junfeng, ZHAO Xiaoli, OU Yangchao. Study on the relationship between energy consumption and economic growth in Beijing [J]. Statistical Research, 2011, 28(03):79-85.

Guochang F, Gang C, Kun Y, et al. Can green tax policy promote China's energy transformation? -A nonlinear analysis from production and consumption perspectives [J]. Energy, 2023, 269.

LI Changsheng, WANG Chongbo, LEI Zhongmin. A study on the fitness of regional energy transition foundation and transition performance in China [J]. Regional Economic Review, 2022, (04):132-144.

Xu Wenli, Sun Lei. Market-incentivized environmental regulation and structural transformation of energy consumption-Empirical evidence from China's carbon emissions trading pilot [J]. Research on Quantitative and Technical Economics, 2023, 40(07):133-155.

LI Rongjie,LI Na,ZHANG Jing et al. Convergence mechanism and influencing factors of regional energy structure decarbonization differences - based on weighted multidimensional vector pinch index[J]. Statistics and Information Forum,2020,35(10):90-99.

Liu Pingkuo, Lu Cunyu. Influencing factors of China's energy transition path selection:Theory testing and empirical analysis [J]. China Soft Science, 2022, (06):51-61.

LI Hai-ship, ZHANG Jing-long. Some insights on the definition of digital economy [J]. Enterprise Economy, 2021, 40(07):13-22+2.

He Weida, Li Menggang. Promoting the transformation and upgrading of coal industry by digitalization [J]. National Governance, 2020, (43):45-48.

Sheng B, Liu YY. A study on the measurement and spatial differentiation characteristics of China's digital economy development index [J]. Nanjing Social Science, 2022, (01):43-54.

WAN Xiaoyu, LUO Yanqing. Measuring the development level of digital economy and its effect on total factor productivity [J]. Reform, 2022, (01):101-118.

Zheng Yaxin. Does digital financial inclusion improve regional innovation output? --An empirical study based on inter-provincial panel data in China [J]. Economic Issues, 2020, (10):53-61.

GUO Feng, SUN Renjin, MENG Siqi. Digital economy, technological innovation and carbon productivity [J]. Research World, 2022, (09):12-19.

ZHANG Sanfeng, WEI Xihai. Does information and communication technology reduce firms' energy consumption--evidence from survey data of Chinese manufacturing firms [J]. China Industrial Economy, 2019(2):155-173.

Beomsoo K, Anitesh B, Rewb W. VirtualField Experiments for a Digital Economy:a new Research Methodology for Exploring an Information Economy [J]. Decision? Support Systems, 2002, 32(3):215-231.

Sadorsky P. Information Communication Technology and? Electricity Consumption in Emerging Economies [J]. Energy policy, 2012, 43:130-136.

Moyer J D, Hughes B B. ICTs:Do They Contribute to Increased Carbon Emissions? [J]. Technological Forecasting & Social Change, 2012(5):919-931 .

Zia A. Measurement of Energy Consumption of ICT Solutions Applied for Improving Energy Efficiency in? Transport Sector [D]. Tampere:Tampere University of Technology, 2016.

LI Shouguo, SONG Baodong. Impact of Internet development on carbon emissions-An empirical study based on panel threshold model [J]. Ecological Economy, 2019(11):33-36.

LI Tao, SHA Weihua. Research on the impact of digital economy on regional total factor energy efficiency--an analysis of the mediating effect based on market trade [J]. Finance and Economics Theory and Practice, 2022, 43(3):120-127.

ZHOU Xiaohui, LIU Yingying, PENG Liuying. Digital economy development and green total factor productivity improvement [J]. Shanghai Economic Research, 2021(12):51-63.

Chen Siyi. Research on the impact of urban-rural income inequality on household energy consumption structure [D]. Southwest University of Finance and Economics, 2021.

LI Yanru, MENG Xue, FENG Xiaoping, HU Feng. Research on the measurement of the development level of digital economy and influencing factors in Chinese provinces [J]. Practice and Understanding of Mathematics, 2023, (10):52-70.

TIAN Jiali, HUANG Wenyan, PENG Jiachao, et al. Transmission mechanism and spatial effect of green finance empowering carbon neutrality [J]. Western Forum, 2022, 32(05):44-62.

CAI Qiang,WANG Xuxu. Impact of green finance on high quality economic development under spatial perspective [J]. Jianghan Forum, 2022, (06):21-28.

Sun Miaoying. Research on the coupling relationship between green finance and high-quality economic development in China [J]. Operation and Management, 2023, (07):177-184.

LIN Chunlei, CUI Linjing. Digital economy development, technological innovation and structural upgrading of distribution industry [J]. Research on Business Economy, 2023(4).

Xia Li. Influence effect of industrial digitalization empowering the development of commerce and circulation industry--Based on the perspective of digital reform [J]. Business and Economic Research, 2022, (11):167-170.

HAN Chunmei, CHENG Yue. Government Funding, Industry-University-Research Coupling Coordination Degree and Regional Innovation Performance - An Empirical Test Based on the Yangtze River Economic Belt [J]. Science and Management, 2024, 44(02):1-9.