The energy intensity reduction effect of developing digital economy: Theory and empirical evidence from China
Junbing Huang,
Yajun Wang,
Bingjiang Luan,
Hong Zou and
Jun Wang
Energy Economics, 2023, vol. 128, issue C
Abstract:
This study develops an endogenous growth model to examine the energy intensity reduction effect of digital economy development, and its influencing mechanisms. The study also conducts empirical analysis using pooled ordinary least squares, two-stage least squares and two-step methods to investigate a provincial dataset from 2011 to 2020 in mainland China. The results indicate that digitalisation reduces energy intensity. We examine endogeneity using historical data related to postal operations in the 1980s, the economic and geographical distance from capital cities to Hangzhou and geographical altitude data as instrumental variables for digital economy development. Further analysis demonstrates that technical, efficiency and structural effects are the primary mediators of energy intensity reduction in the digital economy, which is consistent with the theoretical implications. The results remain robust to a series of tests such as replacing estimators and dependent variables, a California effect test, an environmental Kuznets curve hypothesis test, regional heterogeneity tests and a policy disturbance test. The findings ultimately provide evidence that the digital economy presents a viable new solution to reconcile energy and economic management in the context of China's carbon peak and neutrality objectives.
Keywords: Endogenous growth model; Energy intensity; Digital economy; Mediating mechanism (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:128:y:2023:i:c:s0140988323006916
DOI: 10.1016/j.eneco.2023.107193
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