Green finance and energy efficiency: Dynamic study of the spatial externality of institutional support in a digital economy by using hidden Markov chain

The development of a green finance system can be important for the control of energy consumption. This research focuses on the effects of the spatial externality of institutional support from the green finance systems on the energy efficiency of Chinese cities. The Malmquist data envelopment analysi...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Energy economics 2022-12, Vol.116, p.106431, Article 106431
Hauptverfasser: Huo, Da, Zhang, Xiaotao, Meng, Shuang, Wu, Gang, Li, Junhang, Di, Ruoqi
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The development of a green finance system can be important for the control of energy consumption. This research focuses on the effects of the spatial externality of institutional support from the green finance systems on the energy efficiency of Chinese cities. The Malmquist data envelopment analysis (DEA) model is used to analyze the efficiency of energy consumption. The spatial Durbin model is used to analyze the effects of the spatial externality of green finance on energy efficiency. The results show that green finance has an inhibitory impact on energy consumption. The interaction of the policy of green finance and the development of the digital economy also has a negative spatial externality effect on energy consumption in cities. In addition, the control of energy consumption can be further enhanced due to negative spatial autoregressive relationships with cities. The control of energy consumption in cities with large population can be further strengthened through the positive interaction between gross domestic product (GDP) and green finance. Cluster analysis is performed to analyze the characteristics of cities, and the stationary probability in the switch of clusters is forecasted by the Markov chain. Hidden Markov Chain Modeling (HMM) is applied to analyze the probability of city clusters based on hidden connection between institutional support for digital economy and development of green finance with energy consumption. This study can provide policy makers with a systematic comprehension of the impact of spatial externalities on energy efficiency by green finance system in the cross-functional digital economy. •Research Question.•This research focuses on the effects of the spatial externality of institutional support from the green finance systems on the energy efficiency of Chinese cities by acquiring the cross-function of green finance and digital economy.•Method•The energy efficiency of cities at China is measured by DEA model, and spatial effect of green finance and digital economy on energy efficiency is empirically studied. Hidden Markov Chain Modeling is further performed to reveal the hidden probability of city clusters based on hidden connection between institutional support of digital economy and development of green finance and energy consumption.•Key Contribution.•This study led to a new direction to study the effect of green finance on energy efficiency based on interaction of geographic economy and digital economy.
ISSN:0140-9883
1873-6181
DOI:10.1016/j.eneco.2022.106431