scholarly journals Can Green Finance Optimize Energy Structure: A Spatial Econometric Analysis based on China's Traditional and Renewable Energy Consumption

2021 ◽  
Author(s):  
Hui Wang ◽  
Lili Jiang ◽  
Hongjun Duan ◽  
Yifeng Wang ◽  
Yichen Jiang
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Spillover Effect ◽  
Energy Structure ◽  
Renewable Energy Consumption ◽  
Spatial Spillover ◽  
Consumption Structure ◽  
Green Finance ◽  
The Impact ◽  
Spatial Spillover Effect

Abstract This paper studies the impact of the development of green finance on China’s energy consumption structure. In terms of the construction of the green finance index (GFI), this paper selects 17 basic indexes from the three aspects of economy, finance, and environment, uses the improved entropy weight method to construct the GFI, and studies the spatial spillover effect of the GFI of China's provinces. This paper further studies the impact of green finance on traditional and renewable energy consumption. We first uses panel regression to determine that the development of green finance has a positive effect on the slowdown of traditional energy consumption and acceleration of renewable energy consumption, and then further studies the spatial characteristics of green finance development on energy consumption by using spatial Durbin model. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. Therefore, the government should support the green finance, reduce traditional energy consumption and increase renewable energy consumption.

scholarly journals The Impact of Green Finance Development on China’s Energy Structure Optimization

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Hui Wang ◽  
Lili Jiang ◽  
Hongjun Duan ◽  
Yifeng Wang ◽  
Yichen Jiang ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy Consumption ◽  
Local Development ◽  
Clean Energy ◽  
Green Energy ◽  
Energy Structure ◽  
Renewable Energy Consumption ◽  
Consumption Structure ◽  
Green Finance ◽  
The Impact

This paper studies the impact of the development of green finance on China’s energy consumption structure. 17 basic indexes and the improved entropy weight method are used to construct the green finance index (GFI). Multiple regression, panel regression, and spatial regression are used to study the impact of green finance on China’s traditional energy and renewable energy consumption. The results show that there is a positive spatial spillover effect in the development of green finance among provinces in China. The development of green finance contributes to the conversion of traditional to renewable energy consumption. The effect of green finance on the transformation of energy consumption structure is mainly reflected in the direct effect. The green finance in each province not only helps the local development of green energy but also plays a good role in the production and utilization of clean energy consumption in surrounding provinces. Therefore, the government should support the green finance, reduce traditional energy consumption, and increase renewable energy consumption.

scholarly journals The Relationship between Economic Growth and Pollution in Some New European Union Member States: A Dynamic Panel ARDL Approach

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2363
Author(s):  
Mihaela Simionescu ◽  
Carmen Beatrice Păuna ◽  
Mihaela-Daniela Vornicescu Niculescu
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Ghg Emissions ◽  
Kuznets Curve ◽  
Renewable Energy Consumption ◽  
Panel Ardl ◽  
Domestic Credit ◽  
The Impact ◽  
The Relationship

Considering the necessity of achieving economic development by keeping the quality of the environment, the aim of this paper is to study the impact of economic growth on GHG emissions in a sample of Central and Eastern European (CEE) countries (V4 countries, Bulgaria and Romania) in the period of 1996–2019. In the context of dynamic ARDL panel and environmental Kuznets curve (EKC), the relationship between GHG and GDP is N-shaped. A U-shaped relationship was obtained in the renewable Kuznets curve (RKC). Energy consumption, domestic credit to the private sector, and labor productivity contribute to pollution, while renewable energy consumption reduces the GHG emissions. However, more efforts are required for promoting renewable energy in the analyzed countries.

scholarly journals Do High Oil Prices Obstruct the Transition to Renewable Energy Consumption?

2020 ◽  
Vol 12 (11) ◽  
pp. 4689 ◽  
Author(s):  
Shahriyar Mukhtarov ◽  
Jeyhun I. Mikayilov ◽  
Sugra Humbatova ◽  
Vugar Muradov
Keyword(s):  
Economic Growth ◽  
Renewable Energy ◽  
Energy Consumption ◽  
Negative Impact ◽  
Oil Prices ◽  
Oil Price ◽  
Renewable Energy Consumption ◽  
Long Run ◽  
Carbon Dioxide Co2 ◽  
The Impact

The study analyzes the impact of economic growth, carbon dioxide (CO2) emissions, and oil price on renewable energy consumption in Azerbaijan for the data spanning from 1992 to 2015, utilizing structural time series modeling approach. Estimation results reveal that there is a long-run positive and statistically significant effect of economic growth on renewable energy consumption and a negative impact of oil price in the case of Azerbaijan, for the studied period. The negative impact of oil price on renewable energy consumption can be seen as an indication of comfort brought by the environment of higher oil prices, which delays the transition from conventional energy sources to renewable energy consumption for the studied country case. Also, we find that the effect of CO2 on renewable energy consumption is negative but statistically insignificant. The results of this article might be beneficial for policymakers and support the current literature for further research for oil-rich developing countries.

scholarly journals Spatial-Temporal Effects of PM2.5 on Health Burden: Evidence from China

2019 ◽  
Vol 16 (23) ◽  
pp. 4695 ◽  
Author(s):  
Zeng ◽  
Du ◽  
Zhang
Keyword(s):  
Direct Effect ◽  
Spatial Clustering ◽  
Spillover Effect ◽  
Spatial Spillover ◽  
Regulatory Policies ◽  
Health Burden ◽  
Lag Effect ◽  
Pm2.5 Exposure ◽  
The Impact ◽  
Spatial Spillover Effect

By collecting the panel data of 29 regions in China from 2008 to 2017, this study used the spatial Durbin model (SDM) to explore the spatial effect of PM2.5 exposure on the health burden of residents. The most obvious findings to emerge from this study are that: health burden and PM2.5 exposure are not randomly distributed over different regions in China, but have obvious spatial correlation and spatial clustering characteristics. The maximum PM2.5 concentrations have a significant positive effect on outpatient expense and outpatient visits of residents in the current period, and the impact of PM2.5 pollution has a significant temporal lag effect on residents’ health burden. PM2.5 exposure has a spatial spillover effect on the health burden of residents, and the PM2.5 concentrations in the surrounding regions or geographically close regions have a positive influence on the health burden in the particular region. The impact of PM2.5 exposure is divided into the direct effect and the indirect effect (the spatial spillover effect), and the spatial spillover effect is greater than that of the direct effect. Therefore, we conclude that PM2.5 exposure has a spatial spillover effect and temporal lag effect on the health burden of residents, and strict regulatory policies are needed to mitigate the health burden caused by air pollution.

Does China’s transportation infrastructure have an impact on employment in the service sector?

Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2737-2753
Author(s):  
Hui Wang ◽  
Meiqing Zhang
Keyword(s):  
Large Scale ◽  
Service Industry ◽  
Spillover Effect ◽  
Transportation Infrastructure ◽  
Content Type ◽  
Inland Waterways ◽  
Spatial Spillover ◽  
Positive Effects ◽  
The Impact ◽  
Spatial Spillover Effect

Purpose The large-scale construction of China’s transportation infrastructure has driven the flow of elements between regions, which has provided convenient conditions for the accumulation of advantageous resources. Design/methodology/approach Based on the panel data of 31 provinces in China in the past 2003-2017 years, this paper applies the spatial econometric model and partial differential method and empirically analyzes the spatial spillover effect of transportation infrastructure on employment in the service industry under four spatial weighting matrices. Findings The results show that for every 1 per cent increase in the level of transportation infrastructure, the employment density of the service industry in the region can be increased by 0.1274 per cent. It is worth noting that roads promote the employment of the service industry more than railways and inland waterways. However, inland waterways have not shown positive effects. The results on spatial spillover of transportation infrastructure indicate that railway has obvious promotion effect on the employment level of service industry in the surrounding area, while the highway has hindered the effect. The spatial spillover effect of inland waterway is not obvious. Originality/value The value of this paper is to consider the impact of China’s transportation infrastructure on employment in a particular industry, especially in the service industry. The research will help to provide empirical evidence for policymakers. The government needs to invest and build transportation infrastructure based on the stage and development potential of the employment development of the regional service industry.

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