The Impact of Economic Growth, Energy Consumption and Trade Openness on Carbon Emissions: An Empirical Analysis in China

Liu, Jianxu; He, Jingliang; Dong, Changrui; Sriboonchitta, Songsak

doi:10.1007/978-3-030-14815-7_20

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…Since the 1990s, the positive and negative effects of trade openness on the environment have been the subject of the Environmental Kuznets Curve (EKC), Pollution Paradise, and Race to the Bottom hypotheses (Fan et al, 2019). Some of the studies revealed that the increase in foreign trade increased CO 2 emissions (Ansari et al, 2019;Liu et al, 2019;Nurgazina et al, 2021). Some other studies revealed that foreign trade has no effect on CO 2 emissions or it changes depending on the export rate and time (Mutascu, 2018;Salahuddin et al, 2018;Lv and Xu, 2019;Iqbal et al, 2021).…”

Section: Dae and Comentioning

confidence: 99%

The spatial analysis of green economy indicators of OECD countries

Çay Atalay,

Akan

2023

Front. Environ. Sci.

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The present study aims to examine the effect of the geographical location relationship between economic growth and environmental pollution. For this purpose, the spatial relationship between the variable CO2 emission and the variables energy consumption (ENC), real GDP per capita (GDP), urbanization rate (URB), and trade liberalization (DAE) was investigated by using the data of 37 OECD countries for the period of 1990–2015. The geographical location relationship was determined by using LISA (Local Indicators of Spatial Association) analysis, which is one of the spatial autocorrelation analysis methods. Spatial distribution maps were prepared. Considering the years determined according to Moran I index results, a gradually increasing positive autocorrelation was found for CO2 and ENC variables and a low increasing positive correlation for DAE and GDP variables. For the variable URB, a low increasing positive autocorrelation was found for the year 1990 and a high increasing positive autocorrelation for the year 2015. Then, using the LISA clustering maps, the relationships between the countries were clustered as low, high, and non-related. As a result of this study, given the spatial analysis results, the effect of energy consumption on the carbon emission was found to be positive in general. Increases in trade liberalization increased carbon emissions in some countries and decreased it in some others. On the other hand, increases in the urbanization rate decreased carbon emissions in some countries and had a positive effect in some others. The trade openness index was found to have a generally negative effect on the carbon emission. Within the scope of this study, Spatial Regression Analysis was conducted separately for the years 1990 and 2015. In this analysis, CO2 is the dependent variable, whereas ENC, GDP, URB, and DAE are independent variables. Given the results of spatial regression analysis, it was found that ENC, GDP, and DAE variables have a positive relationship with the CO2 variable. It was determined that there was no significant relationship between URB and CO2. Considering the results achieved, it could be possible to observe the increasing and decreasing effects of variables, which were examined here, on the CO2 emissions.

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Section: Dae and Comentioning

confidence: 99%

The spatial analysis of green economy indicators of OECD countries

Çay Atalay,

Akan

2023

Front. Environ. Sci.

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“…Recent studies have a growing concern to explore the ways to reduce environmental pollution and obtain economic and environmental sustainability. As discussed earlier in the introduction section, various recent studies have accounted for different driving factors to control environmental degradation in China, for instance, RE resource consumption (Khattak et al, 2020;Godil et al, 2021), technological innovations (Shahbaz et al, 2020), green innovation (Hu et al, 2022), industrialization (Dong K. et al, 2018;Wang and Su, 2019), globalization (Ling et al, 2021), economic growth (Liu et al, 2019), trade openness (Liu et al, 2021a), environmental regulations (Li et al, 2022), environmental taxes (Hsu et al, 2021), tourism (Razzaq et al, 2021a), FDI inflows (Shahbaz et al, 2020), and financial development (Godil et al, 2020). It has been observed that the existing literature does not provide any single study which has addressed the role of green energy efficiency on environmental degradation in China.…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic Role of Green Energy Efficiency and Climate Technologies in Realizing Environmental Sustainability: Fresh Insights From China

Liu

Qiu

Zhu

2022

Front. Environ. Sci.

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Amid rising industrialization and economic progress, China has shown exponential growth in energy and fossil fuel consumption; therefore, it faces great global concern and widespread criticism for energy and fuel conservation to reduce fuel-related emissions. In addition, the recent spread of COVID-19 instigates the impact of environmental pollution, exaggerates the virus intensity, and lowers people’s immunity due to poor air quality. Therefore, this study explored the role of green energy efficiency and climate technologies in achieving carbon neutrality in China using an advanced quantile autoregressive distributed lag (QARDL) framework. The results indicated that green energy efficiency and climate technologies significantly reduce environmental pollution across all quantiles in the long run. In contrast, urbanization enhances environmental degradation at lower and higher emissions quantiles, while trade only promotes environmental pollution at lower quantiles. These findings suggested using alternative energy sources and carbon-reducing technologies to ensure a sustainable environment.

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