Factors Affecting Carbon Emissons in the G7 and BRICS Countries: Evidence from Quantile Regression

Zhou, Yefan; Sirisrisakulchai, Jirakom; Liu, Jianxu; Sriboonchitta, Songsak

doi:10.1007/978-3-030-14815-7_34

Cited by 8 publications

(4 citation statements)

References 14 publications

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“…Accordingly, income has influences carbon emissions positively across all estimators at a 10 % significance level. The evidence in this study coincides with that of Zhou et al (2019) for BRICS and G7 countries and Gövdeli (2019) for OECD countries. Specifically, a 1 million dollars increase in income is associated with an increase in emissions between 0.004 to 0.005 million tonnes.…”

Section: Results Of Panel Mg Amg and The Ccemg Estimationssupporting

confidence: 90%

The alternative energy utilization and common regional trade outlook in EU-27: Evidence from common correlated effects

Adedoyin

Alola

Bekun

2021

Renewable and Sustainable Energy Reviews

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Section: Results Of Panel Mg Amg and The Ccemg Estimationssupporting

confidence: 90%

The alternative energy utilization and common regional trade outlook in EU-27: Evidence from common correlated effects

Adedoyin

Alola

Bekun

2021

Renewable and Sustainable Energy Reviews

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“…The quantile regression is the generalization of the middle regression to other quantiles (Lin & Xu, 2018;Chen et al, 2020). The conditional quantile CO2 it by the condition x it can be expressed as (Zhou et al, 2019):…”

Section: Econometric Modelmentioning

confidence: 99%

“…Few researches emphasize on the income inequality variable and empirically examine the effect of income inequality on environmental quality (Torras & Boyce, 1998;Scruggs, 1998;Magnani, 2000;Marsiliani & Renstorm, 2000;Ravallian et al, 2000). However, this issue has been considered a bit more recently, and it is believed that to avoid the miss specification, a criteria of income inequality should be considered in the EKC investigation (Jorgenson et al, 2017;Grunewald et al, 2017;Bae, 2017;Liu et al, 2018;Masud et al, 2018;Liu et al, 2019;Uzar & Eyuboglu, 2019;Ridzuan, 2019;Uddin et al, 2020;Chen et al, 2020;Huang & Duan, 2020).…”

mentioning

confidence: 99%

The Potential Relationship Between Income Inequality and Environmental Quality in Iran: The Panel Quantile Regression Approach

Shabani

Hayati

Pishbahar

et al. 2023

REDR

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This paper addresses the relationship between income inequality and environmental quality in the agriculture sector as the most related sector to the environment. In this context, we used a panel data set for 28 provinces of Iran during 2003-2017 and implemented panel quantile regression. To choose the best econometric specification the Taylor diagram is used. To explore whether the effect on income inequality on CO2 emission is different for rich and poor provinces, we consider the GINI × GDP interaction term in the model. Results confirmed that EKC in the agriculture sector of Iran, and a major and significant effect of energy consumption on CO2 emission. Findings indicated a threshold per capita income ($ 17.60 thousand) from which the effect of income inequality on carbon emissions changes. Based on these results, Marginal Properties to Emit (MPE) is more significant for poor people in low-income provinces than rich ones. Therefore, the government should adopt appropriate policies to increase the income of farmers so that the policy of income distribution, along with social justice, also improves the quality of the environment.

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“…Currently, one of the greatest challenges of the world is the attempt to reach a consensus regarding economic growth, environmental sustentability and population's living conditions (Lira & Cândido, 2008). In this context, studies (Chang, 2015;Camioto et al, 2014;Frugoli et al, 2015;Santana et al, 2014;Verma & Raghubanshi, 2018;Zhou et al, 2019a) were carried out with the objective to check if the growth model considers environmental sustentability and population's life quality as important variables. Other studies (Oliveira et al, 2012;Hervani et al, 2017) had the objective to align sustainability principles with organizations' strategy.…”

Section: Introductionmentioning

confidence: 99%

Efficiency evaluation of sustainable development in BRICS and G7 countries: a Data Envelopment Analysis approach

Camioto

Pulita

2022

Gest. Prod.

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In order to measure the impact of the economic growth over the years, the sustainable development concept works to balance three pillars of sustainability - economic, social and environmental. This paper has the objective to compare emerging countries (BRICS) with the most developed countries (G7) by analysing sustainable development. Data Envelopment Analysis (DEA) was used, thorugh the variant SBM (Slacks Based Measured) model. The inputs were CO2 emission, percentage of unemployed and energy utilization. GDP and life expectancy at birth were used as outputs. The main result was a global average efficency ranking, having the emerging countries in top positions (India, China and Brazil, respectively). In addition, emerging countries have always stood out in the average of the slacks of each analyzed variable. These results are important in terms of being useful for public policies related to sustainable development, especially: (1) to contribute to the discussions related to evaluating the countries, helping to identify those with the best practices with regard to environmental, social and economic aspects in each group; and (2) to guide policy decisions regarding government incentives to promote the development of efficient countries in terms of economic growth and welfare social without harming the environment.

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Factors Affecting Carbon Emissons in the G7 and BRICS Countries: Evidence from Quantile Regression

Cited by 8 publications

References 14 publications

The alternative energy utilization and common regional trade outlook in EU-27: Evidence from common correlated effects

The alternative energy utilization and common regional trade outlook in EU-27: Evidence from common correlated effects

The Potential Relationship Between Income Inequality and Environmental Quality in Iran: The Panel Quantile Regression Approach

Efficiency evaluation of sustainable development in BRICS and G7 countries: a Data Envelopment Analysis approach

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