Renewable and nonrenewable energy consumption, trade and CO₂ emissions in high emitter countries: does the income level matter?

Abstract

This study analyzes the effects of increased income and renewable energy on environmental quality, which has been ignored in the existing literature. An important contribution of this study is to analyze the role of renewable and nonrenewable energy in relation to the rising level of carbon emissions in the leading emitting countries. This research further examines the heterogeneous impacts of rising income levels and EKC investigation for CO₂ emissions. The Kao cointegration, generalized method of moments (GMM), random effects, fixed effect (FE) regression models, and panel causality techniques are employed for panel data estimations. The empirical outcomes mention that an increase in income moderates the ratio of consumption of renewable energy to CO₂ emissions. Increased income contributes more to the energy mix, which contributes to environmental pollution, through nonrenewable energy. This research reports policy-relevant critical masses beyond which an increase in income negatively affects the link between renewable energy and CO₂ emissions.

Keywords:

• renewable energy
• nonrenewable energy
• CO₂ emissions
• trade
• leading emitter countries
• panel data

JEL classification:

• C33
• Q42
• Q55

Acknowledgements

We are grateful to anonymous referees for valuable comments and helpful suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 https://www.eia.gov/totalenergy/data/browser/

2 It is worth mentioning that, at an earlier stage, we chose the top 10 emission countries, but later due to unavailability of data we eliminated two countries (Iran and Saudi Arabia).

3 The Kao cointegration examines the asymptotic null distribution of residual-based cointegration test in panel data by applying Dickey–Fuller (DF) and augmented Dickey–Fuller (ADF) tests.

Additional information

Funding

This study was financially supported by the Major Program of the National Social Science Fund of China (Grant no. 16ZDA088). This work was further supported by the National Natural Science Foundation of China (Grant Numbers 71503001, 71974001); Provincial Natural Science Research Project in Anhui Province (Grant Number KJ2019A0649).