Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 Emissions

The environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus regarding the EKC hypothesis among countries and regions of different income groups. This study revisits the EKC hypothesis by employing cross-correlation analysis to explore the income–CO2 emissions relationship across 158 countries and 44 regions from 1990 to 2020. The empirical method utilizes a dynamic cross-correlation coefficient (CCC) approach, allowing for the assessment of lead-lag dynamics between income and CO2 emissions over time. By categorizing nations into the World Bank’s income classifications, we found a heterogeneous EKC pattern highlighting distinct environmental–economic dynamics across different income groups. The findings indicate that high-income countries show a decoupling of economic growth from CO2 emissions; whereas, low-income countries still exhibit a positive correlation between both variables. This underscores the necessity for tailored policy interventions that promote carbon neutrality, while considering each country’s unique development stage. Our research contributes to the ongoing issue of sustainable economic development by providing empirical evidence of the different pathways nations follow in balancing growth with environmental preservation.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-10-20
DOI
https://doi.org/10.3390/su16209089
Citations
18
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
20.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 Emissions

Inzamam Ul Haq, Andreia Dionísio, Paulo Ferreira, Dora Almeida et al.
18 citations
Sustainability
Energy, Environment, Economic Growth
20.33
article

Global Dynamics of Environmental Kuznets Curve: A Cross-Correlation Analysis of Income and CO2 Emissions

Inzamam Ul Haq, Andreia Dionísio, Paulo Ferreira, Dora Almeida, Luísa Carvalho
article en
18 citations

Abstract

The environmental Kuznets curve (EKC) hypothesis posits an inverted U-shaped relationship between economic growth and environmental degradation. However, there is no consensus regarding the EKC hypothesis among countries and regions of different income groups. This study revisits the EKC hypothesis by employing cross-correlation analysis to explore the income–CO2 emissions relationship across 158 countries and 44 regions from 1990 to 2020. The empirical method utilizes a dynamic cross-correlation coefficient (CCC) approach, allowing for the assessment of lead-lag dynamics between income and CO2 emissions over time. By categorizing nations into the World Bank’s income classifications, we found a heterogeneous EKC pattern highlighting distinct environmental–economic dynamics across different income groups. The findings indicate that high-income countries show a decoupling of economic growth from CO2 emissions; whereas, low-income countries still exhibit a positive correlation between both variables. This underscores the necessity for tailored policy interventions that promote carbon neutrality, while considering each country’s unique development stage. Our research contributes to the ongoing issue of sustainable economic development by providing empirical evidence of the different pathways nations follow in balancing growth with environmental preservation.

SustainabilityVol. 16(20)
Liaoning University (CN), University of Évora (PT), Universidade Politécnica de Portalegre (PT)
Fundação para a Ciência e a Tecnologia
Openalex Percentile: Top 1%
Energy, Environment, Economic Growth
20.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.