Role of energy natural resource productivity and environmental taxation in controlling environmental pollution: Policy‐based analysis for regions

The present study explores the impact of energy natural resource productivity and environmental tax on environmental sustainability in six major CO 2 ‐emitting economies: the Euro Area, China, South Korea, Japan, the United Kingdom and the United States, from 1997 to 2019. This analysis aims to reveal novel findings and implications for different energy natural resource productivity types and environmental regulations. We employed data regarding leading national and regional CO 2 emitters from 1997 to 2020 to conduct an empirical analysis using the panel non‐linear auto‐regressive distributed lag (NARDL) and panel quantile ARDL (QARDL) methods. The results show that energy natural resource productivity and environmental tax are crucial components in reducing CO 2 emissions by controlling for innovation technology and renewable energy consumption. The main findings demonstrate that the impact is stronger in the presence of increased energy natural resource productivity and vice versa. These findings have novel implications for sustainable development and carbon neutrality.

Authors

Institutions

Publication Details

Journal
Geological Journal
Published
2024-08-26
DOI
https://doi.org/10.1002/gj.5047
Citations
2
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
2.26

Funders

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

Role of energy natural resource productivity and environmental taxation in controlling environmental pollution: Policy‐based analysis for regions

Xin Zhao, Abdelmohsen A. Nassani, Yuepeng Zhai, Yuriy Bilan et al.
2 citations
Geological Journal
Energy, Environment, Economic Growth
2.26
article

Role of energy natural resource productivity and environmental taxation in controlling environmental pollution: Policy‐based analysis for regions

Xin Zhao, Abdelmohsen A. Nassani, Yuepeng Zhai, Yuriy Bilan, Kamel Si Mohammed, Xiaowei Ma
article en
2 citations

Abstract

The present study explores the impact of energy natural resource productivity and environmental tax on environmental sustainability in six major CO 2 ‐emitting economies: the Euro Area, China, South Korea, Japan, the United Kingdom and the United States, from 1997 to 2019. This analysis aims to reveal novel findings and implications for different energy natural resource productivity types and environmental regulations. We employed data regarding leading national and regional CO 2 emitters from 1997 to 2020 to conduct an empirical analysis using the panel non‐linear auto‐regressive distributed lag (NARDL) and panel quantile ARDL (QARDL) methods. The results show that energy natural resource productivity and environmental tax are crucial components in reducing CO 2 emissions by controlling for innovation technology and renewable energy consumption. The main findings demonstrate that the impact is stronger in the presence of increased energy natural resource productivity and vice versa. These findings have novel implications for sustainable development and carbon neutrality.

Geological JournalVol. 59(11)
Rzeszów University of Technology (PL), Anhui University of Finance and Economics (CN), King Saud University (SA), Université de ain Témouchent (DZ), University of Business and Technology (SA), Széchenyi István University (HU), College of Business Administration (LV)
King Saud University
Responsible consumption and production
Openalex Percentile: Top 8%
Energy, Environment, Economic Growth
2.26
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.