Assessing the Impact of Green Energy Strategies on Natural Resource Rents in Pakistan

The present research employs the autoregressive distributed lag technique to assess how renewable energy consumption and renewable energy production influence natural resource sustainability within Pakistan during the period 2000–2022. Specifically, the analysis considers renewable energy utilization and its impact on natural resource rents as an indicator of environmental resource exploitation. The empirical findings highlight nuanced relationships: notably, greater renewable energy usage corresponds with diminished natural resource rents, indicating that increased adoption of renewable sources could mitigate pressures on natural resources. Conversely, renewable energy production demonstrates the opposite effect, reflecting that heightened production capacity may amplify economic returns from natural resources through improved extraction efficiencies. This dual nature underscores critical policy implications. Enhanced renewable energy consumption potentially eases ecological stress, preserving natural resources in the long run. Simultaneously, increasing renewable energy production adds economic value by effectively leveraging natural assets sustainably. Consequently, policymakers should adopt strategies that stimulate renewable energy demand through targeted incentives, subsidies, and awareness campaigns, ultimately reducing reliance on traditional, exhaustible energy sources and addressing environmental degradation.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-30
DOI
https://doi.org/10.5281/zenodo.17374928
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing the Impact of Green Energy Strategies on Natural Resource Rents in Pakistan

Zenodo (CERN European Organization for Nuclear Research)
Energy, Environment, Economic Growth
article

Assessing the Impact of Green Energy Strategies on Natural Resource Rents in Pakistan

article en

Abstract

The present research employs the autoregressive distributed lag technique to assess how renewable energy consumption and renewable energy production influence natural resource sustainability within Pakistan during the period 2000–2022. Specifically, the analysis considers renewable energy utilization and its impact on natural resource rents as an indicator of environmental resource exploitation. The empirical findings highlight nuanced relationships: notably, greater renewable energy usage corresponds with diminished natural resource rents, indicating that increased adoption of renewable sources could mitigate pressures on natural resources. Conversely, renewable energy production demonstrates the opposite effect, reflecting that heightened production capacity may amplify economic returns from natural resources through improved extraction efficiencies. This dual nature underscores critical policy implications. Enhanced renewable energy consumption potentially eases ecological stress, preserving natural resources in the long run. Simultaneously, increasing renewable energy production adds economic value by effectively leveraging natural assets sustainably. Consequently, policymakers should adopt strategies that stimulate renewable energy demand through targeted incentives, subsidies, and awareness campaigns, ultimately reducing reliance on traditional, exhaustible energy sources and addressing environmental degradation.

Zenodo (CERN European Organization for Nuclear Research)
Responsible consumption and production
Openalex Percentile: Top 32%
Energy, Environment, Economic Growth
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.