Renewable Energy Credits Transforming Market Dynamics

This research uses advanced statistical methods to examine climate change mitigation policies’ economic and environmental impacts. The primary objective is to assess the effectiveness of carbon pricing, renewable energy subsidies, emission trading schemes, and regulatory standards in reducing CO2 emissions, fostering economic growth, and promoting employment. A mixed-methods approach was employed, combining regression analysis, cost–benefit analysis (CBA), and computable general equilibrium (CGE) models. Data were collected from national and global databases, and sensitivity analyses were conducted to ensure the robustness of the findings. Key findings revealed a statistically significant reduction in CO2 emissions by 0.45% for each unit increase in carbon pricing (p < 0.01). Renewable energy subsidies were positively correlated with a 3.5% increase in employment in the green sector (p < 0.05). Emission trading schemes were projected to increase GDP by 1.2% over a decade (p < 0.05). However, chi-square tests indicated that carbon pricing disproportionately affects low-income households (p < 0.05), highlighting the need for compensatory policies. The study concluded that a balanced policy mix, tailored to national contexts, can optimise economic and environmental outcomes while addressing social equity concerns. Error margins in GDP projections remained below ±0.3%, confirming the models’ reliability.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-10-03
DOI
https://doi.org/10.3390/su16198602
Citations
15
Primary Topic
Energy and Environment Impacts
Type
article
Field-Weighted Citation Impact
1.99

Funders

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

Renewable Energy Credits Transforming Market Dynamics

Francis T. Omigbodun, Bankole I. Oladapo, Mattew A. Olawumi
15 citations
Sustainability
Energy and Environment Impacts
1.99
article

Renewable Energy Credits Transforming Market Dynamics

Francis T. Omigbodun, Bankole I. Oladapo, Mattew A. Olawumi
article en
15 citations

Abstract

This research uses advanced statistical methods to examine climate change mitigation policies’ economic and environmental impacts. The primary objective is to assess the effectiveness of carbon pricing, renewable energy subsidies, emission trading schemes, and regulatory standards in reducing CO2 emissions, fostering economic growth, and promoting employment. A mixed-methods approach was employed, combining regression analysis, cost–benefit analysis (CBA), and computable general equilibrium (CGE) models. Data were collected from national and global databases, and sensitivity analyses were conducted to ensure the robustness of the findings. Key findings revealed a statistically significant reduction in CO2 emissions by 0.45% for each unit increase in carbon pricing (p < 0.01). Renewable energy subsidies were positively correlated with a 3.5% increase in employment in the green sector (p < 0.05). Emission trading schemes were projected to increase GDP by 1.2% over a decade (p < 0.05). However, chi-square tests indicated that carbon pricing disproportionately affects low-income households (p < 0.05), highlighting the need for compensatory policies. The study concluded that a balanced policy mix, tailored to national contexts, can optimise economic and environmental outcomes while addressing social equity concerns. Error margins in GDP projections remained below ±0.3%, confirming the models’ reliability.

SustainabilityVol. 16(19)
Loughborough University (GB), University of Dundee (GB), De Montfort University (GB)
University of Dundee
Openalex Percentile: Top 14%
Energy and Environment Impacts
1.99
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.