Digital transformation and CO2 emissions in Africa
Evidence from dynamic panel and quantile regression analyses
Dados Bibliográficos
| ID | 22234635 |
|---|---|
| Autores | Mosharrof Hosen (0000-0002-9301-4318, Samarkand State University named after Sharof Rashidov), Mohsen Jafarian (0000-0001-9407-9765, UCSI University, autor correspondente), Hatra Voghouei (0000-0002-9610-5346, Keiser University), Taslima Jannat (0000-0002-7427-4923, BRAC University) |
| Ano | 2026 |
| Data de publicação | 2026-06-29 |
| Peer Reviewed | Sim |
| Open Access | Sim |
| Tipo | ARTICLE |
| Periódico | Humanities and Social Sciences Communications (JOURNAL) |
| Identificadores do periódico | ISSN: 2662-9992 • E-ISSN: 2662-9992 |
| Editora | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1057/s41599-026-07978-3 |
| OpenAlex | W7166465250 |
| Idioma | EN |
Digitalization has become a vital driver of agricultural productivity and financial inclusion, both essential for advancing sustainable development. Yet, its environmental implications, particularly its impact on CO2 emissions (SDG 13) in African countries, remain underexplored. This study investigates the interrelationship between digitalization (SDG 9), agriculture, natural resource rents, financial development, urbanization (SDG 11), renewable energy consumption (SDG 7), and CO2 emissions across 29 African Union member states from 2000 to 2020. Using data from the World Bank, we apply the Panel Difference GMM method to address endogeneity and ensure robust causal inference. The findings reveal that digitalization is significantly associated with higher carbon emissions, reflecting the energy demands of digital infrastructure, production, and emerging technologies. Similarly, financial development stimulates economic growth but is associated with higher energy consumption and emissions. Resource rents are also associated with higher emissions, as many African economies rely heavily on extractive industries such as oil and gas. Conversely, agriculture, renewable energy use, and urbanization are associated with lower CO2 emissions, suggesting their potential as sustainability enablers. To enhance methodological rigor, Panel Quantile Regression is employed, highlighting how variable significance shifts across the emission distribution. Overall, the study provides a multisectoral framework for promoting sustainable development, economic resilience, and environmental sustainability in Africa
Linear regression · Panel data · Quantile regression · Regression · Regression analysis · Economic Growth and Development · Energy, Environment, Economic Growth · ICT Impact and Policies
| Velocidade de citação | historical |
|---|---|
| Altamente citado | Não |