The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
What is better for mitigating carbon emissions – Renewable energy or nuclear energy? A panel data analysis
Abstract
This paper investigates the determinants of carbon emissions based on energy consumption, analyzing the data of 30 countries using nuclear energy for the period 1990–2014. Renewable energy and nuclear energy consumption are adopted as determinants, and real coal price and real GDP are used as additive variables. The panel cointegration analysis and Granger causality tests are conducted to investigating the relationship among the variables. First, the panel cointegration test results suggest that long-run equilibrium relationship exists among carbon emissions, renewable energy consumption, and nuclear energy consumption. The results of the long-run cointegrating vector and Granger causality tests indicate that nuclear energy does not contribute to carbon reduction unlike renewable energy. Thus, the development and expansion of renewable, not nuclear, energy are essential to prevent global warming. Though there is a concern that rising energy prices caused by the expansion of renewable energy may impact the economy negatively, our empirical results also imply that renewable energy consumption will promote economic growth. In other words, our evidence shows that using and expanding renewable energy is both economically and ecologically beneficial.
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Cites
Co-integration and error correction: representation, estimation and testing
Engle, R. F., & Granger, C. W. J. (1987) · Econometrica · doi:10.2307/1913236 · Cited by 32,007
Testing for unit roots in heterogeneous panels
Im, K. S., Pesaran, M. H., & Shin, Y. (2003) · Journal of Econometrics · doi:10.1016/s0304-4076(03)00092-7 · Cited by 15,435
Critical Values for Cointegration Tests in Heterogeneous Panels with Multiple Regressors
Pedroni, P. (1999) · Oxford Bulletin of Economics and Statistics · doi:10.1111/1468-0084.61.s1.14 · Cited by 6,726
Cited by
Kirikkaleli, D., Güngör, H., & Adebayo, T. S. (2022) · Business Strategy and the Environment · doi:10.1002/bse.2945 · Cited by 369
Zhang, C., Khan, I., Dagar, V., Saeed, A., & Zafar, M. W. (2022) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2022.121570 · Cited by 340
Zafar, M. W., Zaidi, S. A. H., Sinha, A., Gedikli, A., & Hou, F. (2019) · Resources Policy · doi:10.1016/j.resourpol.2019.05.003 · Cited by 265
Zheng, J., & Wang, X. (2021) · Energy Policy · doi:10.1016/j.enpol.2020.112041 · Cited by 122
Metadata
- Authors
- Jin, T., & Kim, J.
- Venue
- Renewable and Sustainable Energy Reviews
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 91
- Pages
- 464-471
- ISSN
- 1364-0321 (ISSN-L)
- OpenAlex
- W2805901807
- Cited by
- 321
- References
- 3
- FWCI
- 28.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jin, T., & Kim, J. (2018). What is better for mitigating carbon emissions – Renewable energy or nuclear energy? A panel data analysis. Renewable and Sustainable Energy Reviews. https://doi.org/10.1016/j.rser.2018.04.022
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.