The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Renewable energy consumption and economic growth nexus: Evidence from a threshold model
Open accessAbstract
The existing literature on renewable energy consumption and economic growth nexus produces mixed results as the effect of renewable energy consumption on economic growth can be either positive, negative or not significant. This paper examines the causal link between renewable energy use and economic growth by employing a threshold model using a 103-country sample in the 1995 to 2015 period. We find that the relationship between renewable energy consumption and economic growth depends on the amount of renewable energy used. Our results demonstrate that the effect of renewable energy consumption on economic growth is positive and significant if and only if developing countries or non-OECD countries surpass a certain threshold of renewable energy consumption. However, if developing countries use renewable energy below a given threshold level, the effect of renewable energy consumption on economic growth is negative. However, we also find that renewable energy consumption has no significant effect on economic growth in developed countries and a positive and significant effect on economic growth in OECD countries. The findings of this paper suggest that for developing countries to realize positive economic growth from their investment to renewable energy, they need to surpass a certain threshold of renewable energy consumption.
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Cites
Bounds testing approaches to the analysis of level relationships
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001) · Journal of Applied Econometrics · doi:10.1002/jae.616 · Cited by 20,385
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
A simple panel unit root test in the presence of cross‐section dependence
Pesaran, M. H. (2007) · Journal of Applied Econometrics · doi:10.1002/jae.951 · Cited by 12,787
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
Unit root tests for panel data
Choi, I. (2001) · Journal of International Money and Finance · doi:10.1016/s0261-5606(00)00048-6 · Cited by 4,113
Testing Weak Cross-Sectional Dependence in Large Panels
Pesaran, M. H. (2015) · Econometric Reviews · doi:10.1080/07474938.2014.956623 · Cited by 2,950
Error-Correction–Based Cointegration Tests for Panel Data
Persyn, D., & Westerlund, J. (2008) · The Stata Journal: Promoting communications on statistics and Stata · doi:10.1177/1536867x0800800205 · Cited by 770
Cited by
Jaiswal, K. K., Chowdhury, C. R., Yadav, D., Verma, R., Dutta, S., Jaiswal, K. S., SangmeshB, & Karuppasamy, K. S. K. (2022) · Energy Nexus · doi:10.1016/j.nexus.2022.100118 · Cited by 770
Energy structure, digital economy, and carbon emissions: evidence from China
Li, Y., Yang, X., Ran, Q., Wu, H., Irfan, M., & Ahmad, M. (2021) · Environmental Science and Pollution Research · doi:10.1007/s11356-021-15304-4 · Cited by 593
Ivanovski, K., Hailemariam, A., & Smyth, R. (2021) · Journal of Cleaner Production · doi:10.1016/j.jclepro.2020.124956 · Cited by 303
Renewable energy and CO2 emissions: New evidence with the panel threshold model
Chen, C., Pinar, M., & Stengos, T. (2022) · Renewable Energy · doi:10.1016/j.renene.2022.05.095 · Cited by 268
Self-citationRenewable Energy Consumption and Economic Growth Nexus—A Systematic Literature Review
Bhuiyan, M. A., Zhang, Q., Khare, V., Mikhaylov, A., Pinter, G., & Huang, X. (2022) · Frontiers in Environmental Science · doi:10.3389/fenvs.2022.878394 · Cited by 265
Metadata
- Authors
- Chen, C., Pinar, M., & Stengos, T.
- Venue
- Energy Policy
- Publisher
- Elsevier BV
- Published
- 2020-04
- Volume
- 139
- Pages
- 111295
- ISSN
- 0301-4215 (ISSN-L)
- OpenAlex
- W3003923904
- Cited by
- 467
- References
- 7
- FWCI
- 53.93
- Type
- journal article
- Language
- en
- Open access
- green
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