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Cited by 248

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Energy intensity, carbon emissions, renewable energy, and economic growth nexus: New insights from Romania

Open access
Emir, Fırat, Bekun, Festus Victor·2019·Energy & Environment

Abstract

This study empirically examines the relationship between energy intensity, carbon emissions, renewable energy consumption, and economic growth for the case of Romania given the conflicting evidences in the literature between 1990 and 2014 on a quarterly basis. To this end, our study employs an autoregressive distributive lag (ARDL) model for cointegration, while direction of causality was achieved via the Toda–Yamamoto model. Empirical findings reveal cointegration among the variables under consideration. The causality results show feedback causality between energy intensity and economic growth while uni-directional causality is seen running from renewable energy consumption to economic growth. Thus, this study affirms the energy-led growth hypothesis. Therefore, our study corroborates with the current success story of Romania attaining her energy targets within two decades. However, there is need to sustain this milestone by further diversification of her energy portfolio into other cleaner energy sources.

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Metadata

Authors
Emir, F., & Bekun, F. V.
Venue
Energy & Environment
Published
2018-09-18
Volume
30
Issue
3
Pages
427-443
ISSN
  • 0958-305X (ISSN-L)
  • 2048-4070
OpenAlex
W2890387891
Cited by
248
References
2
FWCI
46.27
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Energy intensity, carbon emissions, renewable energy, and economic growth nexus: New insights from Romania. https://app.cochat.ai/papers/10.1177/0958305x18793108
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Emir, F., & Bekun, F. V. (2019). Energy intensity, carbon emissions, renewable energy, and economic growth nexus: New insights from Romania. Energy & Environment. https://doi.org/10.1177/0958305x18793108

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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.