The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Asymmetric impact of fossil fuel and renewable energy consumption on economic growth: A nonlinear technique
Abstract
ABSTRACT Harnessing energy resources contributes to achieving economic targets and environmental change, as well as fulfilling energy demands via producing clean energy and new technologies. However, the procedures for accomplishing these interlinked objectives and achieving sustainable development need to be addressed empirically. To this end, we examined the nexus between fossil fuel, renewable energy, and economic growth, using a time series data 1980-2017 of Pakistan. By employing a non-linear autoregressive distributed lag and asymmetric causality approaches, this study determines the asymmetric impact of one variable on the others. During the investigation, the results confirmed asymmetric and nonlinear co-integration between pairs of the variables. An asymmetric feedback causality was observed between positive shocks to economic growth and renewable energy consumption. In contrast, the asymmetric causality test showed that positive and negative shocks in fossil fuel and economic growth had a neutral effect, while a symmetric bidirectional hypothesis was observed between fossil fuel consumption and economic growth. Finally, an asymmetrically unidirectional causal nexus was confirmed between foreign direct investment and economic growth. Prospectively, our findings suggest the significance of clean energy along with the installation of new technologies for achieving sustainable economic growth without undermining environmental intactness and ecosystem.
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Distribution of the Estimators for Autoregressive Time Series with a Unit Root
Dickey, D. A., & Fuller, W. A. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10482531 · Cited by 23,211
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
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 a unit root in time series regression
PHILLIPS, P. C. B., & PERRON, P. (1988) · Biometrika · doi:10.1093/biomet/75.2.335 · Cited by 19,155
Distribution of the Estimators for Autoregressive Time Series With a Unit Root
Dickey, D. A., & Fuller, W. A. (1979) · Journal of the American Statistical Association · doi:10.2307/2286348 · Cited by 9,106
The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis
Perron, P. (1989) · Econometrica · doi:10.2307/1913712 · Cited by 7,732
A test for independence based on the correlation dimension
Broock, W. A., Scheinkman, J. A., Dechert, W. D., & LeBaron, B. (1996) · Econometric Reviews · doi:10.1080/07474939608800353 · Cited by 3,506
Error‐correction Mechanism Tests for Cointegration in a Single‐equation Framework
Banerjee, A., Dolado, J., & Mestre, R. (1998) · Journal of Time Series Analysis · doi:10.1111/1467-9892.00091 · Cited by 2,305
ON THE RELATIONSHIP BETWEEN ENERGY AND GNP
Kraft, I., & Kraft, A. (1978) · Cited by 2,183
The effect of renewable energy consumption on economic growth: Evidence from top 38 countries
Bhattacharya, M., Paramati, S. R., Ozturk, I., & Bhattacharya, S. (2016) · Applied Energy · doi:10.1016/j.apenergy.2015.10.104 · Cited by 1,527
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Brine management strategies, technologies, and recovery using adsorption processes
Al-Absi, R. S., Abu-Dieyeh, M., & Al-Ghouti, M. A. (2021) · Environmental Technology & Innovation · doi:10.1016/j.eti.2021.101541 · Cited by 48
Metadata
- Authors
- Baz, K., Cheng, J., Xu, D., Abbas, K., Ali, I., Ali, H., & Fang, C.
- Venue
- Energy
- Publisher
- Elsevier BV
- Published
- 2021-07
- Volume
- 226
- Pages
- 120357
- ISSN
- 0360-5442 (ISSN-L)
- OpenAlex
- W3139323434
- Cited by
- 265
- References
- 55
- FWCI
- 37.62
- Type
- journal article
- Language
- en
- Open access
- closed
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