Araştırma Makalesi
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Yıl 2018, Cilt 14, Sayı 29, 199 - 223, 19.07.2019

Öz

Kaynakça

  • Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle, in B.N. Petrov and F. Csáki, eds, 2nd International Symposium on Information Theory, Akadémia Kiadó, Budapest, 267-281. https://hero.epa.gov/hero/index.cfm/reference/details/reference_id/591
  • Al-Mulali, U., Ozturk, I., & Solarin, S.A. (2016). Investigating the environmental Kuznets curve hypothesis in seven regions: The role of renewable energy, Ecological Indicators, 67, 267-282. https://doi.org/10.1016/j.ecolind.2016.02.059
  • Apergis, N., Jebli, M.B., & Youssef, S.B. (2018). Does Renewable Energy Consumption and Health Expenditures Decrease Carbon Dioxide Emissions? Evidence for sub-Saharan Africa Countries, Renewable Energy, 127, 1011-1016. https://doi.org/10.1016/j.renene.2018.05.043
  • Attiaoui, I., Toumi, H., Ammouri, B., & Gargouri, I. (2017). Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach, Environmental Science and Pollution Research, 24 (14), 13036-13048. https://link.springer.com/article/10.1007%2Fs11356-017-8850-7
  • Chen, P.Y., Chen, S.T., Hsu, C.S., & Chen, C.C. (2016). Modeling the global relationships among economic growth, energy consumption and CO2 emissions, Renewable and Sustainable Energy Reviews, 65, 420-431. https://doi.org/10.1016/j.rser.2016.06.074
  • Dickey, D.A., & Fuller, W.A. (1981). Likelihood ratio statistics for autoregressive time series with unit root, Econometrica, 49 (4), 1057-1072. https://www.jstor.org/stable/1912517?seq=1#page_ scan_tab_contents
  • Dickey, D.A., & Fuller, W.A. (1988). Testing for a Unit Root in Time Series Regression, Biometrika Trust, 75 (2), 335-346. http://finpko.faculty.ku.edu/myssi/FIN938/Phillips%20%26%20Perron_ Biometrika_1988_Unit%20Root%20Test.pdf
  • Dogan, E., & Aslan, A. (2017). Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: Evidence from panel models robust to heterogeneity and cross-sectional dependence, Renewable and Sustainable Energy Reviews, 77, 239-245. https://doi.org/10.1016/j.rser.2017.03.111
  • Dogan, E., & Ozturk, I. (2017). The influence of renewable and non-renewable energy consumption and real income on CO2 emissions in the USA: evidence from structural break tests, Environmental Science and Pollution Research, 24 (11), 10846-10854. https://link.springer. com/article/10.1007/s11356-017-8786-y
  • Dogan, E., & Seker, F. (2016). The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries, Renewable and Sustainable Energy Reviews, 60, 1074-1085. https://doi.org/10.1016/j. rser.2016.02.006
  • Engle, R.F., & Granger, C.W.J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing, Econometrica, 55 (2), 251-276. http://www.ntuzov.com/Nik_Site/ Niks_files/Research/papers/stat_arb/EG_1987.pdf
  • Granger, C.W.J. (1969). Investigating Causal Relations by Econometrics Models and CrossSpectral Methods, Econometrica, 37 (3), 424-438. http://tyigit.bilkent.edu.tr/metrics2/read/ Investigating%20%20Causal%20Relations%20by%20Econometric%20Models%20and%20 Cross-Spectral%20Methods.pdf
  • Granger, C.W.J. (1988). Some recent development in a concept of causality, Journal of Econometrics, 39 (1-2), 199-211. https://doi.org/10.1016/0304-4076(88)90045-0
  • Hannan, E.J., & Quinn, B.G. (1979). The Determination of the Order of an Autoregression, Journal of the Royal Statistical Society. Series B, 41 (2), 190-195. http://www.jstor.org/stable/2985032
  • Inglesi-Lotz, R., & Dogan, E. (2018). The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub-Saharan Africa’s Big 10 electricity generators, Renewable Energy, 123, 36-43. https://doi.org/10.1016/j.renene.2018.02.041
  • Johansen, S. (1988). Statistical analysis of cointegration vectors, Journal of Economic Dynamics and Control, 12 (2-3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3
  • Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models, 59 (6), 1551-1580. http://www.jstor.org/stable/2938278
  • Lütkepohl, H. (1991). Introduction to Multiple Time Series Analysis, Springer Berlin Heidelberg New York. http://www.afriheritage.org/TTT/2%20New%20Introduction%20to%20 Multiple%20Time%20Series%20Analysis.pdf
  • Mbarek, M.B., Saidi, K., & Rahman, M.M. (2018). Renewable and non-renewable energy consumption, environmental degradation and economic growth in Tunisia, Quality & Quantity, 52 (3), 1105-1119. https://link.springer.com/article/10.1007%2Fs11135-017-0506-7
  • Menyah, K., & Wolde-Rufael, Y. (2010). CO2 emissions, nuclear energy, renewable energy and economic growth in the US, Energy Policy, 38 (6), 2911-2915. https://doi.org/10.1016/j. enpol.2010.01.024
  • Paramati, S.R., Sinha, A., & Dogan, E. (2017). The significance of renewable energy use for economic output and environmental protection: evidence from the Next 11 developing economies, Environmental Science and Pollution Research, 24 (15), 13546-13560. https://link. springer.com/article/10.1007/s11356-017-8985-6
  • Schwarz, G. (1978). Estimating the dimension of a model, The annals of Statistics, 6 (2), 461-464. http://qwone.com/~jason/trg/papers/schwarz-dimension-78.pdf
  • Shahbaz, M., Solarin, S.A., Hammoudeh, S., & Shahzad, S.J.H. (2017). Bound testing approach to analyzing the environment Kuznets curve hypothesis with structural breaks: The role of biomass energy consumption in the United States, Energy Economics, 68, 548-565. https://doi. org/10.1016/j.eneco.2017.10.004
  • Solarin, S.A., Al-Mulali, U., & Ozturk, I. (2017). Validating the environmental Kuznets curve hypothesis in India and China: The role of hydroelectricity consumption, Renewable and Sustainable Energy Reviews, 80, 1578-1587. https://doi.org/10.1016/j.rser.2017.07.028
  • Sulaiman, J., Azman, A., & Saboori, B. (2013). The Potential of Renewable Energy: Using the Environmental Kuznets Curve Model, American Journal of Environmental Sciences, 9 (2), 103112. https://thescipub.com/pdf/10.3844/ajessp.2013.103.112
  • United Nations for Climate Change (UNFCCC), (September 3rd, 2015), « Intended nationally determined contribution INDC-Algeria».
  • Zoundi, Z. (2017). CO2 emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach, Renewable and Sustainable Energy Reviews, 72, 1067-1075. https://linkinghub.elsevier.com/retrieve/pii/S1364032116306682 http://siteresources.worldbank.org/EXTMETAP/Resources/COED-AlgeriaCP.pdf https://www.iea.org/ https://www.worldbank.org/

Examining the Connection amongst Renewable Energy, Economic Growth and Carbon Dioxide Emissions in Algeria

Yıl 2018, Cilt 14, Sayı 29, 199 - 223, 19.07.2019

Öz

In this paper, we shall study the relationship between renewable energy, economic growth (GDP), carbon dioxide emissions and with control variable that are estimated into realized volatility and to verify if the EKC hypothesis is accepted or not. This study is focussed on the Algerian situation during the periods of 1995-2016 and we employed the VECM procedure and Granger causality to estimate the short and long-run coefficients. We found with VECM that an increase in carbon dioxide emissions, fossil energy consumption and production will raise the level of economic growth, while an increase in GDP, fossil energy consumption and production will upsurge the level of carbon dioxide emissions, but an increase in renewable energy consumption will reduce both GDP and carbon dioxide emissions. We concluded in the short-term that there’s bidirectional causality between carbon dioxide emissions and GDP and there is unidirectional causality running from renewable energy consumption to carbon dioxide emissions. 

Kaynakça

  • Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle, in B.N. Petrov and F. Csáki, eds, 2nd International Symposium on Information Theory, Akadémia Kiadó, Budapest, 267-281. https://hero.epa.gov/hero/index.cfm/reference/details/reference_id/591
  • Al-Mulali, U., Ozturk, I., & Solarin, S.A. (2016). Investigating the environmental Kuznets curve hypothesis in seven regions: The role of renewable energy, Ecological Indicators, 67, 267-282. https://doi.org/10.1016/j.ecolind.2016.02.059
  • Apergis, N., Jebli, M.B., & Youssef, S.B. (2018). Does Renewable Energy Consumption and Health Expenditures Decrease Carbon Dioxide Emissions? Evidence for sub-Saharan Africa Countries, Renewable Energy, 127, 1011-1016. https://doi.org/10.1016/j.renene.2018.05.043
  • Attiaoui, I., Toumi, H., Ammouri, B., & Gargouri, I. (2017). Causality links among renewable energy consumption, CO2 emissions, and economic growth in Africa: evidence from a panel ARDL-PMG approach, Environmental Science and Pollution Research, 24 (14), 13036-13048. https://link.springer.com/article/10.1007%2Fs11356-017-8850-7
  • Chen, P.Y., Chen, S.T., Hsu, C.S., & Chen, C.C. (2016). Modeling the global relationships among economic growth, energy consumption and CO2 emissions, Renewable and Sustainable Energy Reviews, 65, 420-431. https://doi.org/10.1016/j.rser.2016.06.074
  • Dickey, D.A., & Fuller, W.A. (1981). Likelihood ratio statistics for autoregressive time series with unit root, Econometrica, 49 (4), 1057-1072. https://www.jstor.org/stable/1912517?seq=1#page_ scan_tab_contents
  • Dickey, D.A., & Fuller, W.A. (1988). Testing for a Unit Root in Time Series Regression, Biometrika Trust, 75 (2), 335-346. http://finpko.faculty.ku.edu/myssi/FIN938/Phillips%20%26%20Perron_ Biometrika_1988_Unit%20Root%20Test.pdf
  • Dogan, E., & Aslan, A. (2017). Exploring the relationship among CO2 emissions, real GDP, energy consumption and tourism in the EU and candidate countries: Evidence from panel models robust to heterogeneity and cross-sectional dependence, Renewable and Sustainable Energy Reviews, 77, 239-245. https://doi.org/10.1016/j.rser.2017.03.111
  • Dogan, E., & Ozturk, I. (2017). The influence of renewable and non-renewable energy consumption and real income on CO2 emissions in the USA: evidence from structural break tests, Environmental Science and Pollution Research, 24 (11), 10846-10854. https://link.springer. com/article/10.1007/s11356-017-8786-y
  • Dogan, E., & Seker, F. (2016). The influence of real output, renewable and non-renewable energy, trade and financial development on carbon emissions in the top renewable energy countries, Renewable and Sustainable Energy Reviews, 60, 1074-1085. https://doi.org/10.1016/j. rser.2016.02.006
  • Engle, R.F., & Granger, C.W.J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing, Econometrica, 55 (2), 251-276. http://www.ntuzov.com/Nik_Site/ Niks_files/Research/papers/stat_arb/EG_1987.pdf
  • Granger, C.W.J. (1969). Investigating Causal Relations by Econometrics Models and CrossSpectral Methods, Econometrica, 37 (3), 424-438. http://tyigit.bilkent.edu.tr/metrics2/read/ Investigating%20%20Causal%20Relations%20by%20Econometric%20Models%20and%20 Cross-Spectral%20Methods.pdf
  • Granger, C.W.J. (1988). Some recent development in a concept of causality, Journal of Econometrics, 39 (1-2), 199-211. https://doi.org/10.1016/0304-4076(88)90045-0
  • Hannan, E.J., & Quinn, B.G. (1979). The Determination of the Order of an Autoregression, Journal of the Royal Statistical Society. Series B, 41 (2), 190-195. http://www.jstor.org/stable/2985032
  • Inglesi-Lotz, R., & Dogan, E. (2018). The role of renewable versus non-renewable energy to the level of CO2 emissions a panel analysis of sub-Saharan Africa’s Big 10 electricity generators, Renewable Energy, 123, 36-43. https://doi.org/10.1016/j.renene.2018.02.041
  • Johansen, S. (1988). Statistical analysis of cointegration vectors, Journal of Economic Dynamics and Control, 12 (2-3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3
  • Johansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models, 59 (6), 1551-1580. http://www.jstor.org/stable/2938278
  • Lütkepohl, H. (1991). Introduction to Multiple Time Series Analysis, Springer Berlin Heidelberg New York. http://www.afriheritage.org/TTT/2%20New%20Introduction%20to%20 Multiple%20Time%20Series%20Analysis.pdf
  • Mbarek, M.B., Saidi, K., & Rahman, M.M. (2018). Renewable and non-renewable energy consumption, environmental degradation and economic growth in Tunisia, Quality & Quantity, 52 (3), 1105-1119. https://link.springer.com/article/10.1007%2Fs11135-017-0506-7
  • Menyah, K., & Wolde-Rufael, Y. (2010). CO2 emissions, nuclear energy, renewable energy and economic growth in the US, Energy Policy, 38 (6), 2911-2915. https://doi.org/10.1016/j. enpol.2010.01.024
  • Paramati, S.R., Sinha, A., & Dogan, E. (2017). The significance of renewable energy use for economic output and environmental protection: evidence from the Next 11 developing economies, Environmental Science and Pollution Research, 24 (15), 13546-13560. https://link. springer.com/article/10.1007/s11356-017-8985-6
  • Schwarz, G. (1978). Estimating the dimension of a model, The annals of Statistics, 6 (2), 461-464. http://qwone.com/~jason/trg/papers/schwarz-dimension-78.pdf
  • Shahbaz, M., Solarin, S.A., Hammoudeh, S., & Shahzad, S.J.H. (2017). Bound testing approach to analyzing the environment Kuznets curve hypothesis with structural breaks: The role of biomass energy consumption in the United States, Energy Economics, 68, 548-565. https://doi. org/10.1016/j.eneco.2017.10.004
  • Solarin, S.A., Al-Mulali, U., & Ozturk, I. (2017). Validating the environmental Kuznets curve hypothesis in India and China: The role of hydroelectricity consumption, Renewable and Sustainable Energy Reviews, 80, 1578-1587. https://doi.org/10.1016/j.rser.2017.07.028
  • Sulaiman, J., Azman, A., & Saboori, B. (2013). The Potential of Renewable Energy: Using the Environmental Kuznets Curve Model, American Journal of Environmental Sciences, 9 (2), 103112. https://thescipub.com/pdf/10.3844/ajessp.2013.103.112
  • United Nations for Climate Change (UNFCCC), (September 3rd, 2015), « Intended nationally determined contribution INDC-Algeria».
  • Zoundi, Z. (2017). CO2 emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach, Renewable and Sustainable Energy Reviews, 72, 1067-1075. https://linkinghub.elsevier.com/retrieve/pii/S1364032116306682 http://siteresources.worldbank.org/EXTMETAP/Resources/COED-AlgeriaCP.pdf https://www.iea.org/ https://www.worldbank.org/

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Salah Eddine SARİ HASSOUN> (Sorumlu Yazar)
University of Tlemcen
Algeria


Mohammed MÉKİDİCHE Bu kişi benim
University of Tlemcen
Algeria


Mohammed Seghir GUELLİL Bu kişi benim
University of Mascara
Algeria

Yayımlanma Tarihi 19 Temmuz 2019
Başvuru Tarihi 14 Kasım 2018
Kabul Tarihi 15 Ocak 2019
Yayınlandığı Sayı Yıl 2018, Cilt 14, Sayı 29

Kaynak Göster

APA Sari Hassoun, S. E. , Mékidiche, M. & Guellil, M. S. (2019). Examining the Connection amongst Renewable Energy, Economic Growth and Carbon Dioxide Emissions in Algeria . Ekoist: Journal of Econometrics and Statistics , 14 (29) , 199-223 . Retrieved from https://dergipark.org.tr/tr/pub/ekoist/issue/47194/594216