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Estimation and Forecasts for the Share of Renewable Energy Consumption in Final Energy Consumption by 2020 in the European Union

Author

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  • Anca Mehedintu

    (Department of Statistics and Economic Informatics, University of Craiova, A.I. Cuza 13, Craiova 200585, Romania)

  • Mihaela Sterpu

    (Department of Mathematics, University of Craiova, A.I. Cuza 13, Craiova 200585, Romania)

  • Georgeta Soava

    (Department of Statistics and Economic Informatics, University of Craiova, A.I. Cuza 13, Craiova 200585, Romania)

Abstract

European Union Directive 2009/28/EC established that the share of renewable energy in the final energy consumption should reach a target of 20% by 2020 in European Union (EU) countries. This study analyses the tendency of this share using data for EU 28, taken from the Eurostat database for the period 1995–2016. First, after a brief statistical and economic analysis of the three macroeconomic indicators at EU level, five regression models (polynomial, ARIMA) were used to estimate the evolution of the share of renewable energy consumption into the final energy consumption, all of them showing an increasing trend for this indicator. The positive impact of the EU Directive in increasing this share was proved by means of a perturbed regression model. Forecasts of this share for the 2020 horizon were obtained, all showing that the EU target is yet to be reached. Secondly, four groups of EU-countries were considered, according to the final energy consumption. Empirical estimations of renewable energy share into the final energy consumption showed increasing trend for all groups, while providing forecasts quite different from the EU ones. Also, economic interpretations of the results are performed.

Suggested Citation

  • Anca Mehedintu & Mihaela Sterpu & Georgeta Soava, 2018. "Estimation and Forecasts for the Share of Renewable Energy Consumption in Final Energy Consumption by 2020 in the European Union," Sustainability, MDPI, vol. 10(5), pages 1-22, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1515-:d:145597
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    as
    1. Wang, Yuanyuan & Wang, Jianzhou & Zhao, Ge & Dong, Yao, 2012. "Application of residual modification approach in seasonal ARIMA for electricity demand forecasting: A case study of China," Energy Policy, Elsevier, vol. 48(C), pages 284-294.
    2. Suat Ozturk & Feride Ozturk, 2018. "Forecasting Energy Consumption of Turkey by Arima Model," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 8(2), pages 52-60.
    3. Ardakani, F.J. & Ardehali, M.M., 2014. "Long-term electrical energy consumption forecasting for developing and developed economies based on different optimized models and historical data types," Energy, Elsevier, vol. 65(C), pages 452-461.
    4. Salahuddin, Mohammad & Gow, Jeff & Ozturk, Ilhan, 2015. "Is the long-run relationship between economic growth, electricity consumption, carbon dioxide emissions and financial development in Gulf Cooperation Council Countries robust?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 317-326.
    5. Lei Jin & Keran Duan & Xu Tang, 2018. "What Is the Relationship between Technological Innovation and Energy Consumption? Empirical Analysis Based on Provincial Panel Data from China," Sustainability, MDPI, vol. 10(1), pages 1-13, January.
    6. Alper, Aslan & Oguz, Ocal, 2016. "The role of renewable energy consumption in economic growth: Evidence from asymmetric causality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 953-959.
    7. Ediger, Volkan S. & Akar, Sertac, 2007. "ARIMA forecasting of primary energy demand by fuel in Turkey," Energy Policy, Elsevier, vol. 35(3), pages 1701-1708, March.
    8. Salim, Ruhul A. & Shafiei, Sahar, 2014. "Urbanization and renewable and non-renewable energy consumption in OECD countries: An empirical analysis," Economic Modelling, Elsevier, vol. 38(C), pages 581-591.
    9. Anthony N. Rezitis & Shaikh Mostak Ahammad, 2015. "The Relationship between Energy Consumption and Economic Growth in South and Southeast Asian Countries: A Panel Vector Autoregression Approach and Causality Analysis," International Journal of Energy Economics and Policy, Econjournals, vol. 5(3), pages 704-715.
    10. Yabo Zhao & Shaojian Wang, 2015. "The Relationship between Urbanization, Economic Growth and Energy Consumption in China: An Econometric Perspective Analysis," Sustainability, MDPI, vol. 7(5), pages 1-19, May.
    11. Tsai, Sang-Bing & Xue, Youzhi & Zhang, Jianyu & Chen, Quan & Liu, Yubin & Zhou, Jie & Dong, Weiwei, 2017. "Models for forecasting growth trends in renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1169-1178.
    12. Yuan, Chaoqing & Liu, Sifeng & Fang, Zhigeng, 2016. "Comparison of China's primary energy consumption forecasting by using ARIMA (the autoregressive integrated moving average) model and GM(1,1) model," Energy, Elsevier, vol. 100(C), pages 384-390.
    13. Sen, Parag & Roy, Mousumi & Pal, Parimal, 2016. "Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization," Energy, Elsevier, vol. 116(P1), pages 1031-1038.
    14. Erdogdu, Erkan, 2007. "Electricity demand analysis using cointegration and ARIMA modelling: A case study of Turkey," Energy Policy, Elsevier, vol. 35(2), pages 1129-1146, February.
    15. Gunter, Ulrich & Önder, Irem, 2015. "Forecasting international city tourism demand for Paris: Accuracy of uni- and multivariate models employing monthly data," Tourism Management, Elsevier, vol. 46(C), pages 123-135.
    16. Sadorsky, Perry, 2009. "Renewable energy consumption and income in emerging economies," Energy Policy, Elsevier, vol. 37(10), pages 4021-4028, October.
    17. Rafindadi, Abdulkadir Abdulrashid & Ozturk, Ilhan, 2016. "Effects of financial development, economic growth and trade on electricity consumption: Evidence from post-Fukushima Japan," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1073-1084.
    18. Hsu, David, 2015. "Identifying key variables and interactions in statistical models of building energy consumption using regularization," Energy, Elsevier, vol. 83(C), pages 144-155.
    19. Fumo, Nelson & Rafe Biswas, M.A., 2015. "Regression analysis for prediction of residential energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 332-343.
    20. Liddle, Brantley & Lung, Sidney, 2015. "Revisiting energy consumption and GDP causality: Importance of a priori hypothesis testing, disaggregated data, and heterogeneous panels," Applied Energy, Elsevier, vol. 142(C), pages 44-55.
    21. Liu, Yaobin, 2009. "Exploring the relationship between urbanization and energy consumption in China using ARDL (autoregressive distributed lag) and FDM (factor decomposition model)," Energy, Elsevier, vol. 34(11), pages 1846-1854.
    22. Dincer Dedeoglu & Ali Piskin, 2014. "A dynamic panel study of energy consumption–economic growth nexus: evidence from the former Soviet Union countries," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 38(1), pages 75-106, March.
    23. Pappas, S.Sp. & Ekonomou, L. & Karamousantas, D.Ch. & Chatzarakis, G.E. & Katsikas, S.K. & Liatsis, P., 2008. "Electricity demand loads modeling using AutoRegressive Moving Average (ARMA) models," Energy, Elsevier, vol. 33(9), pages 1353-1360.
    24. Shuyu Li & Rongrong Li, 2017. "Comparison of Forecasting Energy Consumption in Shandong, China Using the ARIMA Model, GM Model, and ARIMA-GM Model," Sustainability, MDPI, vol. 9(7), pages 1-19, July.
    25. Zahra Fotourehchi, 2017. "Renewable Energy Consumption and Economic Growth: A Case Study for Developing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 7(2), pages 61-64.
    26. Bhattacharya, Mita & Paramati, Sudharshan Reddy & Ozturk, Ilhan & Bhattacharya, Sankar, 2016. "The effect of renewable energy consumption on economic growth: Evidence from top 38 countries," Applied Energy, Elsevier, vol. 162(C), pages 733-741.
    27. Daniel Ştefan Armeanu & Georgeta Vintilă & Ştefan Cristian Gherghina, 2017. "Does Renewable Energy Drive Sustainable Economic Growth? Multivariate Panel Data Evidence for EU-28 Countries," Energies, MDPI, vol. 10(3), pages 1-21, March.
    28. Suat Ozturk & Feride Ozturk, 2018. "Forecasting Energy Consumption of Turkey by Arima Model," Journal of Asian Scientific Research, Asian Economic and Social Society, vol. 8(2), pages 52-60, February.
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