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Multi-scale Causality between Energy Consumption and GNP in Emerging Markets: Evidence from Turkey

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  • Cifter, Atilla
  • Ozun, Alper

Abstract

Tests results for causality between energy consumption and economic growth do not have a consensus in the financial economics literature. Empirical evidence varies on the economies examined and methodology employed. This paper proposes a wavelet analysis as a semi- parametric model for detecting multi-scale causality between electricity consumption and growth in emerging economies. Using wavelet analysis we find that in the short run there is feedback relationship between GNP and energy consumption, while in the long run GNP leads to energy consumption. Wavelet correlation between GNP and energy consumption is maximum at 3rd time-scale(5-8 years) and this shows that GNP effects electricity consumption maximally around 5-8 years later in the long-run. We also find that the magnitude of the wavelet correlation changes based on time-scales for GNP and energy consumption and thus indicate that GNP and energy consumption are fundamentally different in the long run.

Suggested Citation

  • Cifter, Atilla & Ozun, Alper, 2007. "Multi-scale Causality between Energy Consumption and GNP in Emerging Markets: Evidence from Turkey," MPRA Paper 2483, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:2483
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    References listed on IDEAS

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    Cited by:

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    3. Saldivia, Mauricio & Kristjanpoller, Werner & Olson, Josephine E., 2020. "Energy consumption and GDP revisited: A new panel data approach with wavelet decomposition," Applied Energy, Elsevier, vol. 272(C).
    4. Bamidele P. Abalaba & Matthew Abiodun Dada, 2013. "Energy Consumption and Economic Growth Nexus: New Empirical Evidence from Nigeria," International Journal of Energy Economics and Policy, Econjournals, vol. 3(4), pages 412-423.
    5. Junsheng Ha & Pei-Pei Tan & Kim-Leng Goh, 2018. "Linear and nonlinear causal relationship between energy consumption and economic growth in China: New evidence based on wavelet analysis," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-21, May.
    6. Yu, Lean & Li, Jingjing & Tang, Ling & Wang, Shuai, 2015. "Linear and nonlinear Granger causality investigation between carbon market and crude oil market: A multi-scale approach," Energy Economics, Elsevier, vol. 51(C), pages 300-311.
    7. Haiyun Xu, 2016. "Economic policy uncertainty and housing returns in Germany: Evidence from a bootstrap rolling window," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 34(2), pages 309-332.
    8. Raza Muhammad khan & Sohail Farooq & Muhammad Akram Gilal, 2020. "Electricity Consumption and Economic Growth: A Time-Series Study on Pakistan," Global Economics Review, Humanity Only, vol. 5(1), pages 24-37, March.
    9. Yılmaz Bayar & Hasan Alp Özel, 2014. "Electricity Consumption and Economic Growth in Emerging Economies," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 4(2), pages 1-15, April.
    10. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    11. Inchauspe, Julian & Li, Jun & Park, Jason, 2020. "Seasonal patterns of global oil consumption: Implications for long term energy policy," Journal of Policy Modeling, Elsevier, vol. 42(3), pages 536-556.
    12. Kristjanpoller R., Werner & Sierra C., Alejandro & Scavia D., Javier, 2018. "Dynamic co-movements between energy consumption and economic growth. A panel data and wavelet perspective," Energy Economics, Elsevier, vol. 72(C), pages 640-649.
    13. Upadhyay, Shashankaditya & Banerjee, Anirban & Panigrahi, Prasanta K., 2020. "Causal evolution of global crisis in financial networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    14. Mirza, Faisal Mehmood & Kanwal, Afra, 2017. "Energy consumption, carbon emissions and economic growth in Pakistan: Dynamic causality analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1233-1240.
    15. Erdost Torun & Afife Duygu Ayhan Akdeniz & Erhan Demireli & Simon Grima, 2022. "Long-Term US Economic Growth and the Carbon Dioxide Emissions Nexus: A Wavelet-Based Approach," Sustainability, MDPI, vol. 14(17), pages 1-16, August.
    16. Neeraj, & Panigrahi, Prasanta K., 2017. "Causality and correlations between BSE and NYSE indexes: A Janus faced relationship," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 481(C), pages 284-313.
    17. Tonn, Victor Lux & Li, H.C. & McCarthy, Joseph, 2010. "Wavelet domain correlation between the futures prices of natural gas and oil," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 408-414, November.
    18. Wei, Jiangqiao & Ma, Zhe & Wang, Anjian & Li, Pengyuan & Sun, Xiaoyan & Yuan, Xiaojing & Hao, Hongchang & Jia, Hongxiang, 2022. "Multiscale nonlinear Granger causality and time-varying effect analysis of the relationship between iron ore futures and spot prices," Resources Policy, Elsevier, vol. 77(C).
    19. Jammazi, Rania & Aloui, Chaker, 2015. "Environment degradation, economic growth and energy consumption nexus: A wavelet-windowed cross correlation approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 110-125.

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    More about this item

    Keywords

    Economic Growth; Energy Consumption; Employment; Wavelets; Causality;
    All these keywords.

    JEL classification:

    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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