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Does electricity consumption panel Granger cause GDP? A new global evidence

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  • Narayan, Paresh Kumar
  • Narayan, Seema
  • Popp, Stephan

Abstract

The goal of this paper is to undertake a panel data investigation of long-run Granger causality between electricity consumption and real GDP for seven panels, which together consist of 93 countries. We use a new panel causality test and find that in the long-run both electricity consumption and real GDP have a bidirectional Granger causality relationship except for the Middle East where causality runs only from GDP to electricity consumption. Finally, for the G6 panel the estimates reveal a negative sign effect, implying that increasing electricity consumption in the six most industrialised nations will reduce GDP.

Suggested Citation

  • Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan, 2010. "Does electricity consumption panel Granger cause GDP? A new global evidence," Applied Energy, Elsevier, vol. 87(10), pages 3294-3298, October.
    • Handle: RePEc:eee:appene:v:87:y:2010:i:10:p:3294-3298
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    References listed on IDEAS

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    Cited by:

    1. Smyth, Russell & Narayan, Paresh Kumar, 2015. "Applied econometrics and implications for energy economics research," Energy Economics, Elsevier, vol. 50(C), pages 351-358.
    2. repec:ebl:ecbull:eb-17-00457 is not listed on IDEAS
    3. Karanfil, Fatih & Li, Yuanjing, 2015. "Electricity consumption and economic growth: Exploring panel-specific differences," Energy Policy, Elsevier, vol. 82(C), pages 264-277.
    4. Bashiri Behmiri, Niaz & Pires Manso, José R., 2012. "Crude oil conservation policy hypothesis in OECD (organisation for economic cooperation and development) countries: A multivariate panel Granger causality test," Energy, Elsevier, vol. 43(1), pages 253-260.
    5. Apergis, Nicholas & Polemis, Michael, 2018. "Electricity supply shocks and economic growth across the US states: evidence from a time-varying Bayesian panel VAR model, aggregate and disaggregate energy sources," MPRA Paper 84954, University Library of Munich, Germany.
    6. Brantley Liddle, 2013. "The Energy, Economic Growth, Urbanization Nexus Across Development: Evidence from Heterogeneous Panel Estimates Robust to Cross-Sectional Dependence," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2).
    7. repec:eee:enepol:v:108:y:2017:i:c:p:256-270 is not listed on IDEAS
    8. Al-Mulali, Usama & Ozturk, Ilhan, 2014. "Are energy conservation policies effective without harming economic growth in the Gulf Cooperation Council countries?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 639-650.
    9. Shahbaz, Muhammad & Sarwar, Suleman & Chen, Wei & Malik, Muhammad Nasir, 2017. "Dynamics of electricity consumption, oil price and economic growth: Global perspective," Energy Policy, Elsevier, vol. 108(C), pages 256-270.
    10. Ou, Xunmin & Xiaoyu, Yan & Zhang, Xiliang, 2011. "Life-cycle energy consumption and greenhouse gas emissions for electricity generation and supply in China," Applied Energy, Elsevier, vol. 88(1), pages 289-297, January.
    11. 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.
    12. Evan Lau & Xiao-Hui Chye & Chee-Keong Choong, 2011. "Energy-Growth Causality: Asian Countries Revisited," International Journal of Energy Economics and Policy, Econjournals, vol. 1(4), pages 140-149.
    13. Phiri, Andrew & Nyoni, Botha, 2014. "The electricity-growth nexus in South Africa: Evidence from asymmetric co-integration and co-feature analysis," MPRA Paper 56145, University Library of Munich, Germany.
    14. Dedeoğlu, Dinçer & Kaya, Hüseyin, 2013. "Energy use, exports, imports and GDP: New evidence from the OECD countries," Energy Policy, Elsevier, vol. 57(C), pages 469-476.
    15. Kankal, Murat & AkpInar, Adem & Kömürcü, Murat Ihsan & Özsahin, Talat Sükrü, 2011. "Modeling and forecasting of Turkey's energy consumption using socio-economic and demographic variables," Applied Energy, Elsevier, vol. 88(5), pages 1927-1939, May.
    16. Liddle, Brantley & Lung, Sidney, 2013. "The long-run causal relationship between transport energy consumption and GDP: Evidence from heterogeneous panel methods robust to cross-sectional dependence," Economics Letters, Elsevier, vol. 121(3), pages 524-527.
    17. Al-mulali, Usama & Fereidouni, Hassan Gholipour & Lee, Janice Ym & Sab, Che Normee Binti Che, 2013. "Examining the bi-directional long run relationship between renewable energy consumption and GDP growth," Renewable and Sustainable Energy Reviews, Elsevier, vol. 22(C), pages 209-222.
    18. Baek, Chulwoo & Jung, Euy-Young & Lee, Jeong-Dong, 2014. "Effects of regulation and economic environment on the electricity industry׳s competitiveness: A study based on OECD countries," Energy Policy, Elsevier, vol. 72(C), pages 120-128.
    19. Al-mulali, Usama & Tang, Chor Foon & Ozturk, Ilhan, 2015. "Estimating the Environment Kuznets Curve hypothesis: Evidence from Latin America and the Caribbean countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 918-924.
    20. Narayan, Paresh Kumar & Popp, Stephan, 2012. "The energy consumption-real GDP nexus revisited: Empirical evidence from 93 countries," Economic Modelling, Elsevier, vol. 29(2), pages 303-308.
    21. Paresh Narayan & Russell Smyth, 2014. "Applied Econometrics and a Decade of Energy Economics Research," Monash Economics Working Papers 21-14, Monash University, Department of Economics.
    22. Iwata, Hiroki & Okada, Keisuke & Samreth, Sovannroeun, 2011. "A note on the environmental Kuznets curve for CO2: A pooled mean group approach," Applied Energy, Elsevier, vol. 88(5), pages 1986-1996, May.
    23. Sharma, Susan Sunila, 2011. "Determinants of carbon dioxide emissions: Empirical evidence from 69 countries," Applied Energy, Elsevier, vol. 88(1), pages 376-382, January.
    24. repec:eee:rensus:v:76:y:2017:i:c:p:353-368 is not listed on IDEAS

    More about this item

    Keywords

    C22 Real GDP Electricity consumption Panel Granger causality;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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