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Causality And Dynamics Of Energy Consumption And Output: Evidence From Non-Oecd Asian Countries

Author

Listed:
  • Ruhul A. Salim

    (Curtin Business School, Curtin University of Technology)

  • Shuddhasattwa Rafiq

    (Curtin Business School, Curtin University of Technology)

  • A. F. M. Kamrul Hassan

    (Curtin Business School, Curtin University of Technology)

Abstract

This article examines the short-run and long-run causal relationship between energy consumption and output in six non-OECD Asian developing countries. Standard time series econometrics is used for this purpose. Based on cointegration and vector error correction modeling, the empirical result shows a bi-directional causality between energy consumption and income in Malaysia, while a unidirectional causality from output to energy consumption in China and Thailand and energy consumption to output in India and Pakistan. Bangladesh remains as an energy neutral economy confirming the fact that it is one of the lowest energy consuming countries in Asia. Both the generalized variance decompositions and the impulse response functions confirm the direction of causality in these countries. These findings have important policy implications for concerned countries. Countries like China and Thailand may contribute to the fight against global warming directly implementing energy conservation measures whereas India and Pakistan may focus on technological developments and mitigation policies. For Malaysia, a balanced combination of alternative policies seems to be appropriate.

Suggested Citation

  • Ruhul A. Salim & Shuddhasattwa Rafiq & A. F. M. Kamrul Hassan, 2008. "Causality And Dynamics Of Energy Consumption And Output: Evidence From Non-Oecd Asian Countries," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 33(2), pages 1-26, December.
  • Handle: RePEc:jed:journl:v:33:y:2008:i:2:p:1-26
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    References listed on IDEAS

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    Cited by:

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    4. Bildirici, Melike E. & Bakirtas, Tahsin, 2014. "The relationship among oil, natural gas and coal consumption and economic growth in BRICTS (Brazil, Russian, India, China, Turkey and South Africa) countries," Energy, Elsevier, vol. 65(C), pages 134-144.
    5. Stephan B. Bruns, Christian Gross and David I. Stern, 2014. "Is There Really Granger Causality Between Energy Use and Output?," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    6. Shahbaz, Muhammad, 2017. "Current Issues in Time-Series Analysis for the Energy-Growth Nexus; Asymmetries and Nonlinearities Case Study: Pakistan," MPRA Paper 82221, University Library of Munich, Germany, revised 19 Oct 2017.
    7. Shihong Zeng & Jiuying Chen, 2016. "Forecasting the Allocation Ratio of Carbon Emission Allowance Currency for 2020 and 2030 in China," Sustainability, MDPI, vol. 8(7), pages 1-28, July.
    8. Ali Raza Cheema & Attiya Yasmin Javid, 2015. "The Relationship between Disaggregate Energy Consumption, Economic Growth and Environment for Asian Developing Economies," PIDE-Working Papers 2015:115, Pakistan Institute of Development Economics.
    9. Pan, Xiongfeng & Uddin, Md. Kamal & Saima, Umme & Jiao, Zhiming & Han, Cuicui, 2019. "How do industrialization and trade openness influence energy intensity? Evidence from a path model in case of Bangladesh," Energy Policy, Elsevier, vol. 133(C).
    10. Zhu, Huiming & Duan, Lijun & Guo, Yawei & Yu, Keming, 2016. "The effects of FDI, economic growth and energy consumption on carbon emissions in ASEAN-5: Evidence from panel quantile regression," Economic Modelling, Elsevier, vol. 58(C), pages 237-248.
    11. Pan, Xiongfeng & Uddin, Md. Kamal & Saima, Umme & Guo, Shucen & Guo, Ranran, 2019. "Regime switching effect of financial development on energy intensity: Evidence from Markov-switching vector error correction model," Energy Policy, Elsevier, vol. 135(C).
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    More about this item

    Keywords

    Energy Conservation; Cointegration; Error Correction Model; Generalized Variance Decompositions; Generalized Impulse Response Functions;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy

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