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Clean Energy, Australian Electricity Markets, and Information Transmission

Author

Listed:
  • Sitara Karim
  • Muhammad Abubakr Naeem

    (Department of Business Administration, ILMA University, Pakistan)

Abstract

This study investigates the connectedness between the clean energy and Australian electricity markets from May 2005 to December 2020. Using time-varying parameter vector autoregressions, we find weak connectedness between the clean energy and Australian electricity markets. The weak connectedness of the clean energy markets to the electricity markets illustrates the diversification potential of clean energy for Australian electricity markets. We cite several implications for policymakers, regulatory bodies, investors, and market participants.

Suggested Citation

  • Sitara Karim & Muhammad Abubakr Naeem, 2022. "Clean Energy, Australian Electricity Markets, and Information Transmission," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 3(Early Vie), pages 1-6.
    • Handle: RePEc:ayb:jrnerl:63
    DOI: 2022/06/27
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    References listed on IDEAS

    as
    1. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    2. Richard Green, 2005. "Electricity and Markets," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 21(1), pages 67-87, Spring.
    3. Han, Lin & Kordzakhia, Nino & Trück, Stefan, 2020. "Volatility spillovers in Australian electricity markets," Energy Economics, Elsevier, vol. 90(C).
    4. Antonakakis, Nikolaos & Gabauer, David, 2017. "Refined Measures of Dynamic Connectedness based on TVP-VAR," MPRA Paper 78282, University Library of Munich, Germany.
    5. Giorgio E. Primiceri, 2005. "Time Varying Structural Vector Autoregressions and Monetary Policy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 821-852.
    6. Naeem, Muhammad Abubakr & Karim, Sitara, 2021. "Tail dependence between bitcoin and green financial assets," Economics Letters, Elsevier, vol. 208(C).
    7. Claudiu Albulescu & Aviral Tiwari & Qiang Ji, 2020. "Copula-based local dependence between energy, agriculture and metal commodity markets," Papers 2003.04007, arXiv.org.
    8. Apergis, Nicholas & Gozgor, Giray & Lau, Chi Keung Marco & Wang, Shixuan, 2019. "Decoding the Australian electricity market: New evidence from three-regime hidden semi-Markov model," Energy Economics, Elsevier, vol. 78(C), pages 129-142.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Mbarki, Imen & Khan, Muhammad Arif & Karim, Sitara & Paltrinieri, Andrea & Lucey, Brian M., 2023. "Unveiling commodities-financial markets intersections from a bibliometric perspective," Resources Policy, Elsevier, vol. 83(C).

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    More about this item

    Keywords

    clean energy; Australian energy markets; TVP-VAR;
    All these keywords.

    JEL classification:

    • G00 - Financial Economics - - General - - - General
    • K32 - Law and Economics - - Other Substantive Areas of Law - - - Energy, Environmental, Health, and Safety Law

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