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Understanding Price Leadership in Fiji’s Energy Market

Author

Listed:
  • Biman Chand Prasad
  • Paresh Kumar Narayan
  • Joel Abraham

    (Monash University, Australia)

Abstract

In this note, we explore price leadership in Fiji’s energy market. Using key energy prices, such as oil, diesel, premix, kerosene and motor spirits, we propose a price leader model. The price discovery model and its theory were proposed by Westerlund, Reese, and Narayan (2017). Using an application of this model to Fiji’s energy price data, we unravel evidence that premix is the market leader with a 54.8% market share followed by the oil price (33.9%). From these results, we draw implications for price regulations and identify the future direction for energy policy.

Suggested Citation

  • Biman Chand Prasad & Paresh Kumar Narayan & Joel Abraham, 2024. "Understanding Price Leadership in Fiji’s Energy Market," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 4(4), pages 1-4.
  • Handle: RePEc:ayb:jrnerl:89
    DOI: 2024/07/09
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    References listed on IDEAS

    as
    1. Paresh Kumar Narayan & Stephan Popp, 2010. "A new unit root test with two structural breaks in level and slope at unknown time," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1425-1438.
    2. Hasbrouck, Joel, 1995. "One Security, Many Markets: Determining the Contributions to Price Discovery," Journal of Finance, American Finance Association, vol. 50(4), pages 1175-1199, September.
    3. Paresh Kumar Narayan & Stephan Popp, 2013. "Size and power properties of structural break unit root tests," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 721-728, February.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

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    JEL classification:

    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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