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Cointegration and the Demand for Energy in Fiji

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  • Kumar, Saten

Abstract

This paper applies alternative time series techniques such as General to Specific (GETS) and Johansen Maximum Likelihood (JML) to estimate the long run income and price elasticities of demand for energy for Fiji. We also test for the causal relationship between energy consumption, GDP and energy prices using the Granger causality tests. Our results imply that there is a uni-directional causality running from GDP to energy consumption.

Suggested Citation

  • Kumar, Saten, 2008. "Cointegration and the Demand for Energy in Fiji," MPRA Paper 18704, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:18704
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    References listed on IDEAS

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    Cited by:

    1. Kumar, Saten & Manoka, Billy, 2008. "Testing the Stability of Demand for Money in Tonga," MPRA Paper 19300, University Library of Munich, Germany.
    2. Aisha Kolawole & Sola Adesola & Glauco De Vita, 2017. "A Disaggregated Analysis of Energy Demand in Sub-Saharan Africa," International Journal of Energy Economics and Policy, Econjournals, vol. 7(2), pages 224-235.
    3. Rao, B. Bhaskara & Kumar, Saten, 2006. "Structural Breaks and the Demand for Money in Fiji," MPRA Paper 1549, University Library of Munich, Germany.
    4. Santos, Carlos Filipe & Fuinhas, José Alberto & Marques, António Cardoso, 2014. "O nexus energia-crescimento e o nível da auto-suficiência na produção de petróleo: análise com macro painel [Energy-growth nexus and oil self-sufficiency: macro panel analysis]," MPRA Paper 57008, University Library of Munich, Germany.

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    More about this item

    Keywords

    Energy consumption; GDP; income elasticity; energy price elasticity;
    All these keywords.

    JEL classification:

    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • 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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