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  • The relationship between electricity consumption, peak load and GDP in Saudi Arabia: A VAR analysis

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    AlsaediPUB233767.pdf (1.156Mb)
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    Author(s)
    Alsaedi, Yasir Hamad
    Tularam, Gurudeo Anand
    Griffith University Author(s)
    Tularam, Gurudeo A.
    Alsaedi, Yasir H.
    Year published
    2020
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    Abstract
    International Association for Mathematics and Computers in Simulation (IMACS) This study aims to investigate the dynamic relationship between electricity consumption (EC), peak load (PL) and gross domestic product (GDP) in the Kingdom of Saudi Arabia by employing a vector auto-regression (VAR) analysis using time series data from 1990–2015. We also employ Granger causality testing, the impulse response function and forecast error variance decompositions. The forecasts for the total EC, PL and GDP using the VAR model with a ten-year horizon show positive growth rates of around 7.21%, 6.87% and 14.14%, respectively. We find ...
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    International Association for Mathematics and Computers in Simulation (IMACS) This study aims to investigate the dynamic relationship between electricity consumption (EC), peak load (PL) and gross domestic product (GDP) in the Kingdom of Saudi Arabia by employing a vector auto-regression (VAR) analysis using time series data from 1990–2015. We also employ Granger causality testing, the impulse response function and forecast error variance decompositions. The forecasts for the total EC, PL and GDP using the VAR model with a ten-year horizon show positive growth rates of around 7.21%, 6.87% and 14.14%, respectively. We find bidirectional Granger causal relationships between the PL and the EC and GDP. The results also show that 29% of the PL is explained by its own innovative shocks. The contributions of the EC and GDP to the PL are 10% and 34%, respectively. This study demonstrates PL to be a significant variable that relates to growth.
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    Journal Title
    Mathematics and Computers in Simulation
    DOI
    https://doi.org/10.1016/j.matcom.2019.06.012
    Copyright Statement
    © 2019 IMACS/Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Note
    This publication has been entered into Griffith Research Online as an Advanced Online Version
    Subject
    Mathematical sciences
    Physical sciences
    Publication URI
    http://hdl.handle.net/10072/386724
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    • Journal articles

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