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

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Embargoed until: 2021-06-27
Author(s)
Alsaedi, Yasir Hamad
Tularam, Gurudeo Anand
Year published
2020
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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 ...
View more >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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View more >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
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.
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This publication has been entered into Griffith Research Online as an Advanced Online Version
Subject
Mathematical Sciences
Physical Sciences
Information and Computing Sciences