Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach

This study investigates the use of a non-linear autoregressive exogenous neural network (NARX) model to investigate the nexus between energy usability, economic indicators, and carbon dioxide (CO<sub>2</sub>) emissions in four Association of South East Asian Nations (ASEAN), namely Malay...

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Main Authors: Siti Indati Mustapa, Freida Ozavize Ayodele, Bamidele Victor Ayodele, Norsyahida Mohammad
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Processes
Subjects:
Online Access:https://www.mdpi.com/2227-9717/8/12/1529
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spelling doaj-90493813127742d48d2622f4cf33e7b02020-11-27T08:00:47ZengMDPI AGProcesses2227-97172020-11-0181529152910.3390/pr8121529Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling ApproachSiti Indati Mustapa0Freida Ozavize Ayodele1Bamidele Victor Ayodele2Norsyahida Mohammad3Institute of Energy Policy and Research, Universiti Tenaga Nasional, Jalan Ikram-Uniten, Kajang 43000, MalaysiaDepartment of Accounting and Finance, UCSI University Kuala Lumpur, 1 Jalan Menara Gading, Taman Connaught, Cheras Kuala Lumpur 56000, MalaysiaInstitute of Energy Policy and Research, Universiti Tenaga Nasional, Jalan Ikram-Uniten, Kajang 43000, MalaysiaInstitute of Energy Policy and Research, Universiti Tenaga Nasional, Jalan Ikram-Uniten, Kajang 43000, MalaysiaThis study investigates the use of a non-linear autoregressive exogenous neural network (NARX) model to investigate the nexus between energy usability, economic indicators, and carbon dioxide (CO<sub>2</sub>) emissions in four Association of South East Asian Nations (ASEAN), namely Malaysia, Thailand, Indonesia, and the Philippines. Optimized NARX model architectures of 5-29-1, 5-19-1, 5-17-1, 5-13-1 representing the input nodes, hidden neurons and the output units were obtained from the series of models configured. Based on the relationship between the input variables, CO<sub>2</sub> emissions were predicted with a high correlation coefficient (R) > 0.9. and low mean square errors (MSE) of 3.92 × 10<sup>−21</sup>, 4.15 × 10<sup>−23</sup>, 2.02 × 10<sup>−19</sup>, 1.32 × 10<sup>−20</sup> for Malaysia, Thailand, Indonesia, and the Philippines, respectively. Coal consumption has the highest level of influence on CO<sub>2</sub> emissions in the four ASEAN countries based on the sensitivity analysis. These findings suggest that government policies in the four ASEAN countries should be more intensified on strategies to reduce CO<sub>2</sub> emissions in relationship with the energy and economic indicators.https://www.mdpi.com/2227-9717/8/12/1529ASEANCO<sub>2</sub> emissionsenergy consumptioneconomic indicatorgross domestic productNARX neural network
collection DOAJ
language English
format Article
sources DOAJ
author Siti Indati Mustapa
Freida Ozavize Ayodele
Bamidele Victor Ayodele
Norsyahida Mohammad
spellingShingle Siti Indati Mustapa
Freida Ozavize Ayodele
Bamidele Victor Ayodele
Norsyahida Mohammad
Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach
Processes
ASEAN
CO<sub>2</sub> emissions
energy consumption
economic indicator
gross domestic product
NARX neural network
author_facet Siti Indati Mustapa
Freida Ozavize Ayodele
Bamidele Victor Ayodele
Norsyahida Mohammad
author_sort Siti Indati Mustapa
title Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach
title_short Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach
title_full Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach
title_fullStr Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach
title_full_unstemmed Nexus between Energy Usability, Economic Indicators and Environmental Sustainability in Four ASEAN Countries: A Non-Linear Autoregressive Exogenous Neural Network Modelling Approach
title_sort nexus between energy usability, economic indicators and environmental sustainability in four asean countries: a non-linear autoregressive exogenous neural network modelling approach
publisher MDPI AG
series Processes
issn 2227-9717
publishDate 2020-11-01
description This study investigates the use of a non-linear autoregressive exogenous neural network (NARX) model to investigate the nexus between energy usability, economic indicators, and carbon dioxide (CO<sub>2</sub>) emissions in four Association of South East Asian Nations (ASEAN), namely Malaysia, Thailand, Indonesia, and the Philippines. Optimized NARX model architectures of 5-29-1, 5-19-1, 5-17-1, 5-13-1 representing the input nodes, hidden neurons and the output units were obtained from the series of models configured. Based on the relationship between the input variables, CO<sub>2</sub> emissions were predicted with a high correlation coefficient (R) > 0.9. and low mean square errors (MSE) of 3.92 × 10<sup>−21</sup>, 4.15 × 10<sup>−23</sup>, 2.02 × 10<sup>−19</sup>, 1.32 × 10<sup>−20</sup> for Malaysia, Thailand, Indonesia, and the Philippines, respectively. Coal consumption has the highest level of influence on CO<sub>2</sub> emissions in the four ASEAN countries based on the sensitivity analysis. These findings suggest that government policies in the four ASEAN countries should be more intensified on strategies to reduce CO<sub>2</sub> emissions in relationship with the energy and economic indicators.
topic ASEAN
CO<sub>2</sub> emissions
energy consumption
economic indicator
gross domestic product
NARX neural network
url https://www.mdpi.com/2227-9717/8/12/1529
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