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The Efficiency of Long-Term Forecasting Model on Final Energy Consumption in Thailand’s Petroleum Industries Sector: Enriching the LT-ARIMAXS Model under a Sustainability Policy

Author

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  • Pruethsan Sutthichaimethee

    (Division of Energy Management Technology, School of Energy, Environment and Materials, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Road., Bang Mod, Thung Khru, Bangkok 10140, Thailand)

  • Kuskana Kubaha

    (Division of Energy Management Technology, School of Energy, Environment and Materials, King Mongkut’s University of Technology Thonburi, 126 Pracha Uthit Road., Bang Mod, Thung Khru, Bangkok 10140, Thailand)

Abstract

Presently, Thailand runs various sustainable development-based policies to boost the growth in economy, society, and environment. In this study, the economic and social growth was found to continuously increase and negatively deteriorate the environment at the same time due to a more massive final energy consumption in the petroleum industries sector than any other sectors. Therefore, it is necessary to establish national planning and it requires an effective forecasting model to support Thailand’s policy-making. This study aimed to construct a forecasting model for a final energy consumption prediction in Thailand’s petroleum industry sector for a longer-term (2018–2037) at a maximum efficiency from a certain class of methods. The Long Term-Autoregressive Integrated Moving Average with Exogeneous variables and Error Correction Mechanism model (LT-ARIMAXS model) (p, d, q, Xi, ECT ( t− 1) ) was adapted from the autoregressive and moving average model incorporating influential variables together in both long-term relationships to produce the best model for prediction performance. All relevant variables in the model are stationary at Level I(0) or Level I(1). In terms of the extraneous variables, they consist of per capita GDP, population growth, oil price, energy intensity, urbanization rate, industrial structure, and net exports. The study found that the variables used are the causal factors and stationary at the first difference as well as co-integrated. With such features, it reflects that the variables are influential over the final energy consumption. The LT-ARIMAXS model (2,1,2) determined a proper period ( t − i ) through a white noise process with the Q test statistical method. It shows that the LT-ARIMAXS model (2,1,2) does not generate the issues of heteroskedasticity, multicollinearity, and autocorrelation. The performance of LT-ARIMAXS model (2,1,2) was tested based on the mean absolute percentage error (MAPE) and the root mean square error (RMSE). The LT-ARIMAXS model (2,1,2) can predict the final energy consumption based on the Sustainable Development Plan for the 20 years from 2018 to 2037. The results showed that the final energy consumption continues to increase steadily by 121,461 ktoe in 2037. Furthermore, the findings present that the growth rate (2037/2017) increases by 109.8%, which is not in line with Thailand’s reduction policy. In this study, the MAPE was valued at 0.97% and RMSE was valued at 2.12% when compared to the other old models. Therefore, the LT-ARIMAXS model (2,1,2) can be useful and appropriate for policy-making to achieve sustainability.

Suggested Citation

  • Pruethsan Sutthichaimethee & Kuskana Kubaha, 2018. "The Efficiency of Long-Term Forecasting Model on Final Energy Consumption in Thailand’s Petroleum Industries Sector: Enriching the LT-ARIMAXS Model under a Sustainability Policy," Energies, MDPI, vol. 11(8), pages 1-18, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2063-:d:162649
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    Cited by:

    1. Pruethsan Sutthichaimethee & Chanintorn Jittawiriyanukoon, 2022. "Analyzing the Impact of Causal Factors on Political Management to Determine Sustainability Policy under Environmental Law: Enriching the Covariance-based SEMxi Model," International Journal of Energy Economics and Policy, Econjournals, vol. 12(4), pages 282-293, July.
    2. Wen-Hsien Tsai, 2019. "Modeling and Simulation of Carbon Emission-Related Issues," Energies, MDPI, vol. 12(13), pages 1-8, July.
    3. Pruethsan Sutthichaimethee & Harlida Abdul Wahab, 2021. "A Forecasting Model in Managing Future Scenarios to Achieve the Sustainable Development Goals of Thailand s Environmental Law: Enriching the Path Analysis-VARIMA-OVi Model," International Journal of Energy Economics and Policy, Econjournals, vol. 11(4), pages 398-411.
    4. Pruethsan Sutthichaimethee & Jindamas Sutthichaimethee & Chittinan Vutikorn & Danupon Ariyasajjakorn & Sirapatsorn Wongthongdee & Srochinee Siriwattana & Apinyar Chatchorfa & Borworn Khomchunsri, 2023. "Guidelines for Increasing the Effectiveness of Thailand s Sustainable Development Policy based on Energy Consumption: Enriching the Path-GARCH Model," International Journal of Energy Economics and Policy, Econjournals, vol. 13(1), pages 67-74, January.
    5. Pruethsan Sutthichaimethee & Sthianrapab Naluang, 2019. "The Efficiency of the Sustainable Development Policy for Energy Consumption under Environmental Law in Thailand: Adapting the SEM-VARIMAX Model," Energies, MDPI, vol. 12(16), pages 1-21, August.
    6. Pruethsan Sutthichaimethee & Chanintorn Jittawiriyanukoon, 2022. "The Impact of Causal Factors Relationship over the Changes in Future Scenario Management under the Sustainability Policy of Thailand," International Journal of Energy Economics and Policy, Econjournals, vol. 12(5), pages 36-46, September.

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