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Long-Term Forecasting Models of Oil Demand Emerging from the Global Petrochemical Sector

Author

Listed:
  • Raed Al Mestneer

    (KAPSARC—King Abdullah Petroleum Studies and Research Center, Riyadh 11672, Saudi Arabia)

  • Carlo Andrea Bollino

    (KAPSARC—King Abdullah Petroleum Studies and Research Center, Riyadh 11672, Saudi Arabia
    Department of Economics, University of Perugia, 06123 Perugia, Italy)

Abstract

In the global energy mix by 2040, the growth in demand for oil and gas will be predominantly driven by the petrochemical sector across all regions of the world. The strong performance of this industry is anticipated to necessitate additional volumes of key feedstocks. Therefore, understanding the demand dynamics within the petrochemical sector is crucial for policy makers and industry stakeholders to make informed decisions regarding economic diversification, economic planning, and environmental sustainability. However, there is a notable lack of existing literature that explicitly addresses comprehensive regional and product-level demand modeling for petrochemical feedstocks. In this context, this study aims to estimate the demand for four main petrochemical feedstocks (Naphtha, Ethane, Liquefied Petroleum Gas (LPG), and other petrochemical feedstocks) across eight regions of the world. By estimating a total of 30 equations for price and income elasticities of demand in both the short and long term, the study provides detailed insights into the factors driving demand across different regions. The results demonstrate the robustness of the model, with good econometric properties and significant coefficients. In-sample regional simulations revealed small percentage errors across all regional equations, highlighting the model’s accuracy in tracking historical data. For each of the four feedstocks, an aggregate world equation—in other words, one single econometric world equation for each of the four petrochemical feedstocks’ categories mentioned earlier—was also estimated and compared against the aggregation of the regional simulations, with the latter found to track the history of global petrochemical feedstock demand better in-sample than a single econometric world equation. Overall, the study offers valuable contributions to the existing literature by filling a gap in comprehensive demand modeling for petrochemical feedstocks. It underscores the importance of regional and product-level analyses in understanding global demand patterns and informing strategic decisions in the industry.

Suggested Citation

  • Raed Al Mestneer & Carlo Andrea Bollino, 2024. "Long-Term Forecasting Models of Oil Demand Emerging from the Global Petrochemical Sector," Energies, MDPI, vol. 17(20), pages 1-22, October.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:20:p:5046-:d:1496194
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    References listed on IDEAS

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    1. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
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