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Forecasting COVID-19 impact on RWI/ISL container throughput index by using SARIMA models

Author

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  • Kaan Koyuncu
  • Leyla Tavacioğlu
  • Neslihan Gökmen
  • Umut Çelen Arican

Abstract

Maritime operators are facing their biggest challenge called Coronavirus (COVID-19) since the 2008 financial crisis. As part of the measures taken by the countries against the virus, the domino effect started with the breaks in the interconnected supply chain, like the spider web. The main purpose of this study is modeling the Institute of Shipping Economics and Logistics (ISL) and the Leibniz-Institut für Wirtschaftsforschung (RWI) Container Throughput Index with the time series, to reveal the relationship between the short-term forecast results and the COVID-19 seen in the first months of 2020. The deep effect of COVID-19 on maritime trade is investigated by forecasting the RWI/ISL Container Throughput Index in 89 major international container ports, including and excluding seasonal variations. The modeling process of the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Exponential Smoothing State Space Model (ETS) is explained. To evaluate SARIMA and ETS models’ performance, information criteria, and error measurements are calculated and compared. SARIMA model is found as more suitable model than ETS forecasting seasonally and working-day adjusted and original RWI/ISL. The results indicated that the SARIMA model is suitable and efficient for the forecasting of RWI/ISL. Three months’ forecasting results are showed that the decrease will continue.

Suggested Citation

  • Kaan Koyuncu & Leyla Tavacioğlu & Neslihan Gökmen & Umut Çelen Arican, 2021. "Forecasting COVID-19 impact on RWI/ISL container throughput index by using SARIMA models," Maritime Policy & Management, Taylor & Francis Journals, vol. 48(8), pages 1096-1108, November.
    • Handle: RePEc:taf:marpmg:v:48:y:2021:i:8:p:1096-1108
    DOI: 10.1080/03088839.2021.1876937
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    Citations

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    Cited by:

    1. Yang, Yang & Liu, Qing & Chang, Chia-Hsun, 2023. "China-Europe freight transportation under the first wave of COVID-19 pandemic and government restriction measures," Research in Transportation Economics, Elsevier, vol. 97(C).
    2. Zhao, Hong-Mei & He, Hong-Di & Lu, Kai-Fa & Han, Xiao-Long & Ding, Yi & Peng, Zhong-Ren, 2022. "Measuring the impact of an exogenous factor: An exponential smoothing model of the response of shipping to COVID-19," Transport Policy, Elsevier, vol. 118(C), pages 91-100.
    3. Ahmed Karam & Abdelrahman E. E. Eltoukhy & Ibrahim Abdelfadeel Shaban & El-Awady Attia, 2022. "A Review of COVID-19-Related Literature on Freight Transport: Impacts, Mitigation Strategies, Recovery Measures, and Future Research Directions," IJERPH, MDPI, vol. 19(19), pages 1-27, September.
    4. Huang, Dong & Grifoll, Manel & Sanchez-Espigares, Jose A. & Zheng, Pengjun & Feng, Hongxiang, 2022. "Hybrid approaches for container traffic forecasting in the context of anomalous events: The case of the Yangtze River Delta region in the COVID-19 pandemic," Transport Policy, Elsevier, vol. 128(C), pages 1-12.
    5. Zhao, Chuan & Li, Xin & Zuo, Min & Mo, Lipo & Yang, Changchun, 2022. "Spatiotemporal dynamic network for regional maritime vessel flow prediction amid COVID-19," Transport Policy, Elsevier, vol. 129(C), pages 78-89.
    6. Anqiang Huang & Xinjun Liu & Changrui Rao & Yi Zhang & Yifan He, 2022. "A New Container Throughput Forecasting Paradigm under COVID-19," Sustainability, MDPI, vol. 14(5), pages 1-20, March.

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