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Measuring the impact of an exogenous factor: An exponential smoothing model of the response of shipping to COVID-19

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  • Zhao, Hong-Mei
  • He, Hong-Di
  • Lu, Kai-Fa
  • Han, Xiao-Long
  • Ding, Yi
  • Peng, Zhong-Ren

Abstract

Following the outbreak of the COVID-19 pandemic, various lockdown strategies restrained global economic growth bringing a significant decline in maritime transportation. However, the previous studies have not adequately recognized the specific impacts of COVID-19 on maritime transportation. In this study, a series of analyses of the Baltic Dry Index (BDI), the China Coastal Bulk Freight Index (CCBFI) and of container throughputs with and without the impact of COVID-19 were carried out to assess changing trends in dry bulk and container transportation. The results show that global dry bulk transportation was largely affected by lockdown policies in the second month during COVID-19, and BDI presented a year-on-year decrease of approximately 35.5% from 2019 to 2020. The CCBFI showed an upward trend in the second month during COVID-19, one month ahead of the BDI. The container throughputs at Shanghai Port, the Ports of Hong Kong, the Ports of Singapore and the Ports of Los Angeles from 2019 to 2020 presented the largest year-on-year drops of approximately 19.6%, 7.1%, 10.6% and 30.9%, respectively. In addition, the authors developed exponential smoothing models of BDI, CCBFI, and container transportation, and calculated the percentage prediction error between the observed and predicted values to examine the impact of exogenous effects on the shipping industry due to the outbreak of COVID-19. The results are consistent with the conclusions obtained from the comparison of BDI, CCBFI, and container transportation during the same period in 2020 and 2019. Finally, on the basis of the findings, smart shipping and special support policies are proposed to reduce the negative impacts of COVID-19.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:trapol:v:118:y:2022:i:c:p:91-100
    DOI: 10.1016/j.tranpol.2022.01.015
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    Cited by:

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    4. 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).
    5. Sakawa, Hideaki & Watanabel, Naoki, 2023. "The impact of the COVID-19 outbreak on Japanese shipping industry: An event study approach," Transport Policy, Elsevier, vol. 130(C), pages 130-140.
    6. 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.
    7. Serkan Karakas & Mehmet Kirmizi & Huseyin Gencer & Kevin Cullinane, 2024. "A resilience assessment model for dry bulk shipping supply chains: the case of the Ukraine grain corridor," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(3), pages 391-413, September.
    8. 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.

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