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Multivariate autoregressive models for forecasting seaborne trade flows

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  • Veenstra, Albert W.
  • Haralambides, Hercules E.

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  • Veenstra, Albert W. & Haralambides, Hercules E., 2001. "Multivariate autoregressive models for forecasting seaborne trade flows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 37(4), pages 311-319, August.
    • Handle: RePEc:eee:transe:v:37:y:2001:i:4:p:311-319
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    Citations

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    Cited by:

    1. Zaili Yang & Esin Erol Mehmed, 2019. "Artificial neural networks in freight rate forecasting," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 390-414, September.
    2. Yasmine Rashed & Hilde Meersman & Eddy Van de Voorde & Thierry Vanelslander, 2017. "Short-term forecast of container throughout: An ARIMA-intervention model for the port of Antwerp," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 19(4), pages 749-764, December.
    3. Hercules E. Haralambides & Helen Thanopoulou, 2014. "The Economic Crisis of 2008 and World Shipping: Unheeded Warnings," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 64(2), pages 5-13, April-Jun.
    4. Moon, Sang & Koo, Won W., 2006. "Effects of the Panama Canal on U.S. Competitiveness on the World Soybean Market," 2006 Annual meeting, July 23-26, Long Beach, CA 21418, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    5. Dariusz Bernacki & Christian Lis, 2021. "Forecasting the Cargo Throughput for Small and Medium-sized Ports: Multi-stage Approach with Reference to the Multi-port System," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 208-228.
    6. Heij, C. & Knapp, S., 2012. "Dynamics in the dry bulk market," Econometric Institute Research Papers EI 2012-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    7. Taewoon Kong & Dongguen Choi & Geonseok Lee & Kichun Lee, 2021. "Air Pollution Prediction Using an Ensemble of Dynamic Transfer Models for Multivariate Time Series," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
    8. Yang, Zhongzhen & Jiang, Zhenfeng & Notteboom, Theo & Haralambides, Hercules, 2019. "The impact of ship scrapping subsidies on fleet renewal decisions in dry bulk shipping," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 126(C), pages 177-189.
    9. Tsung-Chen Lee & Chia-Hsuan Wu & Paul T.-W. Lee, 2010. "Impacts of the ECFA on seaborne trade volume and policy development for shipping and port industry in Taiwan," Maritime Policy & Management, Taylor & Francis Journals, vol. 38(2), pages 169-189, December.
    10. Di Zhang & Xinyuan Li & Chengpeng Wan & Jie Man, 2024. "A novel hybrid deep-learning framework for medium-term container throughput forecasting: an application to China’s Guangzhou, Qingdao and Shanghai hub ports," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 26(1), pages 44-73, March.
    11. 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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