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Forecasting Hong Kong's Container Throughput: An Error-Correction Model

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  • Fung, Michael K

Abstract

A three-player oligopoly model is devised to capture the competitive interaction between operators of the Hong Kong container terminals, the Hong Kong midstream and the Singapore container terminals in providing container handling services. The oligopoly model is then estimated statistically and thereby the structural parameters can be identified. The results of the estimation confirm a substitutability between the services supplied by operators of different types (terminal versus midstream) and different locations (Hong Kong versus Singapore). Moreover, the model proposed in this article generates forecasts of demand for Hong Kong's container handling services that are more accurate than those reported by the government authority, and suggests an earlier construction of new terminals to meet future demand. Copyright © 2002 by John Wiley & Sons, Ltd.

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  • Fung, Michael K, 2002. "Forecasting Hong Kong's Container Throughput: An Error-Correction Model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 21(1), pages 69-80, January.
    • Handle: RePEc:jof:jforec:v:21:y:2002:i:1:p:69-80
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    Cited by:

    1. 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.
    2. banerjee, soumya, 2016. "Forecasting Australian port throughput: Lessons and Pitfalls in the era of Big Data," OSF Preprints ewtcf, Center for Open Science.
    3. 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.
    4. Javed Farhan & Ghim Ping Ong, 2018. "Forecasting seasonal container throughput at international ports using SARIMA models," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 20(1), pages 131-148, March.
    5. banerjee, soumya, 2016. "Forecasting Australian port throughput: Lessons and Pitfalls in the era of Big Data," OSF Preprints c3av2, Center for Open Science.
    6. Yi Xiao & Shouyang Wang & Ming Xiao & Jin Xiao & Yi Hu, 2017. "The Analysis for the Cargo Volume with Hybrid Discrete Wavelet Modeling," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 851-863, May.
    7. Lauri Lättilä & Olli-Pekka Hilmola, 2012. "Forecasting long-term demand of largest Finnish sea ports," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 4(1), pages 52-79.

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