Korea Trade Review (무역학회지)

Korea Trade Research Association (한국무역학회)
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A Study on the Prediction of the World Seaborne Trade Volume through the Exponential Smoothing Method and Seemingly Unrelated Regression Model

지수평활법과 SUR 모형을 통한 세계 해상물동량 예측 연구

  • Ahn, Young-Gyun (Maritime Industry Research Department, Korea Maritime Institute)
  • Received : 2019.03.04
  • Accepted : 2019.04.16
  • Published : 2019.04.30
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Abstract

This study predicts the future world seaborne trade volume with econometrics methods using 23-year time series data provided by Clarksons. For this purpose, this study uses simple regression analysis, exponential smoothing method and seemingly unrelated regression model (SUR Model). This study is meaningful in that it predicts worldwide total seaborne trade volume and seaborne traffic in four major items (container, bulk, crude oil, and LNG) from 2019 to 2023 as there are few prior studies that predict future seaborne traffic using recent data. It is expected that more useful references can be provided to trade related workers if the analysis period was increased and additional variables could be included in future studies.

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References

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