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Container Throughput Modelling and Forecasting: An Empirical Dynamic Econometric Time Series Approach.

机译:集装箱吞吐量建模和预测:一种经验动态的计量经济学时间序列方法。

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摘要

Port policy makers rely on demand traffic forecasts to support the decisions related to operation and future port infrastructure investments. It is a challenge to match capacity to demand. On the one hand, they face the risk of costly excess capacity, and on the other hand, under-capacity causes loss of market share.;In addition, the volatility and uncertainty of the global economy, and, consequently, of the maritime trade and port sector impose a challenge to modelling and forecasting container throughput. The main research question of this thesis is which model to use to forecast the container throughput at the port level?.;The aim of the thesis is to provide an instrument to support stakeholders in making short-term operational decisions and long-term planning and investment decisions. This is achieved by developing quantitative models using a time series approach that analyses, identifies and quantifies the relationship between economic activity and container throughput at the port level.;Forecasting the number of TEUs at the port level in the short-term assists in the planning of the operational decisions such as the port capacity utilisation, loading and unloading planning, handling of containers and hinterland connections capacity. In comparison, the long-term forecasting is useful to assess the future infrastructure investment decisions. Application to other ports is feasible taking into account the specific characteristic of each port's location and the country's macroeconomic indicators.;Throughout the thesis, the analysis incorporates the 2008 financial crisis in the modelling process, which has the advantage of providing insight into the data generating process and the impact of the crisis. Moreover, the analysis identifies leading indicators with time lag that enable improving the monthly container throughput forecast. Combining different scenarios and the ARDL model provides reliable long term forecasts.;The findings show that for the short-term, the EU18 industrial confidence indicator and the index of industrial production are leading the container throughput at the Port of Antwerp. For the long-term, the elasticity of the container throughput in the Hamburg-Le Havre range to trade indices is about 1.4 on average.
机译:港口政策制定者依靠需求流量预测来支持与运营和未来港口基础设施投资有关的决策。使容量与需求匹配是一个挑战。一方面,它们面临着高昂的产能过剩的风险,另一方面,产能不足会导致市场份额的损失。此外,全球经济以及随之而来的海洋贸易的动荡和不确定性港口部门对集装箱吞吐量的建模和预测提出了挑战。本论文的主要研究问题是用于预测港口级别集装箱吞吐量的模型?。本论文的目的是提供一种工具,以支持利益相关者制定短期运营决策和长期计划,以及投资决策。这是通过使用时间序列方法开发定量模型来实现的,该方法可以分析,识别和量化港口级别的经济活动与集装箱吞吐量之间的关系。;在短期内预测港口级别的TEU数量有助于规划运营决策,例如港口容量利用,装卸计划,集装箱处理和内陆连接能力。相比之下,长期预测有助于评估未来的基础设施投资决策。考虑到每个港口所处位置的特定特征和该国的宏观经济指标,将其应用到其他港口是可行的。在整个论文中,该分析在建模过程中纳入了2008年的金融危机,其优点是可以提供对数据生成的洞察力过程和危机的影响。此外,该分析还可以识别具有时滞的领先指标,从而可以提高每月集装箱吞吐量的预测。结合不同的情景和ARDL模型可以提供可靠的长期预测。研究结果表明,就短期而言,EU18工业信心指标和工业生产指数正在引领安特卫普港的集装箱吞吐量。从长远来看,汉堡-勒阿弗尔范围内的集装箱吞吐量对贸易指数的弹性平均约为1.4。

著录项

  • 作者

    Rashed, Yasmine.;

  • 作者单位

    Universiteit Antwerpen (Belgium).;

  • 授予单位 Universiteit Antwerpen (Belgium).;
  • 学科 Economics.;Transportation.
  • 学位 Ph.D.
  • 年度 2016
  • 页码 137 p.
  • 总页数 137
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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