Forecast of Monthly Empty Container Throughput Based on Semi-parametric Linear Regression

摘要

Forecast of empty container throughput, especially the recent monthly throughput is an important reference for allocation of empty containers. An innovative statistical method is introduced in this paper. It takes the Hong Kong Port as an example, builds a semi-parametric linear regression model to forecast the recent monthly throughput of empty containers based on some relative statistical data from 2001 to 2008. By comparing the forecast results with the actual data in 2009, the semi-parametric linear regression is proved to be highly accurate, which demonstrates that the semi-parametric linear regression can be used to forecast the short-term monthly throughput of empty containers with appreciated high precision. This method can also be further applied in many other fields.