貨櫃運量之準確預測可作為政府與(擴)建港埠貨櫃碼頭及投資相關內陸運輸系統之參據，尤其是以進出口貿易為導向之國家更形重要。國內過去在預測貨櫃運量時多採迴歸模式，惟其忽略迴歸分析之基本假設，致使迴歸模式參數校估結果有易偏誤或無交率，預測誤差往往高出百分之四十以上。本文檢定GAUSS-Markov定理之迴歸基本假設，利用Cochrane-Orcutt方法消防殘差自我相關性，建立臺灣地區貨櫃運量之預測模式。本模式預測民國74年至78年貨櫃運量，與實際貨櫃運量比較發現，預測誤差均低於百分之九。由本文模式預測民國84年及89年臺灣地區之貨櫃運量分別達1,037萬TEU及1,761萬TEU，可供規劃單位參考。

Precisely forecasting the container demand usually plays a decisive role on government investment in constructing port container wharves and inland transportation systems. It is particularly important for an import/export oriented country. Regression models are commonly used in forecasting the container demand in Taiwan Area, however, such models often violate the basic assumptions of regression analysis which may lead to biased and/or inefficient estimations. Forecast errors are therefore often greater than 40%. This paper constructs a regression model by investigating the vital assumptions. Details of the model estimation procedures are presented. In order to prove the forecasting power, the statistical data of 1985-1989 container volumes in Taiwan Area are used to compare with the theoretical values forecasted by this model and by other previous models. It shows that the maximum forecast error of this model is less than 9%, which is superior to the previous models.