Cointegration versus least squares regression

被引:138
作者
Kulendran, N [1 ]
Witt, SF
机构
[1] Victoria Univ, Sch Appl Econ, Melbourne, Vic, Australia
[2] Univ Surrey, Sch Management Studies, Guildford GU2 5XH, Surrey, England
关键词
forecasting; least squares regression; cointegration; error correction model; ARIMA model; basic structural model; forecast accuracy;
D O I
10.1016/S0160-7383(00)00031-1
中图分类号
F [经济];
学科分类号
02 ;
摘要
Least squares regression models that explain international tourism demand have been shown to generate less accurate forecasts than the naive "no change" model. This study investigates if the reason for such mediocre forecasting performance is the failure to adopt recent developments in econometric methods in the areas of cointegration, error correction models, and diagnostic checking. the empirical results demonstrate that the forecasts produced using these recent methodological developments are more accurate than those generated by least squares regression, but that these newer econometric models still fail to outperform the "no change" model, as well as statistical time series models.
引用
收藏
页码:291 / 311
页数:21
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