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Forecasting with preliminary data
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DOI：10.1002/(SICI)1099-131X(199712)16:7<463::AID-FOR670>3.3.CO;2-H.png)
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摘要
En 中文
This paper examines several methods to forecast revised US trade balance figures by incorporating preliminary data. Two benchmark forecasts are considered: one ignoring the preliminary data and the other applying a combination approach; with the second outperforming the first. Competing models include a bivariate AR error-correction model and a bivariate AR error-correction model with GARCH effects. The forecasts from the latter model outperforms the combination benchmark for the one-step forecast case only. A restricted AR error-correction model with GARCH effects is discovered to provide the best forecasts. (C) 1997 John Wiley & Sons, Ltd.
Keyword:
preliminary data
revised data
vector autoregression
error correction
generalized autoregressive conditional heteroscedasticity
mean squared error
mean absolute error
