Premium
Forecasting with preliminary data
Author(s) -
Ghosh Sucharita,
Lien Donald
Publication year - 1997
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/(sici)1099-131x(199712)16:7<463::aid-for670>3.0.co;2-q
Subject(s) - benchmark (surveying) , bivariate analysis , autoregressive conditional heteroskedasticity , econometrics , forecast error , computer science , forecast verification , economics , machine learning , volatility (finance) , geodesy , geography
Abstract 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. © 1997 John Wiley & Sons, Ltd.