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Univariate Forecasting Comparisons: The Case of the Spanish Automobile Industry
Author(s) -
GARCÍAFERRER A.,
DEL HOYO J.,
MARTÍNARROYO A. S.
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(199701)16:1<1::aid-for643>3.0.co;2-t
Subject(s) - univariate , autoregressive integrated moving average , econometrics , flexibility (engineering) , component (thermodynamics) , computer science , multivariate statistics , time series , statistics , economics , mathematics , machine learning , physics , thermodynamics
This paper investigates the forecasting ability of unobserved component models, when compared with the standard ARIMA univariate approach. A forecasting exercise is carried out with each method, using monthly time series of automobile sales in Spain. The accuracy of the different methods is assessed by comparing several measures of forecasting performance based on the out‐of‐sample predictions for various horizons, as well as different assumptions on the models’ parameters. Overall there seems little to choose between the methods in forecasting performance terms but the recursive unobserved component models provide greater flexibility for adaptive applications. © 1997 by John Wiley & Sons, Ltd.