## Abstract Methods of time series forecasting are proposed which can be applied automatically. However, they are not rote formulae, since they are based on a flexible philosophy which can provide several models for consideration. In addition it provides diverse diagnostics for qualitatively and qu
Interactions between large macro models and time series analysis
β Scribed by Clive W.J. Granger; Yongil Jeon
- Publisher
- John Wiley and Sons
- Year
- 2003
- Tongue
- English
- Weight
- 111 KB
- Volume
- 8
- Category
- Article
- ISSN
- 1076-9307
- DOI
- 10.1002/ijfe.196
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β¦ Synopsis
Abstract
Building large models, with little dynamics, was long considered to be an alternative to small dimensional time series models involving many lags. The advantages of one modelling methodology are compared to others; such as the size of the model, the use of economic theory, and simultaneity in specification. The question of how to evaluate the possible relative advantages of these alternatives is discussed. The conclusion is that in the future, time series models have to become larger, that is, involve more variables and that some lessons can be learnt from the construction of current large econometric models. Copyright Β© 2002 John Wiley & Sons, Ltd.
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This paper reviews the approach to forecasting based on the construction of ARIMA time series models. Recent developments in this area are surveyed, and the approach is related to other forecasting methodologies.