Forecasting with Factors: The Accuracy of Timeliness
AbstractThis paper demonstrates that factor-based forecasts for key Australian macroeconomic series can outperform standard time-series benchmarks. In practice, however, the advantages of using large panels of data to construct the factors typically comes at the cost of using less timely series, thereby delaying when the forecasts can be made. To produce more timely forecasts it is possible to use a narrower data panel, though this will possibly result in less accurate factor estimates and so less accurate forecasts. We demonstrate this trade-off between accuracy and timeliness with out-of-sample forecasts. With the exception of only consumer price inflation, the forecasts do not become less accurate as they utilise less information by excluding less timely series. So while factor forecasts have large data requirements, we show that these should not prevent their practical use when timely forecasts are needed.
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Bibliographic InfoPaper provided by Reserve Bank of Australia in its series RBA Research Discussion Papers with number rdp2007-03.
Date of creation: Apr 2007
Date of revision:
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- E27 - Macroeconomics and Monetary Economics - - Macroeconomics: Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
- E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-05-12 (All new papers)
- NEP-ETS-2007-05-12 (Econometric Time Series)
- NEP-FOR-2007-05-12 (Forecasting)
- NEP-MAC-2007-05-12 (Macroeconomics)
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- Viktors Ajevskis & Gundars Davidsons, 2008. "Dynamic Factor Models in Forecasting Latvia's Gross Domestic Product," Working Papers 2008/02, Latvijas Banka.
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