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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/27136
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| Title: | Unit Root Tests are Useful for Selecting Forecasting Models |
| Authors: | Diebold, Francis X.
Kilian, Lutz |
| Issue Date: | 18-Jan-1999 |
| Series/Report no.: | FIN-99-063 |
| Abstract: | We study the usefulness of unit root tests as diagnostic tools for
selecting forecasting models. Difference stationary and trend stationary
models of economic and financial time series often imply very different
predictions, so deciding which model to use is tremendously important
for applied forecasters. We consider three strategies: always difference
the data, never difference, or use a unit-root pretest. We characterize
the predictive loss of these strategies for the canonical AR(1) process
with trend, focusing on the effects of sample size, forecast horizon,
and degree of persistence. We show that pretesting routinely improves
forecast accuracy relative to forecasts from models in differences, and
we give conditions under which pretesting is likely to improve forecast
accuracy relative to forecasts from models in levels. |
| URI: | http://hdl.handle.net/2451/27136 |
| Appears in Collections: | Finance Working Papers
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