Unit Root Tests Are Useful for Selecting Forecasting Models / Francis X. Diebold, Lutz Kilian.

Format:

Book

Author/Creator:

Diebold, Francis X.

Contributor:

National Bureau of Economic Research.

Kilian, Lutz.

Series:

Working Paper Series (National Bureau of Economic Research) no. w6928.

NBER working paper series no. w6928

Language:

English

Physical Description:

1 online resource: illustrations (black and white);

Place of Publication:

Cambridge, Mass. National Bureau of Economic Research 1999.

Summary:

We study the usefulness of 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. Forecasters face three choices: 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.

Notes:

Print version record

February 1999.