Unit Root Tests Are Useful for Selecting Forecasting Models

Francis Diebold and Lutz Kilian

No 6928, NBER Working Papers from National Bureau of Economic Research, Inc

Abstract: 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.

JEL-codes: C1 (search for similar items in EconPapers)
Date: 1999-02
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: EFG AP
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Citations: View citations in EconPapers (17)

Published as Diebold, Francis X. and Lutz Kilian. "Unit-Root Tests Are Useful For Selecting Forecasting Models," Journal of Business and Economic Statistics, 2000, v18(3,Jul), 265-273.

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Journal Article: Unit-Root Tests Are Useful for Selecting Forecasting Models (2000)
Working Paper: Unit Root Tests are Useful for Selecting Forecasting Models (1999)
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