Unit Root Tests are Useful for Selecting Forecasting Models

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Unit Root Tests are Useful for Selecting Forecasting Models

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Francis X. Diebold
Lutz Kilian

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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.

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Paper provided by New York University, Leonard N. Stern School of Business- in its series New York University, Leonard N. Stern School Finance Department Working Paper Seires with number 99-063.

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Date of creation: 18 Jan 1999
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Handle: RePEc:fth:nystfi:99-063

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Postal: U.S.A.; New York University, Leonard N. Stern School of Business, Department of Economics . 44 West 4th Street. New York, New York 10012-1126
Web page: http://w4.stern.nyu.edu/finance/
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Article
- Diebold, Francis X & Kilian, Lutz, 2000. "Unit-Root Tests Are Useful for Selecting Forecasting Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 265-73, July.
Paper
- Francis X. Diebold & Lutz Kilian, 1999. "Unit Root Tests Are Useful for Selecting Forecasting Models," NBER Working Papers 6928, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

Lutz Kilian, 1998. "Small-Sample Confidence Intervals For Impulse Response Functions," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 218-230, May. [Downloadable!] (restricted)
Christiano, Lawrence J. & Eichenbaum, Martin, 1990. "Unit roots in real GNP: Do we know, and do we care?," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 32, pages 7-61. [Downloadable!] (restricted)
Other versions:
- Lawrence J. Christiano & Martin Eichenbaum, 1989. "Unit roots in real GNP: do we know, and do we care?," Discussion Paper / Institute for Empirical Macroeconomics 18, Federal Reserve Bank of Minneapolis. [Downloadable!]
- Lawrence J. Christiano & Martin Eichenbaum, 1990. "Unit roots in real GNP: do we know, and do we care?," Working Paper Series, Macroeconomic Issues 90-2, Federal Reserve Bank of Chicago.
- Lawrence J. Christiano & Martin Eichenbaum, 1989. "Unit Roots in Real GNP: Do We Know, and Do We Care?," NBER Working Papers 3130, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Rudebusch, Glenn D, 1993. "The Uncertain Unit Root in Real GNP," American Economic Review, American Economic Association, vol. 83(1), pages 264-72, March. [Downloadable!] (restricted)
Other versions:
- Glenn D. Rudebusch, 1992. "The uncertain unit root in real GNP," Finance and Economics Discussion Series 193, Board of Governors of the Federal Reserve System (U.S.).
Ng, S. & Perron, P., 1994. "Unit Root Tests ARMA Models with Data Dependent Methods for the Selection of the Truncation Lag," Cahiers de recherche 9423, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
Other versions:
- Ng, S. & Perron, P., 1994. "Unit Root Tests ARMA Models with Data Dependent Methods for the Selection of the Truncation Lag," Cahiers de recherche 9423, Universite de Montreal, Departement de sciences economiques. [Downloadable!]
John Y. Campbell & Pierre Perron, 1991. "Pitfalls and Opportunities: What Macroeconomists Should Know About Unit Roots," NBER Technical Working Papers 0100, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Other versions:
- Campbell, J.Y. & Perron, P., 1991. "Pitfalls and Opportunities: What Macroeconomics should know about unit roots," Papers 360, Princeton, Department of Economics - Econometric Research Program.
Eugene Canjels & Mark W. Watson, 1997. "Estimating Deterministic Trends In The Presence Of Serially Correlated Errors," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 184-200, May. [Downloadable!] (restricted)
Zivot, Eric & Andrews, Donald W K, 1992. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 251-70, July.
Other versions:
- Eric Zivot & Donald W.K. Andrews, 1990. "Further Evidence on the Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Cowles Foundation Discussion Papers 944, Cowles Foundation, Yale University. [Downloadable!]
- Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and Long-Horizon Forecasting," NBER Technical Working Papers 0217, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Other versions:
- Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and Long-Horizon Forecasting," IMF Working Papers 97/61, International Monetary Fund.
- Peter F. Christoffersen & Francis X. Diebold, 1997. "Cointegration and long-horizon forecasting," Working Papers 97-14, Federal Reserve Bank of Philadelphia. [Downloadable!]
- Christoffersen, Peter F & Diebold, Francis X, 1998. "Cointegration and Long-Horizon Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 450-58, October.
Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-36, July. [Downloadable!] (restricted)
Other versions:
- Graham Elliott & Thomas J. Rothenberg & James H. Stock, 1992. "Efficient Tests for an Autoregressive Unit Root," NBER Technical Working Papers 0130, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Leybourne, S J & McCabe, B P M, 1994. "A Consistent Test for a Unit Root," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 157-66, April.
Stock, James H., 1986. "Unit roots, structural breaks and trends," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 46, pages 2739-2841 Elsevier. [Downloadable!] (restricted)
Diebold, Francis X & Senhadji, Abdelhak S, 1996. "The Uncertain Unit Root in Real GNP: Comment," American Economic Review, American Economic Association, vol. 86(5), pages 1291-98, December. [Downloadable!] (restricted)
Franses, Philip Hans & Kleibergen, Frank, 1996. "Unit roots in the Nelson-Plosser data: Do they matter for forecasting?," International Journal of Forecasting, Elsevier, vol. 12(2), pages 283-288, June. [Downloadable!] (restricted)
Andrews, Donald W K & Chen, Hong-Yuan, 1994. "Approximately Median-Unbiased Estimation of Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(2), pages 187-204, April.
Mehmet Caner & Lutz Kilian, 1999. "Size Distortions of Tests of the Null Hypothesis of Stationarity: Evidence and Implications for Applied Work," Computing in Economics and Finance 1999 511, Society for Computational Economics. [Downloadable!]
Stock, James H, 1996. "VAR, Error Correction and Pretest Forecasts at Long Horizons," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 685-701, November.
James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)

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