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Deterministic vs. Stochastic Trend in U.S. GNP, Yet Again

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  • Francis X. Diebold
  • Abdelhak S. Senhadji

Abstract

A sleepy consensus has emerged that U.S. GNP data are uninformative as to whether trend is better described as deterministic or stochastic. Although the distinction is not critical in some contexts, it is important for point forecasting, because the two models imply very different long-run dynamics and hence different long-run forecasts. We argue that, even for the famously recalcitrant GNP series, unit root tests over long spans can be informative. Our results make clear that uncritical repetition of the `we don't know, and we don't care' mantra is just as scientifically irresponsible as blind adoption of the view that `all macroeconomic series are difference-stationary,' or the view that `all macroeconomic series are trend-stationary.' There is simply no substitute for serious, case- by-case analysis.

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Bibliographic Info

Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 5481.

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Date of creation: Mar 1996
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Publication status: published as American Economic Review, 86, 1291-1298 (1996).
Handle: RePEc:nbr:nberwo:5481

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  1. 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.
  2. Balke, Nathan S & Gordon, Robert J, 1989. "The Estimation of Prewar Gross National Product: Methodology and New Evidence," Journal of Political Economy, University of Chicago Press, vol. 97(1), pages 38-92, February.
  3. 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.
  4. 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.
  5. Zelhorst, Dick & de Haan, Jakob, 1994. "The Nonstationarity of Aggregate Output: Some Additional International Evidence," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(1), pages 23-33, February.
  6. Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
  7. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
  8. Stock, James H & Watson, Mark W, 1988. "Variable Trends in Economic Time Series," Journal of Economic Perspectives, American Economic Association, vol. 2(3), pages 147-74, Summer.
  9. DeJong, David N & Whiteman, Charles H, 1991. "The Case for Trend-Stationarity Is Stronger Than We Thought," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 6(4), pages 413-21, Oct.-Dec..
  10. Francis X. Diebold & Glenn D. Rudebusch, 1988. "Long memory and persistence in aggregate output," Finance and Economics Discussion Series 7, Board of Governors of the Federal Reserve System (U.S.).
  11. Meese, Richard & Geweke, John, 1984. "A Comparison of Autoregressive Univariate Forecasting Procedures for Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(3), pages 191-200, July.
  12. 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.
  13. Hall, Alastair R, 1994. "Testing for a Unit Root in Time Series with Pretest Data-Based Model Selection," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(4), pages 461-70, October.
  14. Rudebusch, Glenn D, 1993. "The Uncertain Unit Root in Real GNP," American Economic Review, American Economic Association, vol. 83(1), pages 264-72, March.
  15. Stock, James H. & Watson, Mark W., 1986. "Does GNP have a unit root?," Economics Letters, Elsevier, vol. 22(2-3), pages 147-151.
  16. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
  17. Graham Elliott, 1998. "On the Robustness of Cointegration Methods when Regressors Almost Have Unit Roots," Econometrica, Econometric Society, vol. 66(1), pages 149-158, January.
  18. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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Cited by:
  1. Ruxandra Prodan, 2004. "Potential Pitfalls in Determining Multiple Structural Changes with an Application to Purchasing Power Parity," Econometric Society 2004 North American Summer Meetings 90, Econometric Society.
  2. Valentina Corradi & Norman R. Swanson, 2003. "The Effect of Data Transformation on Common Cycle, Cointegration and Unit Root Tests: Monte Carlo Results and a Simple Test," Departmental Working Papers 200322, Rutgers University, Department of Economics.
  3. Victor Zarnowitz & Ataman Ozyildirim, 2001. "Time Series Decomposition and Measurement of Business Cycles, Trends and Growth Cycles," Economics Program Working Papers 01-03, The Conference Board, Economics Program.
  4. Guillaume Chevillon, 2004. ""Weak" trends for inference and forecasting in finite samples," Documents de Travail de l'OFCE 2004-12, Observatoire Francais des Conjonctures Economiques (OFCE).

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