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Further Evidence on the Great Crash, the Oil Price Shock, and the Unit Root Hypothesis

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Abstract

Recently Perron (1989) has carried out tests of the unit root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil price shock. His analysis covers the Nelson-Plosser macroeconomic data series as well as a post-war quarter real GNP series. His tests reject the unit root null hypothesis for most of the series. This paper takes issue with the assumption used by Perron that the Great Crash and the oil price shock can be treated as exogenous events. A variation of Perron's test is considered in which the break point is estimated rather than fixed. We argue this test is more appropriate than Perron's, since it circumvents the problem of data-mining. The asymptotic distribution of the "estimated break point" test statistic is determined. The data series considered by Perron are reanalyzed using this test statistic. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependent innovations is investigated. In brief, by treating the break point as endogenous, we find that there is less evidence against the unit root hypothesis than Perron finds for many of the data series, but stronger evidence against it for several of the series, including the Nelson-Plosser industrial production, nominal GNP, and real GNP series.

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File URL: http://cowles.econ.yale.edu/P/cd/d09a/d0944.pdf
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Bibliographic Info

Paper provided by Cowles Foundation for Research in Economics, Yale University in its series Cowles Foundation Discussion Papers with number 944.

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Length: 52 pages
Date of creation: May 1990
Date of revision:
Publication status: Published in Journal of Business and Economic Statistics (July 1992), 10(3): 251-270
Handle: RePEc:cwl:cwldpp:944

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Keywords: Asymptotic distribution; break point; Gaussian process; macroeconomic time series; structural change; test statistic; time trend; trend stationary; unit root hypothesis; weak convergence;

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  1. 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.
  2. Peter C.B. Phillips, 1985. "Time Series Regression with a Unit Root," Cowles Foundation Discussion Papers 740R, Cowles Foundation for Research in Economics, Yale University, revised Feb 1986.
  3. 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.
  4. Mankiw, N. Gregory & Campbell, John, 1987. "Permanent and Transitory Components in Macroeconomic Fluctuations," Scholarly Articles 3207697, Harvard University Department of Economics.
  5. Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
  6. Peter C.B. Phillips & Sam Ouliaris & Joon Y. Park, 1988. "Testing for a Unit Root in the Presence of a Maintained Trend," Cowles Foundation Discussion Papers 880, Cowles Foundation for Research in Economics, Yale University.
  7. 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.
  8. Clark, Peter K, 1987. "The Cyclical Component of U.S. Economic Activity," The Quarterly Journal of Economics, MIT Press, vol. 102(4), pages 797-814, November.
  9. Ploberger, Werner & Kramer, Walter & Kontrus, Karl, 1989. "A new test for structural stability in the linear regression model," Journal of Econometrics, Elsevier, vol. 40(2), pages 307-318, February.
  10. Peter C.B. Phillips & Joon Y. Park, 1986. "Statistical Inference in Regressions with Integrated Processes: Part 1," Cowles Foundation Discussion Papers 811R, Cowles Foundation for Research in Economics, Yale University, revised Aug 1987.
  11. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
  12. Christiano, Lawrence J, 1992. "Searching for a Break in GNP," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(3), pages 237-50, July.
  13. Peter C.B. Phillips, 1988. "Reflections on Econometric Methodology," Cowles Foundation Discussion Papers 893, Cowles Foundation for Research in Economics, Yale University.
  14. Donald W.K. Andrews, 1990. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Cowles Foundation Discussion Papers 943, Cowles Foundation for Research in Economics, Yale University.
  15. Campbell, John & Mankiw, Gregory, 1987. "Are Output Fluctuations Transitory?," Scholarly Articles 3122545, Harvard University Department of Economics.
  16. Perron, Pierre, 1993. "The HUMP-Shaped Behavior of Macroeconomic Fluctuations," Empirical Economics, Springer, vol. 18(4), pages 707-27.
  17. 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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