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Nonlinearly testing for a unit root in the presence of a break in the mean

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  • Gluschenko, Konstantin

Abstract

This paper deals with testing a time series with a structural break in its mean for a unit root when the break date is known. A nonlinear (with respect to coefficients) test equation is used, providing asymptotically efficient estimates. Finite-sample and quasi-asymptotic empirical distributions of the unit root test statistics are estimated, comparing them with those associated with the Perron-type equations. Asymptotic distributions of the nonlinear test statistics are found to be the Dickey-Fuller distributions. The nonlinear test proves to have more power than the test based on the linear model.

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File URL: http://mpra.ub.uni-muenchen.de/678/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 678.

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Date of creation: Aug 2004
Date of revision: Sep 2005
Handle: RePEc:pra:mprapa:678

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Keywords: structural break; nonlinear regression; nonstandard distribution;

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References

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  1. Lucrezia Reichlin & Peter Rappoport, 1989. "Segmented trends and non-stationary time series," ULB Institutional Repository, ULB -- Universite Libre de Bruxelles 2013/10169, ULB -- Universite Libre de Bruxelles.
  2. Kenneth D. West & Whitney K. Newey, 1995. "Automatic Lag Selection in Covariance Matrix Estimation," NBER Technical Working Papers, National Bureau of Economic Research, Inc 0144, National Bureau of Economic Research, Inc.
  3. Ulrich K. M¸ller & Graham Elliott, 2003. "Tests for Unit Roots and the Initial Condition," Econometrica, Econometric Society, Econometric Society, vol. 71(4), pages 1269-1286, 07.
  4. Alan Bartley, William & Lee, Junsoo & Strazicich, Mark C., 2001. "Testing the null of cointegration in the presence of a structural break," Economics Letters, Elsevier, Elsevier, vol. 73(3), pages 315-323, December.
  5. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, American Statistical Association, vol. 15(1), pages 60-67, January.
  6. MacKinnon, James G, 1996. "Numerical Distribution Functions for Unit Root and Cointegration Tests," Journal of Applied Econometrics, John Wiley & Sons, Ltd., John Wiley & Sons, Ltd., vol. 11(6), pages 601-18, Nov.-Dec..
  7. Phillips, P C B, 1987. "Time Series Regression with a Unit Root," Econometrica, Econometric Society, Econometric Society, vol. 55(2), pages 277-301, March.
  8. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, Econometric Society, vol. 57(6), pages 1361-1401, November.
  9. Vogelsang, T.I. & Perron, P., 1991. "Nonstationary and Level Shifts With An Application To Purchasing Power Parity," Papers, Princeton, Department of Economics - Econometric Research Program 359, Princeton, Department of Economics - Econometric Research Program.
  10. Evans, G B A & Savin, N E, 1981. "Testing for Unit Roots: 1," Econometrica, Econometric Society, Econometric Society, vol. 49(3), pages 753-79, May.
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Cited by:
  1. Gluschenko, Konstantin, 2011. "Price convergence and market integration in Russia," Regional Science and Urban Economics, Elsevier, Elsevier, vol. 41(2), pages 160-172, March.

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