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Testing for Structural Breaks at Unknown Time: A Steeplechase

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  • Makram El-Shagi

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  • Sebastian Giesen

    ()

Abstract

This paper analyzes the role of common data problems when identifying structural breaks in small samples. Most notably, we survey small sample properties of the most commonly applied endogenous break tests developed by Brown et al. (J R Stat Soc B 37:149–163, 1975 ) and Zeileis (Stat Pap 45(1):123–131, 2004 ), Nyblom (J Am Stat Assoc 84(405):223–230, 1989 ) and Hansen (J Policy Model 14(4):517–533, 1992 ), and Andrews et al. (J Econ 70(1):9–38, 1996 ). Power and size properties are derived using Monte Carlo simulations. We find that the Nyblom test is on par with the commonly used F type tests in a small sample in terms of power. While the Nyblom test’s power decreases if the structural break occurs close to the margin of the sample, it proves far more robust to nonnormal distributions of the error term that are found to matter strongly in small samples although being irrelevant asymptotically for all tests that are analyzed in this paper. Copyright Springer Science+Business Media, LLC. 2013

Suggested Citation

  • Makram El-Shagi & Sebastian Giesen, 2013. "Testing for Structural Breaks at Unknown Time: A Steeplechase," Computational Economics, Springer;Society for Computational Economics, vol. 41(1), pages 101-123, January.
  • Handle: RePEc:kap:compec:v:41:y:2013:i:1:p:101-123
    DOI: 10.1007/s10614-011-9271-1
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    1. Ploberger, Werner & Krämer;, Walter, 1990. "The Local Power of the CUSUM and CUSUM of Squares Tests," Econometric Theory, Cambridge University Press, vol. 6(03), pages 335-347, September.
    2. Diebold, Francis X. & Chen, Celia, 1996. "Testing structural stability with endogenous breakpoint A size comparison of analytic and bootstrap procedures," Journal of Econometrics, Elsevier, vol. 70(1), pages 221-241, January.
    3. Lown, Cara & Morgan, Donald P., 2006. "The Credit Cycle and the Business Cycle: New Findings Using the Loan Officer Opinion Survey," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 38(6), pages 1575-1597, September.
    4. Panagiotis Mantalos & Ghazi Shukur, 2007. "The Robustness of the RESET Test to Non-Normal Error Terms," Computational Economics, Springer;Society for Computational Economics, vol. 30(4), pages 393-408, November.
    5. Achim Zeileis, 2005. "A Unified Approach to Structural Change Tests Based on ML Scores, F Statistics, and OLS Residuals," Econometric Reviews, Taylor & Francis Journals, vol. 24(4), pages 445-466.
    6. Zeileis, Achim & Kleiber, Christian & Kramer, Walter & Hornik, Kurt, 2003. "Testing and dating of structural changes in practice," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 109-123, October.
    7. Kwiatkowski, Denis & Phillips, Peter C. B. & Schmidt, Peter & Shin, Yongcheol, 1992. "Testing the null hypothesis of stationarity against the alternative of a unit root : How sure are we that economic time series have a unit root?," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 159-178.
    8. Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996. "Optimal changepoint tests for normal linear regression," Journal of Econometrics, Elsevier, vol. 70(1), pages 9-38, January.
    9. Jushan Bai & Serena Ng, 2005. "Tests for Skewness, Kurtosis, and Normality for Time Series Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 23, pages 49-60, January.
    10. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    11. Bai, Jushan, 1997. "Estimating Multiple Breaks One at a Time," Econometric Theory, Cambridge University Press, vol. 13(03), pages 315-352, June.
    12. Margaret M. McConnell & Gabriel Perez-Quiros, 2000. "Output fluctuations in the United States: what has changed since the early 1980s?," Proceedings, Federal Reserve Bank of San Francisco, issue Mar.
    13. Fatih Guvenen, 2009. "A Parsimonious Macroeconomic Model for Asset Pricing," Econometrica, Econometric Society, vol. 77(6), pages 1711-1750, November.
    14. Herwartz, Helmut & Reimers, Hans-Eggert, 2001. "Empirical modeling of the DEM/USD and DEM/JPY foreign exchange rate: Structural shifts in GARCH-models and their implications," SFB 373 Discussion Papers 2001,83, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    15. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    16. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    17. Hansen, Bruce E., 1992. "Testing for parameter instability in linear models," Journal of Policy Modeling, Elsevier, vol. 14(4), pages 517-533, August.
    18. Zeileis, Achim & Shah, Ajay & Patnaik, Ila, 2010. "Testing, monitoring, and dating structural changes in exchange rate regimes," Computational Statistics & Data Analysis, Elsevier, vol. 54(6), pages 1696-1706, June.
    19. Michel Juillard & Charles Freedman & Dmitry Korshunov & Douglas Laxton & Ondrej Kamenik & Ioan Carabenciov & Igor Ermolaev & Jared Laxton, 2008. "A Small Quarterly Multi-Country Projection Model with Financial-Real Linkages and Oil Prices," IMF Working Papers 08/280, International Monetary Fund.
    20. Achim Zeileis, 2004. "Alternative boundaries for CUSUM tests," Statistical Papers, Springer, vol. 45(1), pages 123-131, January.
    21. Hansen, Bruce E, 1997. "Approximate Asymptotic P Values for Structural-Change Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 60-67, January.
    22. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    23. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    24. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    25. Engle, Robert F. & Mustafa, Chowdhury, 1992. "Implied ARCH models from options prices," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 289-311.
    26. Luger, Richard, 2001. "A modified CUSUM test for orthogonal structural changes," Economics Letters, Elsevier, vol. 73(3), pages 301-306, December.
    27. Stock, James H & Watson, Mark W, 1996. "Evidence on Structural Instability in Macroeconomic Time Series Relations," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(1), pages 11-30, January.
    28. Ploberger, Werner & Kramer, Walter, 1992. "The CUSUM Test with OLS Residuals," Econometrica, Econometric Society, vol. 60(2), pages 271-285, March.
    29. Dufour, Jean-Marie & Ghysels, Eric, 1996. "Editors' introduction recent developments in the econometrics of structural change," Journal of Econometrics, Elsevier, vol. 70(1), pages 1-8, January.
    30. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2010. "A First Look on the New Halle Economic Projection Model," IWH Discussion Papers 6/2010, Halle Institute for Economic Research (IWH).
    31. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    32. Jarque, Carlos M. & Bera, Anil K., 1980. "Efficient tests for normality, homoscedasticity and serial independence of regression residuals," Economics Letters, Elsevier, vol. 6(3), pages 255-259.
    33. Giesen, Sebastian & Holtemöller, Oliver & Scharff, Juliane & Scheufele, Rolf, 2012. "The Halle Economic Projection Model," Economic Modelling, Elsevier, vol. 29(4), pages 1461-1472.
    34. Breitung, Jorg, 2002. "Nonparametric tests for unit roots and cointegration," Journal of Econometrics, Elsevier, vol. 108(2), pages 343-363, June.
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    Cited by:

    1. Karfakis, Costas, 2013. "Credit and business cycles in Greece: Is there any relationship?," Economic Modelling, Elsevier, vol. 32(C), pages 23-29.
    2. Holtemöller Oliver, 2013. "Explosive Preisentwicklung und spekulative Blasen auf Rohstoffmärkten / Explosive behavior and speculative bubbles on commodity markets," ORDO. Jahrbuch für die Ordnung von Wirtschaft und Gesellschaft, De Gruyter, vol. 64(1), pages 405-420, January.
    3. Ivan Mendieta-Muñoz, 2014. "Is there any relationship between the rates of interest and profit in the U.S. economy?," Studies in Economics 1416, School of Economics, University of Kent.

    More about this item

    Keywords

    Structural breaks; Small sample Monte Carlo study; Size adjusted power; C12; C15;

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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