Structural break

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Linear regression with a structural break

In econometrics, a structural break, or structural change, is an unexpected shift in a time series that can lead to huge forecasting errors and unreliability of the model in general.[1] This issue was popularised by David Hendry.

Structural break tests[edit]

For a linear model with one known single break in mean, the Chow test is often used. If the single break in mean is unknown, then Hartley's test may be appropriate. Other challenges are where there are:

Case 1: a known number of unknown breaks in mean;
Case 2: an unknown number of (unknown) breaks in mean;
Case 3: breaks in variance.

The Chow test is not applicable for these situations;[1] however, for cases 1 and 2, the sup-Wald, sup-LM, and sup-LR tests developed by Andrews (1993, 2003)[2][3] may be used to test for parameter instability when the change points (the structural break locations) are unknown.[2][3] For a cointegration model, the Gregory–Hansen test (1996) is used for one unknown structural break,[4] and the Hatemi-J test (2006) is used for two unknown breaks.[5]

In general, the CUSUM (cumulative sum) and CUSUM-sq (CUSUM squared) tests can be used to test the constancy of the coefficients in a model. The bounds test can also be used.[6]

There are several statistical packages that can be used to find structural breaks, including R,[7] GAUSS, and Stata, among others.

More sophisticated model[edit]

The latest method has been used by Bai and Perron (2003) in which multiple structural breaks can be automatically detected from data.[8] The literature in this regard is very vast starting right from 1987 to 2010.[citation needed] Recently[when?] economists are going for both growth rate analysis and also econometric analysis in order to find break points[citation needed].

See also[edit]

References[edit]

  1. ^ a b Gujarati, Damodar (2007). Basic Econometrics. New Delhi: Tata McGraw-Hill. pp. 278–284. ISBN 0-07-066005-0. 
  2. ^ a b Andrews, D (July 1993). "Tests for Parameter Instability and Structural Change with Unknown Change Point". Econometrica. 61 (4): 821–856. doi:10.2307/2951764. Retrieved 22 August 2014. 
  3. ^ a b Andrews, D (January 2003). "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum" (PDF). Econometrica. 71 (1): 395–397. doi:10.1111/1468-0262.00405. Retrieved 22 August 2014. 
  4. ^ Gregory, Allan; Hansen, Bruce (1996). "Tests for Cointegration in Models with Regime and Trend Shifts". Oxford Bulletin of Economics and Statistics. 58 (3): 555–560. doi:10.1111/j.1468-0084.1996.mp58003008.x. 
  5. ^ Hacker, R. Scott; Hatemi-J, Abdulnasser (2006). "Tests for Causality between Integrated Variables Using Asymptotic and Bootstrap Distributions: Theory and Application". Applied Economics. 38 (15): 1489–1500. doi:10.1080/00036840500405763. 
  6. ^ Pesaran, M. H.; Shin, Y.; Smith, R. J. (2001). "Bounds testing approaches to the analysis of level relationships". Journal of Applied Econometrics. 16 (3): 289–326. doi:10.1002/jae.616. 
  7. ^ Kleiber, Christian; Zeileis, Achim (2008). Applied Econometrics with R. New York: Springer. pp. 169–176. ISBN 978-0-387-77316-2. 
  8. ^ Bai, Jushan; Perron, Pierre (2003). "Computation and Analysis of Multiple Structural Change Models". Journal of Applied Econometrics. 18 (1): 1–22. doi:10.1002/jae.659.