Structural break

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Linear regression with a structural break

A structural break is a concept in econometrics. A structural break appears when we see an unexpected shift in a (macroeconomic) time series. This can lead to huge forecasting errors and unreliability of the model in general.[1] This issue was popularised by David Hendry.

Test[edit]

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.[2]

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:

  • a known number of unknown breaks in mean;
  • an unknown number of (unknown) breaks in mean;
  • breaks in variance.

The Chow test is not applicable for these situations.[1]

For nonstationary process, there are many more challenges. For a cointegration model, the Gregory and Hansen test (1996) is used for one unknown structural break,[3] and the Hatemi-J test (2006) is used for two unknown breaks.[4]

There are several programs that can be used to find structural breaks, including R (open source) and GAUSS.

More sophisticated model[edit]

If there are too many unknown breaks, then just assume the parameter to be time varying.

The latest method has been used by Bai and Perron (2003) in which multiple structural breaks can be automatically detected from data.[5] The literature in this regard is very vast starting right from 1987 to 2010.[citation needed] Recently economists are going for both growth rate analysis and also econometric analysis in order to find break points one such way has been recommended by Chandan Mukherjee (2009)[full 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. ^ 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. 
  3. ^ 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. 
  4. ^ 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. 
  5. ^ 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.