Structural Break Tests Robust to Regression Misspecification

Alaa Abi Morshed, E. Andreou, Otilia Boldea

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Abstract

Structural break tests developed in the literature for regression models are sensitive to model misspecification. We show - analytically and through simulations - that the sup Wald test for breaks in the conditional mean and variance of a time series process exhibits severe size distortions when the conditional mean dynamics are misspecified. We also show that the sup Wald test for breaks in the unconditional mean and variance does not have the same size distortions, yet benefits from similar power to its conditional counterpart.
Hence, we propose using it as an alternative and complementary test for breaks. While the conditional tests based on dynamic regression models detect breaks in the mean and variance of the US unemployment growth and interest rate growth series around the Great Moderation, the evidence for these breaks disappears when using the unconditional tests. Therefore, there is no evidence of long-run mean or volatility shifts in unemployment growth and interest rate growth.
Original languageEnglish
Place of PublicationTilbug
PublisherCentER, Center for Economic Research
Number of pages39
Volume2016-019
Publication statusPublished - 2 May 2016

Publication series

NameCentER Discussion Paper
Volume2016-019

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Keywords

  • structural change
  • sup Wald test
  • dynamic misspecification

Cite this

Abi Morshed, A., Andreou, E., & Boldea, O. (2016). Structural Break Tests Robust to Regression Misspecification. (CentER Discussion Paper; Vol. 2016-019). Tilbug: CentER, Center for Economic Research.