## 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.

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 language | English |
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Place of Publication | Tilbug |

Publisher | CentER, Center for Economic Research |

Number of pages | 39 |

Volume | 2016-019 |

Publication status | Published - 2 May 2016 |

### Publication series

Name | CentER Discussion Paper |
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Volume | 2016-019 |

## Keywords

- structural change
- sup Wald test
- dynamic misspecification